I'm a Portuguese physics student starting his masters at Instituto Superior Técnico (Universidade de Lisboa).

This year I'm an exchange student at École Polytechnique Federale de Lausanne.

Besides my love for physics, I've always been interested in software and programming languages.

- Julia and Tensor Networks for Statistical Physics

I am a 15-year-old student, currently attending the City of London School. I have always had a deep interest in programming, first starting with Scratch when I was quite young, then moving onto Python, then finally, a few years ago, Julia. I have since presented at JuliaCon 2018, 2019 and 2020 and therefore have some experience with the language.

- Game development in Julia with GameZero.jl

I got PhD in 2015 about physics, particle physics, in Osaka university in Japan. From June 2021, I am a faculty member of International Professional University of Technology in Osaka in Japan. September 2018 - May 2021, a postdoc in Riken Brookhaven research center in the USA. October 2015 - August 2018, a postdoc in central china normal university in China. I am interested in application of machine learning on lattice QCD and physics. I published a book "Deep Learning and Physics" from springer.

- LatticeQCD.jl: Simulation of quantum gauge fields

- Open and interactive Computational Thinking with Julia and Pluto

PhD candidate at MIT AeroAstro

- Airborne Magnetic Navigation Enhanced with Neural Networks

I'm a *theoretical physicist* who is slowly evolved in an *algorithm researcher*. I specialize in mathematical methods in optics and mechanics, both classical and quantum paradigms. I'm currently signed at National Institute of Astrophysics, Optics and Electronics.

My current research projects are:

- Energy analysis of harmonic oscillators arrays
- Phase transitions under group theoretical approximation
- Quantum state tomography and unitary transformations
- Epistemological and ontological problems in quantum mechanics

- Julia as a framework for a Theoretical Physics PhD

Computer Science undergraduate student at the University of Pisa. Interested in functional programming, programming language theory, category theory, algebraic and symbolic computation, computability theory.

- Unleashing Algebraic Metaprogramming in Julia with Metatheory.jl

- Vectorized Query Evaluation in Julia

- UnitCommitment.jl: Security-Constrained Unit Commitment in JuMP

I am a grad student working in computational climate science at MIT. In the Julia world I've mostly been developing Oceananigans.jl. We're building a new climate written in Julia as part of the Climate Modeling Alliance project.

- Scaling of Oceananigans.jl on multi GPU and CPU systems

I am pursuing a Ph.D. in Computational Science and Engineering at Georgia Institute of Technology. Currently, my research is mainly focused on applications of deep learning in inverse problems and uncertainty quantification.

- InvertibleNetworks.jl - Memory efficient deep learning in Julia

Alissa is a first year research analyst at the Federal Reserve Bank of New York. She has a B.A. from Grinnell College, double-major in Economics and Computer Science.

- Modeling the Economy During the Pandemic

Hands-on Executive Consultant, ERP Implementation, AI Data Science, Machine Learning, Deep Learning, Business Intelligence, Flutter DART Angular Mobile apps.

- ML for GL, Machine Learning for General Ledger using Julia

I am interested in the intersection of mathematics and physiology. I am a computer science student at the University of Chicago on a gap year. I am working at Julia Computing on building surrogates of systems biological models for JuliaSim.

- Systems Biology in ModelingToolkit

Ander Gray received an MSci in Physics from Queen’s University Belfast (2017). Since then, he has been a PhD student at the University of Liverpool and Culham Centre for Fusion Energy, studying Uncertainty Quantification. For his thesis work, Ander researches methods for efficiently propagating uncertainty in radiation transport simulations. He is also involved in developing methods and software for calibrating and propagating uncertainties through computational models, in the form of imprecise probabilities.

- Set Propagation Methods in Julia: Techniques and Applications

- Modia – Modeling Multidomain Engineering Systems with Julia

Andrei Sarychev has taught Economics at the University of British Columbia and London School of Economics before joining the UK financial sector regulator. He devised the first scenario design framework for use in the UK stress-testing. At the Bank of England he developed a broad variety of analytical models for use in forecasting, policy analysis, and risk assessment. He also designed the European Central Bank's macro-financial platform. His research interests lie in modelling complex multivariate distributions and Bayesian methods.

- Vine-Copula package for the analysis of non-Gaussian processes

Chemical engineering

- Clapeyron.jl: An Extensible Implementation of Equations of State

Andrew Dolgert is a computational scientist at the University of Washington. He has been a high-performance computing consultant for many years, working on diverse projects such as parallelization of molecular dynamics, immersive visualization of fracture mechanics, provenance for the Large Hadron Collider, and time series analysis of the world's global health. His recent work is on continuous-time, discrete-event simulation and on testing of scientific code.

- Using optimization to make good guesses for test cases

I first used Julia to perform research during postdocs in quantum simulation, before using it in industry with a team working on various geospatial applications. Nowadays we use Julia at ELARA AI to simulate, analyze and optimize real-world businesses. I have contributed packages including *StaticArrays*, *CoordinateTransformations*, *Rotations*, *TypedTables*, *SplitApplyCombine*, *AcceleratedArrays* and *Dictionaries*.

- Dictionaries.jl - for improved productivity and performance

I am a doctoral candidate in Vanderbilt’s human genetics PhD training program.

- PRS.jl: Fast Polygenic Risk Scores

Anthony Blaom is a mathematician, publishing chiefly in the areas of differential geometry and dynamical systems, and a scientific computing consultant. He is a co-creator and lead contributor for MLJ, an open-source machine learning platform written in Julia, which began as a project at the Alan Turing Institute, London.

Initially trained as an a mechanical engineer, Anthony earned a PhD in Mathematics at Caltech in 1998. He is currently a Senior Research Fellow in the Department of Computer Science, University of Auckland.

- Training deep learners and other iterative models with MLJ

Arsh Sharma is a student at the National Institute of Technology, Hamirpur, India. He is currently working as a GSoC student for the Julia Language Community building Javis.jl, a math viz tool.

- Towards an increased code-creativity harmony in Javis

Senior year CS undergraduate at BITS Pilani - Pilani campus India. As a JSOC '20 student I worked on Fairness.jl . I am interested in fairness in machine learning, causality, counterfactual fairness and reinforcement learning. Lately, I have been exploring Quantum AI and causal RL. Happy to chat at ashryaagr@gmail.com or julia slack :-)

To know more about me, visit www.ashrya.in

- Bias Audit and Mitigation in Julia

Avik Sengupta is the head of product development and software engineering at Julia Computing, contributor to open source Julia and maintainer of several Julia packages, including JavaCall, TextAnalysis and GameZero. Avik is the author of Julia High Performance, co-founder of two artificial intelligence start-ups in the financial services sector and creator of large complex trading systems for the world's leading investment banks.

- Game development in Julia with GameZero.jl

Hi there! My name is Axel and I'm an intern at TNO, the Netherlands Organisation for Applied Scientific Research, working with Scientific Machine Learning for predicting structural responses. The internship is a part of my master thesis at University College London.

My fields of interest are computational structural engineering and computational design. Over the years, I've become more interested in more computing related topics like HPC, parallell processing and machine learning. This fall, I will move to the U.S. to start my PhD in Civil Engineering at Princeton University. I'm very interested in Julia for my future research and seeking collaborators in the Julia community.

- SciML for Structures: Predicting Bridge Behavior

Ayan Biswas is a scientist in the Data Science at Scale team (CCS-3) at Los Alamos National Laboratory. His research interests include exascale data analysis and reduction, in situ workflows, uncertainty quantification, statistical analysis/inference and high-dimensional data visualization. He also has vast experience in working with vector fields and information theory applications for visualization and analysis. He received his PhD in Data Visualization from The Ohio State University in 2016. Contact him at ayan@lanl.gov.

- In-Situ Inference for Exascale Simulations with Julia

Research consultant xKDR

- Watching earth at night

Bart Janssens is a military associate professor at the mechanics department of the Royal Military Academy, with a passion for computer graphics, high performance computing and fluid mechanics. For performance reasons, he used C++ until being introduced to Julia. His current work focuses on making scientific C++ libraries such as Trilinos interoperate with Julia, in order to port existing CFD code to Julia. He also uses JupyterLab and Pluto in his engineering (thermodynamics and gas turbines mostly) courses.

- Build your own fast, multi-user Jupyter and Pluto server

Bas Peters is visiting assistant professor in the mathematics department at Emory University. Previously, Bas worked for Computational Geosciences Inc as a research scientist, and received his PhD degree from the University of British Columbia in 2019. His main research interests are constrained optimization; design, optimization, and regularization of deep neural networks, geoscientific and geospatial applications, inverse problems, reinforcement learning, image processing, and numerical linear algebra.

- InvertibleNetworks.jl - Memory efficient deep learning in Julia

Benoît Legat is a postdoctoral associate at MIT with Prof. Pablo Parrilo

in the Laboratory for Information and Decision Systems (LIDS).

He received his Ph.D. degree in applied mathematics from the UCLouvain, Belgium, in 2020.

His research interests include mathematical optimization, invariant set computation and

optimal control.

- Symmetry reduction for Sum-of-Squares programming
- MutableArithmetics: An API for mutable operations

Postdoc at the University of Southern California

- Modeling Marine Ecosystems At Multiple Scales Using Julia

I am a computational researcher at the Metric Geometry and Gerrymandering Group at Tufts University, where I develop open-source tools for redistricting research.

- GerryChain.jl: detecting gerrymandering with Markov chains

Bishmer Sekaran is an Artificial Intelligence researcher based in Singapore. He first discovered Julia in 2020 and has been a vocal proponent ever since.

- Awesome Computer Vision Done Quick

I am a researcher in the fields of operations research and computational social science.

For development I use the Julia language. I currently mostly contribute to DataFrames.jl and related packages.

- The state of DataFrames.jl
- Release management - lessons learned in JuliaData ecosystem
- DataFrames.jl 1.2 tutorial

I am a PhD student in applied mathematics with Prof. Jan S. Hesthaven at EPFL. I am interested in novel computational methods for problems arising in engineering and scientific computing. I have been working in the field of Computational Linear Algebra to help develop new methods for solving linear systems. Coming from Matlab, Julia has taught me that fast code and readable code are not mutually exclusive.

- HssMatrices.jl

Brian Doolittle (They/Them) is 3rd year physics PhD student at the University of Illinois Urbana-Champaign where they research nonlocality in quantum networks. Before graduate school Brian worked as a software engineer at AthenaHealth developing clinical decision support systems and open standards for healthcare interoperability.

- BellScenario.jl - Computing Quantum Nonlocalty

Brian Guenter is a Senior Principal Researcher at Microsoft Research, where he manages the Interactive Media Group.

- Optical simulation with the OpticSim.jl package

Caleb Winston is a co-creator of Banyan and the creator of Emu, a GPGPU framework for Rust. In the past, he has worked on GPU-accelerated data science at NVIDIA and virtualization for wet labs at the Molecular Information Systems Lab at the University of Washington, Seattle. His primary interests are in making computing at both massive scale and the edge accessible for anyone to easily program.

- Auto-Parallelization at Cloud Scale with Banyan

Dr. Carleton Coffrin is a staff scientist at Los Alamos National Laboratory in the Advanced Network Science Initiative, an interdisciplinary team that investigates the application of emerging optimization and machine learning methods to problems in critical infrastructure systems. Dr. Coffrin’s work focuses on developing novel optimization methods for network design, operation, and restoration for power networks. His work on power system optimization has been recognized by the IEEE PES 2014 Optimal Power Flow Competition, the ARPA-e 2020 Grid Optimization Competition and Los Alamos National Laboratory's Early Career Researcher award. Dr. Coffrin is also exploring how novel computing devices, such as quantum computers and memristor networks, can improve the next generation of optimization algorithms. Dr. Coffrin received his Ph.D. in Computer Science from Brown University in 2012, under the supervision of Pascal Van Hentenryck.

- A Brief Introduction to InfrastructureModels

- Julia in High-Performance Computing

Hi, I'm Chad. My interests range from applied problems through "technology transfer", to applied research. I've been involved in probabilistic programming for the last ten years, and have led design of a few prototype systems. Since 2015 I've been very interested in Julia, resulting in Soss.jl and MeasureTheory.jl, as well as some utility packages around these.

Most recently I've founded Informative Prior, where I'm available for contract consulting work involving teaching, development, or application of probabilistic modeling software.

- Composable Bayesian Modeling with Soss.jl
- Applied Measure Theory for Probabilistic Modeling

Chandrasekhar Ramakrishnan studied mathematics at the University of California, Berkeley (B.A. 1997) and art and computer science at the University of California, Santa Barbara (M.A. 2003). He has worked as a software developer and data-science consultant for companies, research institutions, and NGOs in the US, Germany, and Switzerland. Since 2009, he has been at **ETH Zürich** supporting projects by developing software solutions for data management, analysis, and visualization.

- Reproducibility, Julia, and Renku

Research scientist at Microsoft mixed reality and AI labs. Interested in computer graphics and vision.

- Optical simulation with the OpticSim.jl package

Quantum computing | quantum machine learning

GitHub: ChenZhao44,

Twitter: @ChenZhao44

- ZXCalculus.jl: A Julia package for the ZX-calculus

- Conic optimization example problems in Hypatia's examples folder

Statistician and SIMD-enthusiast.

- Roadmap to Julia BLAS and LinearAlgebra

I'm a long time enthusiastic user of Julia and enjoy contributing to various packages across the open source ecosystem, Julia standard libraries and compiler. I love hearing about people's fascinating technical computing adventures of all types! Find me at https://github.com/c42f

- DataSets.jl: A bridge between code and data

Chris Hill is a principal researcher at MIT. He is a lead architect of the widely used MIT General Circulation Model (MITgcm). He has been working with the Julia community for almost a decade.

- Scaling of Oceananigans.jl on multi GPU and CPU systems

Chris ran the Bay Area Julia Users group from 2016 to 2020.

- Lattice Reduction using LLLplus.jl

Chris Rackauckas is an Applied Mathematics Instructor at MIT and the Director of Scientific Research at Pumas-AI. He is the lead developer of the SciML open source scientific machine learning organization which develops widely used software for scientific modeling and inference. One such software is DifferentialEquations.jl for which its innovative solvers won an IEEE Outstanding Paper Award and the inaugural Julia Community Prize. Chris' work on high performance differential equation solving is seen in many applications from the MIT-CalTech CLiMA climate modeling initiative to the SIAM DSWeb award winning DynamicalSystems.jl toolbox. Chris is also the creator of Pumas, the foundational software of Pumas-AI for nonlinear mixed effects modeling in clinical pharmacology. These efforts on Pumas led to the International Society of Pharmacology's (ISoP) Mathematical and Computational Special Interest Group Award at the American Conference of Pharmacology (ACoP) 2019 for his work on improved clinical dosing via Koopman Expectations, along with the ACoP 2020 Quality Award for his work on GPU-accelerated nonlinear mixed effects modeling via generation of SPMD programs. For this work in pharmacology, Chris received the Emerging Scientist award from ISoP in 2020, the highest early career award in pharmacometrics.

- JuliaSim: Machine Learning Accelerated Modeling and Simulation
- Simulating Big Models in Julia with ModelingToolkit

Christian Schilling received his Ph.D. degree in computer science from the University of Freiburg, Germany, in 2018 under the supervision of Andreas Podelski. He was a postdoctoral research fellow at IST Austria in the group of Thomas A. Henzinger. Since 2020 he is the interim professor for cyber-physical system at the University of Konstanz, Germany. Christian's research in the area of formal methods is focused on the analysis, verification, and synthesis of systems with dynamical or machine-learned components. He is a co-lead developer in the JuliaReach ecosystem.

- It's all Set: A hands-on introduction to JuliaReach
- Set Propagation Methods in Julia: Techniques and Applications

Forest Engineer, from the Federal University of Santa Maria (UFSM) Frederico Westphalen Campus. Currently a Master's student in the Graduate Program in Agronomy: Agriculture and Environment at UFSM - FW. He develops works in the areas of Forest Engineering, Agrometeorology, Vegetable Production, Forest Biomass, Agroforestry Systems and Julia Language applied in the Forest Inventory.

- Use of Julia Language in the Forest Inventory

Collaborator on YAML, HTSQL, DataKnots, and other projects that advance the usability of software systems.

- HypertextLiteral : performant string interpolation for HTML/SVG
- FunSQL: a library for compositional construction of SQL queries

I am an assistant professor at the Wisconsin Institute for Discovery and the Department of Plant Pathology at the University of Wisconsin-Madison. Originally from Mexico City, I did my Undergraduate degrees in Actuarial Sciences and Applied Mathematics at ITAM. Then, I did a MA in Mathematics and a PhD in Statistics at the University of Wisconsin-Madison.

In my spare time, I enjoy swimming, running, biking, climbing and yoga!

Pronouns: she/her

- PhyloNetworks: a Julia package for phylogenetic networks

I am a professor for computational number theory at Kaiserslautern University. I a PI of the DFG (German research association) funded OSCAR project as well as a developer of both OSCAR and Hecke.

- The OSCAR Computer Algebra System

Clayton Barrows is a member of the Forecasting and Modeling Group at the National Renewable Energy Laboratory. His research focuses on improving the technical and economic efficiency of energy systems through advanced computation and analysis. At NREL, Clayton leads a team in developing and utilizing energy and infrastructure systems models to gain new insights into pathways towards system modernization. In his research, Clayton draws upon deep experience in applying the tools of network science and optimization to improve the fidelity and scalability of infrastructure systems models. He has applied these techniques to inform policy in studies and applications around the world.

- Scalable Power System Modeling and Analaysis

Economist by training and horticulturist by experience. Erstwhile volunteer CTA for Andrew Ng's early Coursera courses in machine learning.

- Three mini-utilities to manage computing resources

Dr. Cong Van is a mathematician, currently a Postdoc fellow at FedEx Institute of Technology, working on Structured Illumination Microscopy (SIM), one type of super-resolution fluorescence microscopes. Dr. Cong Van used Julia during his PhD and during his previous position at Mitsubishi Electric Research Labs (MERL) for thermodynamic property models.

- Using Julia in microscope image processing

Soon-to-be college student who loves everything related to computers and virtual reality

- Pluto.jl Notebooks are Web APIs!

Developer of Ahorn and similar tools.

- Julia and deploying complex graphical applications for laypeople

I have been working with Julia since 2015 and have made a variety of contributions to the ecosystem. I am a member of the Julia Community Prize committee and work for Beacon Biosignals as a Principal Software Architect.

- Julia in Private Organizations

I grew up in Grand Rapids, Michigan, but now I live in Ames, Iowa. Both are great places to live, but I hope to move closer to GR eventually. I first became truly interested in science in high school chemistry class. Later, I found organic chemistry to be the most fun, and this interest spread to biochemistry and math (BS double major). I decided to continue my exploration and get an MS in chemistry, during which I studied a family of DNA polymerases that are recruited to replicate past lesions in the DNA. After that, I still wanted more time to study, so here I am at Iowa State in a great bioinformatics and computational biology PhD program. I want my life to be about exploration of STEM, and my favorite set of tools is Julia.

- Composite Interfaces for Bioinformatics

I am associate professor at the University of Granada, in Computer Science, with experience in Artificial Intelligence, in particular in Intelligence Optimization and in Machine Learning. In my daily life I am a believer of free software (use daily Emacs, Linux, ...). I have been for years a great Python fan, and more recently fan of Julia, in which I have created several small but useful packages. personal website.

- Faster scripts in Julia with DaemonMode.jl

Dan Padilha is a Masters (Aerospace Engineering) student at The University of Tokyo and JAXA Institute of Space & Astronautical Science (ISAS). He has a background in computer science and 6 years of professional experience as a software systems and research engineer in quantum computing (at Rigetti in London), machine learning (at QxBranch in Adelaide), and embedded systems (at NICTA in Sydney). He has been involved in two successful start-up companies, presented at high-performance computing and emerging technologies conferences, run software workshops at over a dozen multinational corporations and universities, and led technical engagements designing novel algorithms and analytics platforms. He is currently a member of the Tsuda Laboratory at ISAS, working on software tools for astrodynamics research.

- Designing Spacecraft Trajectories with Julia

Research scientist at Beacon Biosignals

- Standardize your predictors with StandardizedPredictors.jl

David Anthoff is an environmental economist who studies climate change and environmental policy. He co-develops the integrated assessment model FUND that is used widely in academic research and in policy analysis. His research has appeared in Nature, Science, the American Economic Review and other academic journals. He contributed a background research paper to the Stern Review and has advised numerous organizations (including US EPA and the Canadian National Round Table on the Environment and the Economy) on the economics of climate change.

He is an assistant professor in the Energy and Resources Group at the University of California, Berkeley. Previously he was an assistant professor in the School of Natural Resources and the Environment of the University of Michigan, a postdoc at the University of California, Berkeley and a postdoc at the Economic and Social Research Institute in Ireland. He also was a visiting research fellow at the Smith School of Enterprise and the Environment, University of Oxford.

He holds a PhD (Dr. rer. pol.) in economics from the University of Hamburg (Germany) and the International Max Planck Research School on Earth System Modelling, a MSc in Environmental Change and Management from the University of Oxford (UK) and a M.Phil. in philosophy, logic and philosophy of science from Ludwig-Maximilians-Universität München (Munich, Germany).

- Julia in VS Code - What's New
- Julia in the Windows Store
- Package development in VSCode

David Fobes (Ph.D.) is a scientist at Los Alamos National Laboratory in the Information Systems and Modeling group. Prior to joining LANL in 2015, he obtained a PhD in physics from Tulane University. At LANL, he specializes in development and implementation of algorithms for critical infrastructure systems, focusing on optimization of unbalanced multi-phase electric distribution systems, and post-event system evaluation and restoration, and has served on multiple projects for DOE and DHS in these areas. He is the lead developer of PowerModelsDistribution, a critical library for distribution system optimization relied upon by several ongoing projects, and has led and participated in a variety of other software development efforts in the infrastructure modeling space, including serving as Scrum Master and developer for a team focused on modeling the inter-dependencies between electric and natural gas infrastructure systems using co-simulation. He is an author of over 43 peer reviewed journal and conference publications, is a certified Scrum Master, and has received multiple awards for his infrastructure optimization works.

- Unbalanced Power Flow Optimization with PowerModelsDistribution

Professor of Computational Science at the Universidad Nacional Autónoma de México and visiting professor at MIT.

Interested in computational science, interval arithmetic, and numeric-symbolic computing.

Author of the JuliaIntervals suite of packages for interval arithmetic, and various tutorials on Julia.

- Global constrained nonlinear optimisation with interval methods
- Introduction to metaprogramming in Julia
- Calculating a million stationary points in a second on the GPU
- Solving discrete problems via Boolean satisfiability with Julia
- Open and interactive Computational Thinking with Julia and Pluto
- Publish your research code: The Journal of Open Source Software
- Set Propagation Methods in Julia: Techniques and Applications

I am a PhD student at the Division of Systems and Control

within the Department of Information Technology and the

Centre for Interdisciplinary Mathematics in Uppsala,

supervised by Fredrik Lindsten,

Dave Zachariah, and Erik Sjöblom. The main focus of my PhD studies is uncertainty-aware deep learning. Currently, I

am particularly interested in analyzing and evaluating

calibration of

probabilistic models. Please visit my webpage for more information.

My GitHub profile provides an overview of my contributions to the Julia ecosystem. Currently, I am a member of the steering council of SciML and the Turing team.

- EllipticalSliceSampling.jl: MCMC with Gaussian priors
- Calibration analysis of probabilistic models in Julia

I am a quant for BestX and use Julia in my day to day work of assessing trading costs across different financial markets. Outside of my day job you'll find me writing on a variety of topics for my blog or tinkering away on different Julia packages.

- Building the BestX Event Risk Model using HawkesProcesses.jl

- Set Propagation Methods in Julia: Techniques and Applications

Dhairya Gandhi is a data scientist at Julia Computing Inc. and is the lead developer of the Machine Learning framework Flux.

- A Tour of the differentiable programming landscape with Flux.jl

- Scalable Power System Modeling and Analaysis

Dino Butron is a Senior Applications Engineer at Hamamatsu Corporation in Bridgewater, NJ where his focus is on high sensitivity photodetectors for use in various markets. He is currently involved in leading discussions for detector selection and developing simulation tools.

Dino is an expert in the operating principles and application of various detectors such as photodiodes, avalanche photodiodes (APD), SPPC (SPAD), MPPC (SiPM), and photomultiplier tubes (PMT). He has worked on many photodetector experiments resulting in a deep understanding of detector performance. In addition, he has vast knowledge programming signal-to-noise ratio and output simulations. He received his Bachelor’s degree in Electrical Engineering from Manhattan College, Riverdale, NY, in 2012.

- Using Julia to simulate non-linearity in photon counters

I am a PhD candidate in the SPS group of Electrical Engineering department in Eindhoven University of Technology. My research interests lie in the fields of computer science, software developing, numerical modeling, machine learning, computational optimization and high-performant parallelized applications.

- ReactiveMP.jl: Reactive Message Passing-based Bayesian Inference

I am a dynamic educational professional, data science enthusiast, speaker, board member, book author, researcher, and L&D coach greatly passionate about different applications of data science, and enjoy speaking on various data science topics and creating a learning experience by reinventing technology.

Currently, I am working on several projects to create more engaging and exciting educational opportunities by using Data Science, AI, and Machine Learning project for education

I actively work to share insights and perspectives through writing, consulting, and coaching with clients, practitioners, students, and fellow academicians in the field of learning. When not reading or writing, one can find me doodling away to my heart’s content.

- Visualization storytelling

- Space Engineering in Julia

Group leader for Statistical Sciences at Los Alamos National Laboratory

- In-Situ Data Analysis with Julia for E3SM at Large Scale
- In-Situ Inference for Exascale Simulations with Julia

I am a Ph.D. student in the Theoretical Systems Biology Group at the University of Melbourne led by Prof. Michael Stumpf. I focus my research on hybrid models, in which I combine mechanistic modelling techniques, e.g. differential equations, with machine learning approaches such as neural networks. I am passionate about using hybrid models in developmental biology to enhance our understanding of cell fate decision making.

In 2017, I received a Bachelor of Science in Bioinformatics from the Technical University of Munich and the Ludwig Maximilian University of Munich. In 2018, I graduated from Imperial College London with a Master of Science in Bioinformatics and Theoretical Systems Biology.

- Julia for Biologists

- Runtime-switchable BLAS/LAPACK backends via libblastrampoline

Engineer at BlackRock AI Labs

- Linearly Constrained Separable Optimization

Postdoctoral Associate at Julia Lab, Massachusetts Institute of Technology.

- Towards MDP.jl: The Julia Library of MD Potentials

Postdoctoral researcher at the International Centre for Numerical Methods in Engineering

- New tools to solve PDEs in Julia with Gridap.jl

I recently finished my PhD in quantum information theory at the University of Cambridge. I’m now a Research Scientist working at Beacon Biosignals, trying to make brain monitoring easily accessible, interpretable, and actionable.

- Code, docs, and tests: what's in the General registry?

Erik Dasbach joined Merck 20+ years ago and his work experiences have included mathematical modeling, clinical trial design and analytics, population health and epidemiologic studies, patient reported outcome measure development and analytics, real-world database analytics, and platform development for sharing data, models, and analytics.

Prior to joining Merck, Erik worked in a variety of scientific and technology roles in the healthcare industry including the Centers for Disease Control and Prevention, the National Cardiovascular Network, the hospital industry, business development, and software development.

Erik received his Ph.D. from the University of Wisconsin-Madison in Industrial & Systems Engineering with a specialty in decision sciences and health technology assessment.

- Julia & Healthcare Technology Assessment Analytics

I am Evangelos Paradas from Thessaloniki, Greece. I am physicist, holding a PhD in Particle Physics. The trip into the algorithms' world, started during my PhD, as I was responsible for a few algorithms of the High Level trigger of the CMS experiment at CERN.

In this context, the algorithms were written in C++. After a few years I moved to the Netherlands, working at ASML as Algorithm Deployment architect.

- Early adopters jumping the adoption chasm in a company

Fearghal O’Donncha is a research scientist at IBM Research — Ireland. His work focuses on applying simulation models, analytics, and machine learning techniques to assist industry operations. This encompasses developing and deploying simulation-based models, integrating sensor data from a variety of IoT platforms, developing AI-based models that extract value from sensor or expert data, and optimizing these tools to a variety of HPC and cloud-based platforms. He is an adjunct faculty member at the National University of Ireland, Galway.

- Data driven insight into fish behaviour for aquaculture

Felix J. Herrmann graduated from Delft University of Technology in 1992 and received his Ph.D. in engineering physics from that same institution in 1997. After research positions at Stanford University and the Massachusetts Institute of Technology, he became back in 2002 faculty at the University of British Columbia. In 2017, he joined the Georgia Institute of technology where he is now a Georgia research Alliance Scholar Chair in Energy, cross-appointed between the Schools of Earth & Atmospheric Sciences, Computational Science & Engineering, and Electrical & Computer Engineering. His cross-disciplinary research program spans several areas of computational imaging including seismic, and more recently, medical imaging. Dr. Herrmann is widely known for tackling challenging problems in the imaging sciences by adapting techniques from randomized linear algebra, PDE-constrained and convex optimization, high-performance computing, machine learning, and uncertainty quantification. Over his career, he has been responsible for several cost-saving innovations in industrial time-lapse seismic data acquisition and wave-equation based imaging. In 2019, he toured the world presenting the SEG Distinguished Lecture "Sometimes it pays to be cheap – Compressive time-lapse seismic data acquisition". In 2020, he was the recipient of the SEG Reginald Fessenden Award for his contributions to seismic data acquisition with compressive sensing. At Georgia Tech, he leads the Seismic Laboratory for Imaging and modeling and he is co-founder/director of the Center for Machine Learning for Seismic (ML4Seismic), designed to foster industrial research partnerships to drive innovations in artificial-intelligence assisted seismic imaging, interpretation, analysis, and time-lapse monitoring.

- InvertibleNetworks.jl - Memory efficient deep learning in Julia

Felix Wechsler studied Physics and Informatics at the Technical University of Munich in Germany. For his master studies in Photonics he moved to Jena (city of light). Currently he finishes his master thesis in the field of computational microscopy at the Biomedical Imaging Group of Leibniz Institute of Photonic Technology under the joint supervision of Rainer Heintzmann and Ivo Ihrke.

- FourierTools.jl | Working with the Frequency Space
- DeconvOptim.jl: Microscopy Image Deconvolution
- IndexFunArrays.jl | Fun with indices (and functions on them)

Flemming is a 3rd year PhD student in the Chemical Engineering Department at MIT working on the moment-based analysis of stochastic processes.

- Bounding the Moments of Polynomial Jump-Diffusion Processes

https://github.com/fonsp

- Open and interactive Computational Thinking with Julia and Pluto
- 🎈 Pluto.jl — one year later

I am in the second year of the Bachelor Degree in Physics at the University of Turin. I am mainly interested in the theoretical and mathematical aspects of physics. I also conduct research in machine learning, with a particular interest towards the connection between machine learning and physics. Recently I have worked in the field of Scientific Machine Learning using Julia libraries, such as NeuralPDE.jl.

- Physics-Informed ML Simulator for Wildfire Propagation

Physics graduate student interested in Scientific Machine Learning.

- Chaotic time series predictions with ReservoirComputing.jl

Francesc Verdugo PhD is assistant research professor at CIMNE (Barcelona, Spain) and he is interested in the research of new discretization methods to solve partial differential equations (PDEs). He is co-founder of the Gridap.jl project to solve PDEs in Julia.

- New tools to solve PDEs in Julia with Gridap.jl

Professor in Applied Mathematics at the University of Waterloo

- Scaling of Oceananigans.jl on multi GPU and CPU systems

François Pacaud is a postdoctoral appointee at Argonne National Lab, supervised by Mihai Anitescu. His work focuses on the development of new nonlinear optimization algorithms on GPU architectures.

- Nonlinear programming on the GPU

PhD candidate in physics at the University of Basel.

Member of the SciML open source software organization for scientific machine learning.

Google Summer of Code 2020 student with the project: High weak order SDE solvers and their utility in neural SDEs.

- MitosisStochasticDiffEq.jl - Filtering & Guiding for SDEs

Prof of marine hydrodynamics & biologically inspired engineering at University of Southampton, physics-based machine learning at Alan Turing Institute. https://weymouth.github.io/

- WaterLily.jl: Real-time fluid simulation in pure Julia

Postdoc at Utrecht University

- InvertibleNetworks.jl - Memory efficient deep learning in Julia

I work as a reseach scientist at the Massachusetts Institute of Technology (MIT) where I investigate oceanography and climate. As part of the Department of Earth, Atmospheric and Planetary Sciences, my work focuses on ocean modeling and the analysis of global ocean data sets such as Argo profile collections, satellite records of sea level, or ocean color retrievals. I co-develop computer programs in various languages and carry out ocean state estimation using the MIT general circulation model in order to interpolate and interpret ocean observations. My scientific interests include: ocean circulation and climate variability; tracer transport and turbulent transformation processes; interaction of ecological, geochemical, and physical processes; global cycles of heat, water, and carbon; observational statistics; forward and inverse modeling.

- Modeling Marine Ecosystems At Multiple Scales Using Julia
- OceanRobots.jl -- Ocean Robots Simulation And Data Ingestion
- ClimateModels.jl -- A Simple Interface To Climate Models

I hold Post Graduate Diploma in Cyber Laws and Cyber Forensics from National Law School of India University Bangalore. I have presented talks many conferences including PyData Global, JuliaCon 2018 and 2020, PyCon FR/HK/TW/ID/TZ/AU, COSCUP Taiwan, FOSDEM 2021, FOSSASIA 2021, PyCon Africa, BuzzConf, EuroPython, PiterPy Russia, SciPy India. Worked as a Reviewer and Program Committee member for reputed International conferences including SciPy USA, SciPy Japan, JuliaCon, JupyterCon, PyData Global, and PyCon India, and publishers include Manning USA and Oxford Univesity Press. I am also a GitHub Certified Campus Advisor. I lead the PyData Belagavi chapter and the OWASP Belagavi chapter. I am working as CFP Co-Chair for PyCon India 2021.

- Multilingual Natural Language Processing using Julia

Postdoc in climate physics in the MPI for Meteorology (Hamburg) and professional drummer. Lead dev for JuliaDynamics and JuliaMusic.

- Changing Physics education with Julia

www.github.com/gstavrinos

- ROS.jl beta release: The C++ Robot Operating System wrapper

Msc student in Mathematics at Queen Mary University of London

- Probabilistic K-Nearest Neighbours

PhD student in Physics at University of Buenos Aires.

- Generative Models with Latent Differential Equations in Julia

Frédéric Gillot is Assistant Professor at École Centrale de Lyon within the Department of Solid Mechanics, Mechanical Engineering and Civil Engineering. He carries out his research at the Tribology and System Dynamics Laboratory (LTDS), a French CNRS joint research unit (no. 5513). He graduated in Engineering from École nationale supérieure des arts et métiers (ENSAM) and the University of Wien, Austria. An alumnus of École normale supérieure, he holds an agrégation in Mechanical Engineering, a research master and a PhD from École Centrale de Nantes and the University of Nantes. He pursued post-doctoral research for two years at the University of Tokyo (Todai) with funding from the Japan Society for the Promotion of Science. His current research interests address parametric shape optimisation, multi-objective optimisation and robust optimisation.

- Non-linear SDE mechanical simulations

- The Design of the MiniZinc Modelling Language

Glen Hertz has spent 15 years as a field applications engineer supporting customers of commercial SPICE simulators. He joined Julia Computing as the Principal EDA Solutions Architect in 2021 to direct the JuliaSPICE product.

- JuliaSPICE: A Composable ML Accelerated Analog Circuit Simulator

I'm a Research Software Engineer at InveniaLabs, UK.

Interested in the application of Julia for scalable, sustainable, research.

- Clearing the Pipeline Jungle with FeatureTransforms.jl

Goran Frehse has a Diploma in Electrical Engineering and Information Technology from Karlsruhe Institute of Technology, Germany, and a PhD in Computer Science from Radboud University Nijmegen, the Netherlands. From 2006 to 2018, he was an associate professor at the University Grenoble Alpes, from which he obtained a habilitation in 2016. From 2016 to 2018, he held a research chair (Chaire Initiative Universitaire Alpes) at the Univ. Grenoble Alpes. Since 2018, he is a professor at ENSTA Paris, where he continues his research on safe cyber-physical systems.

- Set Propagation Methods in Julia: Techniques and Applications

Gregor Kappler carries out psychometric research and data science consulting, and is founder of FilingForest, a julia-focused startup developing solutions for fast unbiased measurement in graph data.

Gregor was initially trained as a mathematician and psychologist, has implemented solutions for semantic text analytics for his PhD in 2007, and developed psychometric models for measuring with texts.

He has worked as a lecturer and researcher at the University of Vienna and the University of Jena and worked on a series of predictive analytic projects for software vendors and customers.

Gregor has switched to Julia from R in 2018, and is creator of the CombinedParsers package which provides parser combinators for fast, recursive and type-save parsing in pure Julia.

- Theory is (nearly) implementation with julia types
- Parse and broker (log) messages with CombinedParsers(.EBNF)

Research scientist and ocean physicist at MIT

- Scaling of Oceananigans.jl on multi GPU and CPU systems

Russian/Hungarian biophysics and machine learning PhD student at King's College London, collaborating with Microsoft Research Cambridge. Born in Vienna. Wanted to become an actor but luckily landed in research

- FlowAtlas.jl: interactive exploration of phenotypes in cytometry

- Automatic dualization with Dualization.jl

I am a Computer Science student at the *Universidade Federal do Rio Grande do Sul*. My interests hop around the fields of Operating Systems, Algorithm Design, Computer Graphics and Image Processing. Currently, I am working as a Back End Development intern at DeepX , using Elixir and Rust. I've been using Julia for a couple of years in order to get fast image processing results with easy-on-the-eyes code.

- DesignByContract.jl: Enforcing interfaces between functions

PhD candidate in chemistry at the University of Georgia. Currently working at the Center for Computational Quantum Chemistry under supervision of Prof. Henry Schaefer.

I am originally from Sao Paulo, Brazil where I got my degree in chemistry. Upon realizing that I was not talented enough for lab work, I found a new passion in programming. Today my main interests are the development of wave function methods and their application in chemical problems.

- Fermi.jl: A modern design for quantum chemistry

I am a late-stage Ph.D. student in Robotics at MIT CSAIL, and I first used "Julia" in 2012!

- Structural lambdas for generic code and delayed evaluation

I am a mechanical engineer working on ground systems software in the European space industry.

Working on reimagining space exploration with Open Source at JuliaAstro, JuliaSpace, and OpenAstrodynamics.

- To the Moon and Beyond with Julia
- A Short History of AstroTime.jl

I am a Postdoctoral Fellow in the Cluster of Excellence at the University of Münster, Germany. My research is focused on the analysis and development of numerical methods for partial and ordinary differential equations. In particular, I am interested in the stability of these schemes as well as mimetic and structure-preserving techniques, allowing the transfer of results from the continuous level to the discrete one.

- Adaptive and extendable numerical simulations with Trixi.jl

PhD from Department of Automatic Control, Lund Institute of Technology in 1978 about a new modeling language. Started Dynasim 1992, sold to Dassault Systèmes in 2006. Chief architect for modeling software Dymola. Initiated design of Modelica modeling language in 1996.

Previous experience include: Mogram AB (CEO), Dassault Systèmes (CTO Systems), Dynasim AB (CEO).

Working with Julia since 2015 and with Modia since 2016.

- Modia – Modeling Multidomain Engineering Systems with Julia

Ian Slagle is an junior undergraduate student studying Computer Science, Mathematics, and Physics at Coe College in Cedar Rapids, IA who utilizes Julia in his research. He currently plans to attend graduate school for Data Science.

- Solving Pokemon Go Battles using Julia

- Parameter Identifiability in Ordinary Differential Equations

I am a PhD student in Imperial College working at the intersection of reinforcement learning, optimal control and process systems engineering. Previously, I worked in data science and software engineering within the energy and food industries in Mexico. I have a background in physics.

- Constrained Control with Neural Feedback Policies in DiffEqFlux

- HiGHS

I am a software developer from Deloitte Digital Australia, currently working with a talented team of individuals on Deloitte's Optimal Reality offering (https://optimalreality.com/), a cloud based platform for delivering digital twin capability based on simulation techniques pioneered in Formula One racing.

- A new OpenStreetMap interface: LightOSM.jl

Been a Julia enthusiast for a long time, since Julia 0.1! Always been interested in data engineering, making data processing more efficient, and various data formats, and Julia is just such a fun tool to dive into these kinds of problems.

- Partitions and chains: enabling batch processing for your data

My Name Is Jacob S. Zelko – Pleasure To Meet You!

I am a graduate of Georgia Institute of Technology with a BS in biomedical engineering. While pursuing my BS, I worked as a data information specialist and biomedical informaticist in the Department of Biomedical Informatics at Emory University doing research in the areas of computational psychiatry and worked with The Center for Discovery as an engineering consultant to aid in caring for their juvenile neurocognitively diverse population. Currently, I work as a Health Data Analytics and Informatics Researcher at Georgia Tech Research Institute and as a Consultant with the Centers for Disease Control.

- Live Coding: Outreach and Beyond
- Javis.jl - Julia Animations and Visualizations

- Modelling Australia's National Electricity Market with JuMP

- AlgebraicDynamics: Compositional dynamical systems

I work for Julia Computing on Julia compiler technology.

- Atomic fields: the new primitives on the block

Jasmine is the Director of Data Science at InsightRX, a precision medicine company. She writes software and develops models to help pharmacists tailor medications to their patients. Jasmine received her PhD in Bioengineering from the University of California, Berkeley. Her thesis was about the interplay between growth factors and mechanical cues in the progression of brain cancer. She also teaches introductory programming workshops.

- Jumping into the Julia Community via Advent Of Code

Jean-François Baffier is an academic researcher at the RIKEN Center for Advanced Intelligence Project (AIP), and a consultant in Artificial Intelligence, Big Data Science, Data Structures, and Algorithms. As an academic, he gives back to society through fundamental research in computer science supplemented by open source libraries and softwares.

His current research project involves the study of the “Analysis of information networks,” the “Smart compression for high-scalability of data structures,” and “Explainable Artificial Intelligence.” Other topic of interest covers modeling of failures and routing in Networks, Game Analysis, and AI for Games.

- Put some constraints into your life with JuliaCon(straints)

I'm a Chemical Engineering faculty member at Cornell. I've been using Julia in my Cornell life (both teaching and research) since the 0.3 timeframe. I've also in the last year started a small consulting company which uses Julia to develop server side applications for data science applications.

- Case Study: Server Side Julia for COVID-19 Patient Workflows

Second year undergraduate at MIT studying Computer Science and Engineering.

degreeff@mit.edu

https://github.com/jrdegreeff

- Scalable Material Simulations in a Julia Infrastructure

Over the course of six years in data I’ve optimized digital marketing, applied machine learning to the contemporary art world, and contributed to the digitization of the automobile industry. I am currently a Master’s student in Economics at the Humboldt University in Berlin.

- ComposableCommunities.jl: Evolving Julia package communities

- TSSOS.jl: exploiting sparsity in polynomial optimization

https://giggleliu.github.io/about/

- Pebble games - Time and space to differentiate a program

- Modeling Bilevel optimization problems with BilevelJuMP.jl

I'm an aerospace engineering MS student who will be graduating in May 2021. My academic research has primarily been space robotics software development. I've worked on an open source Julia package, `UnitfulAstrodynamics.jl`

, throughout my graduate astrodynamics courses. I'll be working as an aerospace controls engineer on the Orion project starting in July 2021.

- Going to Jupiter with Julia

- Cerberus: A solver for mixed-integer programs with disjunctions

Johannes Blaschke is a computer systems engineer at the National Energy Research Scientific Computing Center (NERSC), where he is engaging with scientists to help them optimize their software for the next-generation supercomputers. His work focuses on enabling the real-time reconstruction of x-ray scattering data using extreme-scale computing environments. Johannes received his PhD in Theoretical Physics from the University of Goettingen, while researching statistical mechanics problems at the Max Planck Institute for Dynamics and Self-Organization. After his PhD, Johannes developed fluid-structure interaction codes for fluctuating hydrodynamics simulations of multi-phase and active matter simulations at the Technical University of Berlin and the Center for Computational Sciences and Engineering at Lawrence Berkeley National Laboratory. In 2019 Johannes joined the Data Science Engagement Group at NERSC.

- Deploying Julia on a Brand New Supercomputer at NERSC

I am a PhD candidate in economics at the European University Institute in Florence, a guest researcher at the University of Oslo and a visiting scholar at the University of Minnesota and the Federal Reserve Bank of Minneapolis.

My research interests are macroeconomics, fiscal policy and computational methods. I also work on household finance and machine learning.

https://www.jofleck.com // https://twitter.com/_jofleck

- Using Julia to study economic inequality and taxation

Student of Technical Cybernetics (Technische Kybernetik und Systemtheorie) at TU Ilmenau, Germany.

- Gift orders of magnitude of speed up to random strangers

I am a theoretical physicist working at Irelands national supercomputing centre ICHEC.

- Introducing QXGraphDecompositions

PhD Candidate in Computer Science at Cornell University

- Exploiting Structure in Kernel Matrices

Infrastructure programmer building high performance distributed systems, mobile applications, or embedded systems depending on the era. Historically a C/C++ programmer, but have also spent parts of my career programming in pascal, perl, javascript and other more obscure languages. Every seven years, I pick up a new tool for my toolbox and this time it was Julia.

- Strengths and Challenges of Julia for learning Linear Algebra

MRI physics PhD student at the University of British Columbia. I study brain tissue microstructure by simulating MRI signals and using Bayesian learning for fast parameter inference.

- Matlab to Julia: Hours to Minutes for MRI Image Analysis

Jonathan Laurent is a PhD student in Computer Science at Carnegie Mellon University. His current research interests lie at the intersection of machine learning and automated theorem proving.

- Building on AlphaZero with Julia

Born in Mexico City. Studied a Bachelors in Chemical Engineering at UNAM. M.Sc. on Materials Science and Engineering at MIT. Studied PhD at TU Eindhoven on Applied Physics.

Worked for Philips Research 1 year.

Working at ASML for 7 years on algorithms.

- Early adopters jumping the adoption chasm in a company

Jorge Pérez Zerpa obtained a Doctorate in Engineering degree by Universidad de la República in Uruguay, a MSc in Mechanical Engineering degree by Universidade Federal de Rio de Janeiro in Brazil, and did a stage at INRIA's TAO team in France. He is Assistant Professor at the Structures Department of the School of Engineering in Universidad de la República, and Researcher level 1 at ANII.uy . His research work includes the development and application of numerical methods in computational modelling of solids and structures, with focus in constitutive parameter identification methods. He leads the development of the Open Nonlinear Structural Analysis Solver (onsas.org) based in the application of the Finite Element Method.

- Set Propagation Methods in Julia: Techniques and Applications

I'm a senior software engineer with GN Advanced Science and have been working with Julia since 2014. My Julia work is focused on platform development for rapid prototyping of audio signal processing algorithm personalization and cloud-based deployment. I'm passionate about making software development accessible from a technical perspective through abstraction and automation.

- Semantically Releasing Julia Packages

I am a PhD Student in Universidade de Aveiro, Portugal, currently pursuing Biochemistry with a twist. Over the past 5 years I've directed my research efforts towards Computational Chemistry, more specifically, for the development of scientific software. I started learning Julia 3 or 4 years ago, and have since grown more and more in love with its syntax and ecosystem. Currently, my main PhD project is the development of ProtoSyn, a simple and intuitive package for the molecular manipulation and simulation of peptides.

- ProtoSyn: a Julia based platform for molecular modelling

- Infinite-Dimensional Optimization with InfiniteOpt.jl

I am a quantitative ecologist currently working as a postdoctoral research fellow at the University of Michigan. My research is focused on using quantitative methods and scientific programming to move forward in our understanding of how species, ecological, and ecosystem processes are affected by Global Change. I am particularly interested in encouraging the use of Julia language for ecological research and to this end, I am developing programming resources for ecologists. Some examples can be found at my GitHub repository (https://github.com/jmrmcode).

- Modeling species co-occurrence with Turing.jl

I am an HPC software engineer working at the JuliaLab. I maintain Dagger.jl, AMDGPU.jl, and BPFnative.jl, and generally enjoy the challenge of hacking on compilers and HPC runtimes.

- GPU programming in Julia BoF
- GPU programming in Julia
- Easy, Featureful Parallelism with Dagger.jl
- BPFnative.jl: eBPF programming in Julia

Ph.D. candidate at the Institute of Information and Communication Technologies, Electronics and Applied Mathematics (ICTEAM) of Université Catholique de Louvain (UCL), Louvain-la-Neuve, Belgium.

- Set Propagation Methods in Julia: Techniques and Applications

Dr. Júlio Hoffimann is a research scientist with more than 10 years of experience in advanced statistical theories for geosciences. He is the author and lead developer of the GeoStats.jl framework, as well as various other open source projects that are widely used by geoscientists around the world: https://juliohm.github.io

- Geostatistical Learning

I'm a PhD student researching speech processing at the Institute for Systemic Neuroscience in Hamburg, Germany. I'm a core contributor to Makie.jl and the author of packages such as MakieLayout.jl, Chain.jl, Animations.jl.

- A deep dive into MakieLayout

Born 1961 in Erfurt, Germany. Diploma in mathematics from Moscow State University in 1984, Ph.D from Technical University Chemnitz-Zwickau in 1995. Joined the Karl-Weierstraß-Institute Institute of Mathematics of the Academy of Sciences of the GDR in 1984.

Since 1992 with Weierstrass Institute for Applied Analysis and Stochastics (WIAS). Currently, deputy head of the Numerical Analysis group of WIAS. Main field of activity is algorithm and software development for nonlinear systems of partial differential equations. Interdisciplinary research activities include numerical modeling of various phenomena in fuel cells, batteries, semiconductors, subsurface flow processes.

- Julia for Charge Transport in Condensed Matter

I am a longtime Julia contributor with a special interest in GPU programming and HPC. I currently work at Amazon Braket as a scientist.

- Quantum Computing with Julia

I'm a PhD candidate in Chemical Engineering and Computation and DOE Computational Science Graduate Fellow at MIT.

- Feasible nonlinear optimization with LFP-SQP

Kevin Squire is a Senior Software Engineer at Second Spectrum, Inc., where he works in the AI group on machine learning algorithms and infrastructure. Previously, he completed a postdoc in Computational Genetics at UCLA and taught Computer Science at the Naval Postgraduate School. He received his PhD in Electrical Engineering from the University of Illinois. Kevin has been interested in Julia since its first public release and was an early contributor to the language.

- Deep Dive: Creating Shared Libraries with PackageCompiler.jl
- Creating a Shared Library Bundle with Package Compiler

PhD student in the University of Évora

- CompositionalNetworks.jl: a scaling glass-box neural network

I am a PhD student in Computational Mechanics at Chalmers University of Technology (Sweden), where I use Julia for doing Finite Element simulations.

- Improving Gender Diversity in the Julia Community
- Discussing Gender Diversity in the Julia Community

Started learning Julia a year ago! Electrical Engineering B.Sc graduate in May 2021 from Winnipeg, Canada. Aspiring Julia data scientist with interests in scientific machine learning.

- The wonderfully helpful Julia community

- Lale in Julia: A package for semi-automated data science

developer NeuralPDE

- Decomposition Physics-Informed Neural Networks (PINNs)

Senior Machine Learning Engineer at Beacon Biosignals, working with julia since 1.0.

- kubernetes-native julia development

I'm a contributor to the Julia language and many packages.

- Deep Dive: Creating Shared Libraries with PackageCompiler.jl
- PGFPlotsX.jl - Plotting with LaTeX, directly from Julia
- Creating a Shared Library Bundle with Package Compiler

Working on a sparse-AI actor runtime, researching decentralized algorithms, playing with runtime code generation.

- Catwalk.jl: A profile guided dispatch optimizer

I am a 16 year old student at Wilton High School in Wilton, CT. Currently, I am self-teaching myself Julia and I am also learning Java in my AP Computer Science Class in school.

- Learning during the pandemic

I am a full time academic teacher and researcher at the University of the Bio Bio, Concepcion, Chile. My research interests are related with sensors and embedded solutions for extreme and hostile environments like polar regions. I am also interested in low level digital hardware development like FPGA and ASIC.

- Julia managed sensor - actuator network for Antarctic studies

A Biostatistics PhD student from the University of Oslo. I'm working on combining computer simulations with Bayesian statistical models. I have been a big fan of Julia since version 0.4. My research interests are Bayesian statistics, symbolic computing and applied category theory.

- Introduction to Bayesian Data Analysis
- Designing ecologically optimized vaccines
- Transpilers.jl - Transpile all the things

The author of PyYAML, LibYAML, HTSQL, and DataKnots.

- PrettyPrinting: optimal layout for code and data
- FunSQL: a library for compositional construction of SQL queries

Mathematics undergraduate student and Economics graduate. I love playing computational statistics using Julia.

- Discussing Gender Diversity in the Julia Community

Research Associate and PhD candidate at TU Berlin, open-science and macro-energy system modeling, https://github.com/leonardgoeke

- AnyMOD.jl: A Julia package for creating energy system models

I have been working as a data scientist and technical writer for about 2.5 years. In my projects, I try to combine both disciplines either by documenting thoroughly a data science project, or following a data-driven approach (if possible) when documenting products and technical processes.

- My experience trying to reinvent the FluxML website

Lingling Fan is a full professor at University of South Florida, working on the following research areas: control, dynamics, optimization, and system identification of power systems, power electronics and electric machines. Her recent research interests include mechanism analysis of various dynamics seen in real world (wind farm oscillations, solar PV tripping), computing, and programming with Julia.

- Julia Admittance: A Toolbox for Admittance Extraction

Dr Tang is a research scientist in the CCS-7 Programming Models team at Los Alamos National Laboratory. His research interests include programming model, co-design, performance/energy analysis and modeling. Dr Tang received his Ph.D. from the Department of Computer Science and Engineering at University of Notre Dame in 2017.

- In-Situ Data Analysis with Julia for E3SM at Large Scale

Interested in networks medicine, systems biology and bioinformatics, I am currently a predoctoral researcher in the group of Jörg Menche at the Max Perutz Labs and the Research Center for Molecular Medicine in Vienna, Austria. You can learn more about me on my personal website.

- BioProfiling.jl: Profiling for high-content cell imaging

Logan is the Community Manager for the Julia Language. Get in contact with him here: https://twitter.com/OfficialLoganK

- Learn about Blockchain Development in Julia
- Diversity and Inclusion in the Julia community

I am an undergraduate physics student at the University of Turin. I have a strong interest in many aspects of physics, ranging from theoretical physics to HEP and cosmology. Currently I am doing my undergraduate thesis about the study of the properties of the hypertriton nuclei with ALICE's data using machine learning techniques. Meanwhile, I am one of the co-founder of MLJC, a student association that focuses on ML research and know-how sharing. My interest are mainly on scientific ML, NLP & NLU, and the theoretical aspects of ML. One of my strongest motivation is to help accelerating pure sciences using ML approaches. I participated in the ProjectX 2020 competition held by the University of Toronto in the UniTo team.

- Physics-Informed ML Simulator for Wildfire Propagation

PhD student in computer science at the University of Vaasa. Research interests in compuational methods for efficient and reliable positioning.

- IntervalLinearAlgebra.jl: Linear algebra done rigorously

My name is Luca Luberto and I am a PhD student at the Institute of Computational Phyiscs in Engineering, Technical University of Kaiserslautern.

Currently I am working on the simulation of selective laser melting.

- Simulation of additive manufacturing processes in Julia

Geo-HPC, GPUs, supercomputing & Julia @ VAW ETHZ.

- Solving differential equations in parallel on GPUs

- NOMAD.jl

Lyndon White (@oxinabox) is a research software engineer at Invenia Labs (Cambridge, UK). He helps researchers use machine learning, constrained optimization, and generally tools from the technical computing domain to optimize the power grid. He get to do all the best parts of being a software developer and all the best parts of being a researcher, its great.

He works a lot on the Julia AutoDIff code, and is the leader of the ChainRules project.

- Fancy Arrays BoF 2
- ExprTools: Metaprogramming from reflection

After completing studies in mechanical engineering in Germany, worked for a coupled of years in the industry and academia. Now working in Switzerland in the aviation sector and developing code as a hobby.

- Flywheel: 1-D Finite element tool for gyroscopic systems

GeoData Scientist at Deltares. Github: @evetion

- SpaceLiDAR.jl: Processing ICESat-2 & GEDI satellite LiDAR data

Malcolm is a simulation engineer at Deloitte Digital Australia with a background in real-time simulation in the automotive and transport domains. Currently he is developing real-time simulations of large transport networks as part of the Optimal Reality team, and enjoying contributing to Julia.

- Enabling Rapid Microservice Development with a Julia SDK

Manuela Vanegas Ferro is a PhD candidate in Biological Design at Arizona State University. She earned a Bachelor of Science degree in Biology and Microbiology and a Master of Science degree in Computational Biology from Universidad de los Andes in Colombia. Manuela has experience in modeling complex biological systems at different scales. Currently, she is developing an individual-based model that integrates biological features of coffee rust disease and socio-economic aspects of coffee farmers' management practices to find optimal long-term farming strategies.

- An individual-based model to simulate Coffee Leaf Rust epidemics

PhD student at Paderborn University. My main research interest lies in multiobjective (non-linear) optimization.

- A Derivative-Free Local Optimizer for Multi-Objective Problems

Marcelo Forets is an Applied Mathematician that works as Assistant Professor at Universidad de la República (Uruguay). Born in Uruguay (Montevideo, 1988), he graduated in Physics and in Electrical Engineering, then moved to France for a PhD in Mathematics and Informatics (Univ. Joseph Fourier, France) on the quantum random walk, a model of particular interest to Quantum Computing. He was a post-doc researcher at VERIMAG laboratory of Université Grenoble Alpes (France) under the supervision of Oded Maler and Goran Frehse, where he started to develop what is now the JuliaReach package ecosystem. His research has to do with developing innovative numerical tools that impact decisions regarding reliability, correctness and safety of control systems, hybrid dynamical systems, and robustness analysis of neural networks.

- It's all Set: A hands-on introduction to JuliaReach
- Set Propagation Methods in Julia: Techniques and Applications

I am a PhD Student at Università degli Studi di Genova. I am a memeber of the Euclid Consortium. Euclid is a space-based mission which will map the galaxy distribution in order to study the nature and origin of Dark Energy and Dark Matter. In the consortium, I am active in the developement of tools used to analyze data and perform cosmological analysis.

- Speeding up cosmological data analysis with Julia

I'm a mathematician, researcher in geometric group theory at KIT (Karlsruhe, Germany); I received my PhD in pure mathematics in 2014 and since then changed my scientific focus to aspects including more computational problems. I've been coding in julia for since 2016 mostly around group theory, mathematical optimization and certified computation.

- Symmetry reduction for Sum-of-Squares programming

Mark Kittisopikul is a postdoctoral Scientific Computing Associate at the Janelia Research Campus of the Howard Hughes Medical Institute working with the Scientific Computing team to support the computational needs of the lab of Philipp Keller for next-generation light-sheet microscopy.

- Processing Light-Sheet Microscopy Data Using Julia

Mark Schulze is a legal expert on corporate law & tax, but that only happened to happen after trying to settle in the information & electrical engineering field. After working as an audio engineer in the first place, he continued to work on web applications as a hobby and now approaches to learn backend orientated skills in Julia, that would help to go further in legal tech practises and knowledge engineering.

- TypeDBClient.jl - interface to a strongly-typed database

Senior Lecturer (associate professor) with the University of Cambridge Department of Computer Science.

- Modelling cryptographic side-channels with Julia types

Ph.D. student in Electrical Engineering @KU Leuven and @Energyville, Belgium.

- PowerModelsDistributionStateEstimation.jl

- Modia – Modeling Multidomain Engineering Systems with Julia

Mary is a Senior Research Software Engineer at Brown University’s Center for Computation and Visualization, and a consulting Senior Software Engineer at RelationalAI. She works with researchers to provide scientific and technical computing expertise, combined with best practices, to advance computational research. She received her B.S. in Engineering Science from Smith College and her M.S. in Computer Science from Brown University.

- Types from JSON

- InvertibleNetworks.jl - Memory efficient deep learning in Julia

Mathieu is a researcher in computational mathematics working at the Zuse Institute Berlin. His interests span mixed-integer, convex optimization, applications in engineering and statistics.

- Flexible set projections with MathOptInterface
- FrankWolfe.jl: scalable constrained optimization

Software Developer at Invenia Technical Computing.

- Distributed Computing using AWSClusterManagers.jl

Will Fill out later

- Bootstrapping Data Science and Diversity

Matthew Fishman received a PhD in physics from Caltech in the spring of 2018. His thesis was on the development of new tensor network algorithms for studying quantum many-body systems. In the fall of 2019, he started as an Associate Data Scientist at the Center for Computational Quantum Physics, part of the Flatiron Institute in New York City. There, he is lead developer of the C++ and Julia versions of the ITensor library, a leading software package for performing tensor network calculations.

- What's new in ITensors.jl

MIT Chemical Engineering Ph.D. Student

- Simulating Chemical Kinetics with ReactionMechanismSimulator.jl

Computer Science PhD student at Princeton University's Center for Information Technology Policy (CITP).

- GerryChain.jl: detecting gerrymandering with Markov chains

Matthew E. Wilhelm received a B.S. in Applied Mathematics from the University of North Carolina at Greensboro, Greensboro, NC, USA (2009), and a M.S. in Chemical Engineering from Columbia University, New York, NY, USA (2011). He is currently a PhD Candidate in Chemical and Biomolecular Engineering at the University of Connecticut where his research interests include: nonconvex optimization, dynamic simulation and optimization, mathematical biology, and engineering & STEM pedagogy.

- Set Propagation Methods in Julia: Techniques and Applications

I'm a bachelors student of Automation Engineering. I have experience working on embedded systems, Data analysis, Machine learning Topics and Wireless Communications. All of these topics in real world applications.

The last two years i was be a part of the Chilean Antarctic Scientific Expeditions, I collaborated with scientists of different nationalities and specialities in interdisciplinary works relatives to Antarctic Sciences.

- Julia managed sensor - actuator network for Antarctic studies

- Solving differential equations in parallel on GPUs

Since April 2020 I am full professor for Algorithmic Algebra and Geometry at TU Kaiserslautern, Germany. My research focuses on computer algebra, group theory and algebraic Lie theory.

Besides being one of the principal investigators on the grant behind OSCAR, and one of its developers, I am also core developer of the GAP computer algebra system for computational group theory.

Outside of mathematics, I've been involved in many open source projects over the past decades; e.g. in the distant past, I served as project leader for ScummVM as well as the Fink project, and contributed to TeXShop.

- The OSCAR Computer Algebra System

I am an AI Researcher at Ericsson Research. My research interests lie in reinforcement learning, planning under uncertainty, and AI safety. Prior to joining Ericsson I completed my PhD at Stanford University under the supervision of Prof. Mykel Kochenderfer. My thesis was about safe and scalable planning under uncertainty for autonomous driving and all the code was written in Julia. At Juliacon 2021 I will present work I did during my thesis.

- Probabilistic Model Checking using POMDPModelChecking.jl

I am a graduate student in the department of industrial engineering at Seoul National University in South Korea.

- Github: https://github.com/maxkapur

- Email: maxkapur@gmail.com

- Blog: maxkapur.com

- DeferredAcceptance: Solving and analyzing school-choice problems

- Single-cell resolved cell-cell communication modeling in Julia

Mia is a graduate student at the University of British Columbia, working with Michael Friedlander. She's been interested in computers and programming since being in elementary school, and after finishing her undergraduate in astrophysics at UBC she is very excited to continue learning in (and hopefully contributing to!) the field.

- AtomicSets.jl

By training a chemist, who got more and more twisted towards the "dark side" of numerical analysis. Now working as a PostDoc at the Applied and Computational Mathematics lab of RWTH Aachen University, Germany. Lead developer of DFTK, a Julia code for mathematical research in on density-functional theory (a quantum chemistry method).

- A mathematical look at electronic structure theory
- Building a Chemistry and Materials Science Ecosystem in Julia

- What's new in COSMO?

I am a postdoctoral fellow and research software engineer at the Numerical Simulation Research Group of the University of Cologne, Germany. My research focus is on numerical methods for adaptive multi-physics simulations, high-order schemes, and high-performance computing.

- Julia in High-Performance Computing
- Adaptive and extendable numerical simulations with Trixi.jl

I am a postdoctoral researcher at Ghent University. My interest is in using computational intelligence to understand and design biological systems.

- Learning to align with differentiable dynamic programming

Physics Undergraduate based in Mexico City, UNAM. I enjoy handstands and coding in Julia.

- Towards a symbolic integrator with Rubin.jl
- DoctorDocstrings.jl - an interactive docstrings worfklow tool

Miha is a theoretical physicist by training and holds an MSci degree from Imperial College London. After completing his Masters, he moved to the countryside to pursue a PhD at the University of Oxford where he analysed the data from the Large Hadron Collider at CERN searching for a rare decay of the Higgs boson. He now works as a Research Software Engineer at Invenia Labs, where he builds tools that accelerate research in electricity grid efficiency.

- Everything you need to know about ChainRules 1.0

Mike Klepper is a software engineer working in web-database connectivity and IoT arenas. He holds a BSc in mathematics from the University That Shall Not Be Named, and a MSc in computer science from Franklin University in Columbus, Ohio.

He is the author of several blogs including "Patriot Geek" and "Red White and Julia".

He is currently pursuing a master's degree in mathematics from the Open University in the UK.

In his copious spare time he is the operations officer for a community support group in eastern Pennsylvania, where he is developing the concepts of "counter-logistics" and "logistic system reverse engineering."

- A Tool for Julia Bloggers

I am a physicist studying exotic matter formation via resonance phenomena of the QCD.

Field: elementary particles, hadron spectroscopy

Organizations: CERN (LHCb, COMPASS), JPAC, ORIGINS Cluster

- Julia for data analysis in High Energy Physics

PhD student in Climate Computing

Atmospheric, Oceanic and Planetary Physics

University of Oxford

milan.kloewer@physics.ox.ac.uk

www.milank.de

twitter @milankloewer

github @milankl

- 3.6x speedup on A64FX by squeezing ShallowWaters.jl into Float16

- Linear programming by first-order methods

I'm a third-year Math/Computer Science major at Grinnell College. I'm interested in data protection, cybersecurity, and user interface. In my free time, I'm a captain of Grinnell's Mock Trial Team, and I bake and cook.

- Applications of Julia for Network Science Text Analysis

I'm a postdoctoral researcher at the Luxembourg Centre for Systems Biomedicine, recently finished my PhD at Charles university in Prague, Dept. of SW engineering. I'm working on various computationally intensive problems in bioinformatics and cheminformatics.

- COBREXA.jl: COnstraint-Based Reconstruction & EXa-scale Analysis

### main theme

My main research focus has been to find, study, and develop a **high-level computer programming formalism
allowing to deform programs in a continuous fashion** (just as one can deform recurrent neural networks in a continuous fashion).

I was trying to approach this problem from various angles: doing research in the mathematics of continuous domains

for denotational semantics of programming languages, studying theoretical neuroscience, and so on.

Finally, our research collaboration was starting to see the hints of the possible solution from approximately Fall of 2012,

and the formalism for continuously deformable programs was developed by our research collaborations in 2015-2016.

These days I am continuing to focus on studying and experimenting with this formalism and I am hoping that it will

eventually stop being a purely research subject and will become a technology.

I maintain a Web site for this formalism here: https://anhinga.github.io/

I also maintain a list of open problems and promising research and technological directions and interdisciplinary

connections related to this formalism: https://www.cs.brandeis.edu/~bukatin/dmm-collaborative-research-agenda.pdf

### brief timeline

My background in software, mathematics, and science goes back to Soviet Union, to machine code, Algol-60, Fortran-4,

and to punched cards; to Pushchino, the Biological Center of the Soviet Academy of Sciences, and to

the Mathematical class of Moscow High School number 7.

I started to focus on continuous models of computations in college, then emigrated to USA, worked as

a scientific programmer for Alex Rashin at Biosym Technologies doing computational geometry and computational chemistry

(I was the second author on several papers in *The Journal of Physical Chemistry* and *Biophysical Chemistry*

from that period), then did a PhD in Computer Science at Brandeis University focusing of mathematics

of continuous domains for denotational semantics (this is a copy of my 2002 PhD thesis: https://arxiv.org/abs/1512.03868).

In parallel, I worked in various places in the software industry. There I had a chance to first touch

dataflow programming, Common Lisp, and actor model of programming.

This century I have been working at a geographic software company (ownership of it went through acquisitions, spin-offs,

and such, so one very long employment looks like several shorter ones from a formal viewpoint),

while doing research in parallel. My research focus was mostly on theoretical neuroscience for a while,

then a research collaboration on deep connections between *partial metrics* and *fuzzy equalities*,

and finally (from approximately Fall of 2012) a research collaboration

on deep connections between *partial contradictions* and *vector semantics of programming languages*

and, from 2014-2015 on, a series of research collaborations on *neuromophic computations with linear streams*.

Starting from about 2011 I was gradually moving from just being a lover of computer animation and electronic music to

my first attempts to make some visual, audio, and audio-visual art of my own, and I am continuing to make new computer art every few months or so.

It involved playing a bit with MilkDrop 2 for WinAmp, mixing music a bit with Serato DJ,

doing a lot of animations and a bit of sound work in Processing, doing a tiny bit of that in Clojure,

and finally working a bit with shader-based GLSL animations.

### 2015-present

*Linear streams* are streams for which linear combinations of several streams are defined. If one makes sure that

linear computations and general (often non-linear) computations are interleaved, then one gets continuously deformable programs which

we call **Dataflow matrix machines (DMMs)**. Another way to obtain DMMs is to start with recurrent neural networks

and replace streams of numbers with linear streams and allow complicated "activation functions"

(that is, transformations of linear streams) with arbitrary arity.

This setup also allows these neural machines to have very natural and flexible self-modification facilities.

There are toy implementations in Processing with mutable matrices, and the reference implementation in Clojure with

immutable streams of tree-shaped "flexible-rank tensors". The reference paper on DMMs is https://arxiv.org/abs/1712.07447

I hope to create the next application of this formalism in Julia

(both **Julia Flux** and **JAX** are the machine learning frameworks which finally have sufficient flexibility

we need to take full advantage of the flexibility of DMMs). I started to switch to Julia in the early 2020.

I recently sketched a three-page note outlining my hopes in this sense: https://www.cs.brandeis.edu/~bukatin/towards-practical-dmms.pdf

- Multiplying monochrome images as matrices: A*B and softmax

A topology optimization researcher, a co-maintainer of Turing.jl, a scientist at Pumas-AI, and an enthusiastic learner of anything "scientific computing".

- Nonconvex.jl
- TopOpt.jl: topology optimization software done right!

A Machine Learning Engineer with a background in robotics and mechatronics system. My primary focus is in the areas of optimization and AI.

- Julia for end to end financial analysis

I am Associate Senior Lecturer at the Department of Mathematical Sciences of Chalmers University of Technology and University of Gothenburg and working on statistical theory and methodology for dynamical stochastic models. In general, dynamical stochastic models describe the evolution of processes and systems which have dynamics with temporal or spatial interactions and show stochastic behaviour. Applications of such models are found in all areas, be it to model the change in the extension of the West Antarctic ice shelf, the interaction of neurons in the brain or the deformation of tissue during tumour growth.

- Github: https://github.com/mschauer
- Academic website: http://www.math.chalmers.se/~smoritz/index.htm
- Twitter: @MoritzSchauer

- ZigZagBoomerang.jl - parallel inference and variable selection

Research Software Developer at UCL during the day, binary builder during the night.

- Code, docs, and tests: what's in the General registry?
- Runtime-switchable BLAS/LAPACK backends via libblastrampoline

I'm a PhD student at University of Tübingen, working on probabilistic numerics, machine learning, and Bayesian inference.

- Probabilistic Numerics for Differential Equations

Niall is a computational scientist at the Irish Centre for High End Computing where he works on a variety of projects covering quantum computation, AI and data analytics.

- Distributed Quantum Circuit Simulation

My coding and musical lives began early, starting piano lessons at the age of 4 and computing with the advent of the ZX80! After an undergrad Masters degree in Electronic Engineering Science and a 20+ year career in Software Testing, I recently completed a Masters of Applied Data Science at the University of Canterbury, New Zealand. I had the opportunity to bring together my love of data, computing and music to explore Sonification for my degree project and I hope to build on it beginning work on a PhD later this year.

Although experienced in software engineering, I am new to Julia and keen to contribute to the friendly, supportive, growing community.

- Sonification: Exploring streaming data using live music coding

Canadian economist currently living in Toulouse, France. I'm interested in many fields, including numerical methods. Scarred for life by the experience of waiting six months for my estimates to converge.

- SpeedMapping.jl: Implementing Alternating cyclic extrapolations

Senior Machine Learning Engineer at Second Spectrum.

- Deep Dive: Creating Shared Libraries with PackageCompiler.jl

Oleg is a data scientist at Fonterra, a New Zealand Dairy Co-operative. Much of his work concerns milk production planning problems. Previously, he worked at Suez, who supply systems for the control of water utilities based on integer programming.

- Solving optimization problems at Fonterra

I'm a master student in computer science in Heidelberg, Germany. I like to teach and blog about programming especially about Julia.

- ConstraintSolver.jl - First constraint solver written in Julia
- Javis.jl - Julia Animations and Visualizations

- New tools to solve PDEs in Julia with Gridap.jl

Oscar Dowson is a core-developer of JuMP and member of the JuMP steering committee.

- The state of JuMP

PhD in Engineering Science by Tecnologico de Monterrey, Mexico.

Current postdoctoral fellow at University of Waterloo.

My research interests include: optimal control, model predictive control, scheduling and nonlinear optimization of chemical and energy processes.

- Optimal control problems in Chemical Engineering with Julia

I am a master's student at Utrecht University, and a contributor for Catlab.jl

- Shaped Data with Acsets

I'm currently a postdoctoral researcher at the University of Chicago working on a class of strategies used to accelerate learning the properties of systems simulated with molecular dynamics.

- Enhanced Sampling in Molecular Dynamics Simulations with Julia

I am a research associate and software engineer at Tufts University's MGGG Redistricting Lab, an interdisciplinary research group that applies mathematical techniques to the study of gerrymandering.

- GerryChain.jl: detecting gerrymandering with Markov chains

Profession: Mechanical engineer

Location: Germany, Landshut

Github: https://github.com/pbayer

Linkedin: https://www.linkedin.com/in/paul-bayer-4104a78/

- Actors.jl: Concurrent Computing with the Actor Model

I am a research scientist at the IBM Research working on the following areas: AutoML, AutoAI, RL/ML Optimization, and Decision Optimization.

- Finding an Effective Strategy for AutoML Pipeline Optimization
- Lale in Julia: A package for semi-automated data science
- Data driven insight into fish behaviour for aquaculture

I am a systems biology PhD student with background in molecular biology. My doctoral research at the University of Oxford aims at improving our mechanistic understanding of cell cycle dynamics with mathematical models. This involves (1) casting chemical reaction networks into executable models, (2) obtaining highly multiplexed snapshot measurements of cell cycle regulators, from which we reconstruct their time-courses, and (3) developing parameter optimisation and model reduction/selection toolboxes.

- Systems Biology in ModelingToolkit

Thermodynamics enthusiast.

- Clapeyron.jl: An Extensible Implementation of Equations of State

Software developer, electrical engineer, IC designer. Author of Apicula FPGA tools and Mosaic IC design software.

- JuliaSPICE: A Composable ML Accelerated Analog Circuit Simulator

Scientific programmer at University of Leipzig.

- Intercepts in pairs of geographical tracks from TrackMatcher

Ph.D. in Chemical & Biomolecular Engineering at Cornell University

- Optimization-based gap finding and filling in Julia

Philipp A. Witte is a researcher at Microsoft Research for Industry (RFI), a new initiative within Microsoft for developing innovative research solutions for industry-related problems ranging from AI/ML to edge- and high-performance computing. Prior to Microsoft, Philipp received his B.Sc. and M.Sc. in Geophysics from the University of Hamburg and his Ph.D. in Computational Science and Engineering from the Georgia Institute of Technology. During his Ph.D., Philipp worked with Professor Felix J. Herrmann at the Seismic Laboratory for Imaging and Modeling (SLIM) on computational aspects of least squares seismic imaging and full-waveform inversion. He has authored and contributed to multiple open-source software packages, including Devito, the Julia Devito Inversion framework (JUDI) and InvertibleNetworks.jl, a Julia framework for deep learning with normalizing flows.

- InvertibleNetworks.jl - Memory efficient deep learning in Julia
- Redwood: A framework for clusterless supercomputing in the cloud

- Unleashing Algebraic Metaprogramming in Julia with Metatheory.jl

Phillip was a struggling mathematician, then a linguist and now a neuroscientist, but always a hacker.

- Non-parametric Methods for Mixed-Effects Models of EEG Data
- Fast Simulation-Based Power Analyses for Mixed-Effects Models
- Effects.jl: Effectively Understand Effects in Regression Models

I am an Imperial chemical engineering undergraduate with a great interest in all things related to thermodynamics! I’ve been using Julia for the past two years to develop an extensible open-source implementation of equations of state: OpenSAFT

- Clapeyron.jl: An Extensible Implementation of Equations of State

Przemysław Szufel is an Assistant professor at SGH Warsaw School of Economics, Poland and an Adjunct Professor, Cybersecurity Research Lab, Ted Rogers School of Management, Ryerson University, Toronto.

He has first started using Julia at the version 0.3. He is a co-author of the book “Julia 1.0 Programming Cookbook: Over 100 numerical and distributed computing recipes for your daily data science workﬂow” which has been translated by O’Reilly from English to Japanese. Przemysław also holds currently 4-th place on the StackOverflow portal answering Julia-related questions. He is the maintainer and co-auhtor of three Julia libraries in the public repository: OpenStreetMapX, OpenStreetMapXPlot and SimpleHypergraphs.

He is a co-author of over 40 publications, including handbooks and journal papers, in the area of applying advanced analytics, machine learning, simulation methods and optimization.

- Simulating a public transportation system with OpenStreetMapX.jl

Usually writing code (or docs!) or triathlon-ing.

More at my website.

- Introducing Chemellia: Machine Learning, with Atoms!
- Building a Chemistry and Materials Science Ecosystem in Julia

Age:

10 Years

Education:

6th Grade, Sree VidyaNikethan International School, Hyderabad, India

- Musical Julia

A random Julia enthusiast, occasional contributor.

- ReTest.jl - more productive testing

My research focuses on developing tools to image cellular function at high resolution. We develop techniques to measure multidimensional information in small biological objects such as cells, cellular organelles or other small structures of interest. Computer-based reconstruction methods, especially inverse-modeling based in automatic differentiation are of primary interest.

- FourierTools.jl | Working with the Frequency Space
- View5D.jl
- TiledViews.jl

- IndexFunArrays.jl | Fun with indices (and functions on them)

4th year PhD student at the Julia Lab, MIT.

- Bayesian Neural Ordinary Differential Equations

I am a PhD Candidate at the Julia Lab at MIT. I've been working in Julia for the past 6 years.

- Surrogate Models of Multiscale Dynamical Systems

Ravinder works on machine learning in material design, dynamic fracture and cracks propagation on ballistic impact, and two-dimensional materials. He completed his B.Tech in Civil Engineering from IIT Roorkee. He worked in the industry for a year after which joined M3RG, IIT Delhi as a research scholar.

- PeriDyn: A Peridynamics Package

Richard Gankema is a Computer Scientist at RelationalAI, working on various systems-related topics such as data structures, memory management and query execution. Before joining RelationalAI he worked as a PhD candidate at CWI’s Database Architectures group in Amsterdam, which sparked his interest in vectorization and other techniques for optimizing the performance of data-processing.

- Vectorized Query Evaluation in Julia

- Power Market Tool (POMATO)

I am a researcher at INRIA Sophia Antipolis (France) with interest in Mathematical neurosciences, modeling synaptic plasticity and analysis of PDEs. Please, have a look at my website.

- BifurcationKit.jl: bifurcation analysis of large scale systems

Russell Bent (Ph.D.) is a scientist in the Applied Mathematics and Plasma Physics Group (T-

5), where he leads LANL’s inter-organizational Advanced Network Sciences Initiative (ANSI).

ANSI is an interdisciplinary initiative that enables fundamental and applied research to

address long-term challenges in critical infrastructure design, operation, and security. Dr.

Bent is the principal investigator for several DOE projects in critical infrastructure systems

research and development that focus on improving robustness of infrastructure systems to

extreme events, increasing resilience of distribution networks, modeling interdependencies

between systems, managing disasters that impact critical infrastructure, modeling smart

grid technologies, and developing methods for mixed-integer, non-linear optimization. He is

also the lead developer for the software Alpine, A Global Solver for Nonconvex MINLPS and

the software GasModels.jl, a toolbox for modeling natural gas systems. He is the author of

one book, Online Stochastic Combinatorial Optimization, and over 100 peer reviewed

journal and conference publications.

- Gasmodels,jl: Optimization for Natural Gas Systems in Julia

- Hybrid Strategies using Piecewise-Linear Decision Rules

N/A

- Solving differential equations in parallel on GPUs

Samuel Ozminkowski is a M.S. student in Statistics at the University of Wisconsin-Madison, in the Solis-Lemus lab. His work is focused on using Bayesian models with network predictors, specifically focusing on microbiome networks. He earned his undergraduate degree in Computer Science at the University of Michigan.

- Bayesian network regression with applications to microbiome data

Sam Urmy, PhD (@ElOceanografo), is a Research Fish Biologist at the US National Oceanic and Atmospheric Administration's Alaska Fisheries Science Center. He has used Julia for simulating seabirds, detecting dolphin clicks, and, currently, analyzing sonar surveys of fish in Alaska.

- Bootstrapping Data Science and Diversity

Santiago Badia is Professor of Computational Mathematics at Monash since June 2019. He obtained his PhD at Universitat Politècnica de Catalunya (UPC) in 2006. Previously, he worked at the Applied Mathematics departments at Politecnico di Milano (Italy) in 2006 and Sandia National Labs (New Mexico, USA) in 2007-08. He joined UPC in 2009, where he was appointed Professor of Computational Science and Engineering in 2017. He is adjoint researcher at CIMNE (Barcelona), where he leads the Large Scale Scientific Computing Department.

He works on the numerical approximation of partial differential equations (PDEs), e.g., using finite element methods, for modelling fluid and solid mechanics, electromagnetics, and multiphysics problems. He is particularly interested in large scale scientific computing and numerical linear algebra.

As a by-product of his research, Prof Badia leads some high-performance scientific projects, like FEMPAR. FEMPAR provides state-of-the-art numerical discretizations of PDEs and highly scalable numerical linear algebra solvers. FEMPAR has been used to model metal additive manufacturing, superconductor devices, breeding blankets in fusion reactors, or nuclear waste repositories. It has attained perfect weak scalability up to 458,672 cores in JUQUEEN (Germany) solving up to 60 billion unknowns. In 2019 he co-started the Gridap project, which heavily relies on functional programming and multiple dispatching in Julia, with the aim to create an easy-to-use but very efficient PDE solver.

- New tools to solve PDEs in Julia with Gridap.jl

I am currently pursuing MPhil in Statistics from University of Pune, India. I have worked as a Student Developer for Google Summer of Code 2020 with The Julia Language Organisation, during which I built the algorithmic variants of the nested sampling algorithm in Julia. I am also working with the R Contribution Working Group to develop a novice-friendly "R Developer's Guide".

- Algorithmic Variants of Nested Sampling

I'm a software engineer at Amazon working on Amazon Braket, a managed quantum computing platform. I graduated from The Ohio State University with a Master's in Computer Science in August 2019. I worked on high performance computing for representation learning in graphs at the Data Mining Research Laboratory at OSU. I dabble in quantum computing, graphs, high performance computing and most recently in serverless compute.

- Quantum Computing with Julia

Satvik is a co-founder and head of Machine Learning at Temple Capital, a crypto currency quant fund.

- Rewriting Pieces of a Python Codebase in Julia

PhD Candidate at Cornell University

- Exploiting Structure in Kernel Matrices

Software engineer at Julia Computing and one of the maintainers of the Julia extension for VSCode.

- Package development in VSCode

they/them

Seth is a frontend web developer for Beacon Biosignals and part-time Exercism mentor for the Julia language. They've been developing in Julia since November 2019 and are a contributor to StaticArrays.jl. Their specialty is esoteric languages.

- Disrupting Esoteric Language Microbenchmarks with an 80-line JIT

Shahriar Iravanian, MD, MSE, is a practicing cardiac electrophysiologist and biophysical researcher with an interest in non-linear dynamics and high-performance computing with a focus on the modeling of cardiac arrhythmias. He received a Master of Science in computer science from Johns Hopkins University and finished his cardiology and electrophysiology training at the Emory University in 2011.

- Systems Biology in ModelingToolkit

Shashi is a grad student at MIT. Yingbo is an undergrad at UMBC and works at Julia Computing. We like coding in Julia.

- Symbolics.jl - fast and flexible symbolic programming

Shivay Lamba is a software developer specializing in DevOps, Machine Learning and Full Stack Development.

He is an Open Source Enthusiast and has been part of various programs like Google Code In and Google Summer of Code as a Mentor and is currently a MLH Fellow. He has also worked at organizations like Amazon, EY, Genpact. He is a Tensorflow.JS SIG member and community lead from India.

- GADM.jl : Julia Package for Polygon Provision from GADM Dataset

Shlok is a Senior Research Analyst at the Federal Reserve Bank of New York working on the DSGE team in the Research group. He holds a B.S. in Economics and a B.S. in Statistics and Machine Learning from Carnegie Mellon University. He is interested in using Julia to develop scalable models for macroeconomic forecasting and spatial economics research.

- Modeling the Economy During the Pandemic

A maintainer of Julia IDEs, julia-vscode and Juno.

Also involved with the Julia compiler development, mainly around its abstract interpretation based type inference implementation.

- A quick dive into Julia's type inference algorithm
- JET.jl: The next generation of code checker for Julia
- Package development: improving engineering quality & latency

- NExOS.jl for Nonconvex Exterior-point Operator Splitting

- Building Interactive REPL-based Visualizations in GridWorlds.jl

Simon is the lead software engineer at the CliMA project.

- Julia in High-Performance Computing
- Deep Dive: Creating Shared Libraries with PackageCompiler.jl
- ClimaCore.jl: Tools for building spatial discretizations
- Creating a Shared Library Bundle with Package Compiler

Simon Danisch is a senior developer at Beacon-Biosignals. Simon has been part of the Julia community for more than 8 years and has contributed many Julia packages:

- GeometryBasics
- GPUArrays
- Makie
- PackageCompiler
- JSServe
- FileIO

- Makie showcases and future

- Physics-Informed ML Simulator for Wildfire Propagation

Simon is a Software Engineer from Switzerland. Most of Julia contributions are related the the JuliaGraphs ecosystem.

- Writing fast sequential Julia Code
- Graph Machine Learning with GraphKernels.jl
- Efficient graph data structures: What we have and what could be

Postgraduate computer science student at the University of Cambridge, currently working with Markus Kuhn.

- Modelling cryptographic side-channels with Julia types

Sophie is a math PhD student at Stanford University. Her research interests are focused on dynamical systems including topological invariants of dynamical systems, composing dynamical systems, and the question of how continuous dynamical systems compute.

- AlgebraicDynamics: Compositional dynamical systems

Julia co-creator & co-founder of Julia Computing.

- State of Julia

Stephan Sahm is Senior Data Science and ML Engineering Consultant. Having programmed in Java, Matlab, Python, R, Scala and Julia he appreciates the combination of simplicity and speed which the Julia language brings to Data Science. With master degree in math/stochastics and cognitive science together with 5 years industry experience he can help you bring your favourite Data idea into production.

- Monads in Julia: TypeClasses.jl and DataTypesBasic.jl
- Monads 2.0, aka Algebraic Effects: ExtensibleEffects.jl

I hold a PhD Economics from the University of Edinburgh. I work in London as a quantitative research in cash equities. I have done a few open source numerical mathematics packages mainly in fixed point acceleration and shape preserving splines.

- HighFrequencyCovariance: Estimating Covariance Matrices in Julia

- MadNLP.jl: A Mad Nonlinear Programming Solver.

I'm a postdoc at Julia Lab. I'm working on parallelism and compiler.

- JuliaFolds: Structured parallelism for Julia
- Teaching parallelism to the Julia compiler

Theo Diamandis is a PhD student studying optimization at MIT.

- Sparse Matrix Decomposition and Completion with Chordal.jl

Hi! I am a PhD student at TU Berlin and Julia adept since 0.4! I develop packages for probabilistic inference and more especially Gaussian Processes. For more info check my website theogf.github.io

- Sampling Live Visualizations with Turkie and TuringCallbacks

- ConstraintProgrammingExtensions.jl

MS in mathematics, Phd in mechanical engineering. Has worked in biotechnology for 20 years. Programmed in FORTRAN 3 years, Perl 5 years and R 15 years. Has been dipping toes in Julia for 2 years.

- Fitting Plate-reader Curves with Julia

I'm a software engineer at Julia Computing, working on Julia's GPU packages and compilers.

- GPU programming in Julia BoF
- CUDA.jl 3.0
- GPU programming in Julia

Head of Scientific Computing at Cervest, working on Climate Intelligence solutions which quantify climate risk on a per-asset level, globally.

PhD in Physics from RMIT University in Melbourne, Australia; focusing on defects in the Josephson junctions of superconducting phase-qubits. Followed up by a postdoctoral position at Chalmers University in Gothenburg, Sweden investigating high energy laser-plasma interactions and fusion energy. More recently a researcher at the Stockholm Resilience Centre, with research areas concerning Planetary Boundaries, global climate-economy models, social ecological systems and other Earth system sciences.

- Agents.jl and the next chapter in agent based modelling

Timothy E. Holy is the Alan A. and Edith L. Wolff Professor of Neuroscience and Biomedical Engineering at Washington University in St. Louis. His lab combines technological innovation with analysis of the rules governing neuronal function and computation. His work on Julia includes contributions to the type system, the array and broadcasting infrastructure, the standard library, and developer tools like the profiler, debugger, Revise, and many others.

- Package latency and what developers can do to reduce it
- Package development: improving engineering quality & latency

Tobias Knopp received his Diplom degree in computer science in 2007 and his PhD in 2010, both from the University of Lübeck with highest distinction. For his PhD on the tomographic imaging method Magnetic Particle Imaging (MPI) he was awarded with the Klee award from the DGBMT (VDE) in 2011. From 2010 until 2011 he led the MAPIT project at the University of Lübeck and published the first scientific book on MPI. In 2011 he joined Bruker Biospin to work on the first commercially available MPI system. From 2012 until 2014 he worked at Thorlabs in the field of Optical Coherence Tomography (OCT) as a software developer. Since 2014, Tobias Knopp is a professor for Biomedical Imaging at the University Medical Center Hamburg-Eppendorf and the Hamburg University of Technology in Hamburg, Germany. Beside his work as a researcher in the field of tomographic imaging method Tobias Knopp is an open-source developer and part of the Julia community since 2012.

- Tomographic Image Reconstruction with Julia

Toby Driscoll is a Professor of Mathematical Sciences at the University of Delaware and founding director of the Center for Applications for Mathematics in Medicine. His research is in scientific computing, numerical methods for differential equations, modeling, and biomedical applications. He is the author of the Schwarz-Christoffel Toolbox for MATLAB and a leading contributor to the Chebfun software project. He is author or co-author of four books and is working on a Julia version of the textbook *Fundamentals of Numerical Computation*.

- Detection of tear film breakup using Julia

Tomas Pevny has graduated from Faculty of Nuclear sciences and Physical Engineering, CTU, Prague, in 2003. From 2004-2008, he was pursuing Ph.D. at Binghamton University, SUNY, USA specializing on Steganalysis. In 2008-2009 he spent a wonderful post-doc year in Grenoble. Since 2009, he is with Faculty of electrical engineering, CTU, at Prague. From 2013-2019, he was also consulting scientist at Cisco and from 2019 he is consulting scientist at Avast. His specialization is machine learning in security domains. He is an active user of Julia since 2015.

- Hierarchical Multiple Instance Learning

Ph.D. candidate at the Stanford Intelligent Systems Laboratory, Stanford (USA).

- Set Propagation Methods in Julia: Techniques and Applications

Tom Kwong is an experienced software engineer with over 28 years of industry programming experience. He has spent the majority of his career in the financial services industry. His expertise includes software architecture, design and development. In 2017, he discovered the Julia language and started working on several open-source projects such as SASLib.jl, BinaryTraits.jl and ContextTracking.jl. He has an MS Computer Science degree from University of California, Santa Barbara. He currently works at Facebook.

- HoJBot: a community-driven Discord bot

Tristan Carion is a mechanical engineer from UCL (Université Catholique de Louvain-la-Neuve) in Belgium. After graduating in 2016, he spent a few years working for the industry. He also spent some time traveling the world. He went back to the academic world in 2020 where he joined the Royal Military Academy of Belgium (RMA) as a researcher. He is working for a joint project of RMA, ECMWF and RMI (Royal Meteorological Institute of Belgium), which consists of implementing atmospheric dispersion models and response models on the ECMWF Weather Cloud and use the ensemble forecasts from ECMWF to produce ensemble dispersion modeling.

- Web application for atmospheric dispersion modeling.

I am a senior research software developer at University College London. My background is in developing plasma physics simulations for supercomputers. I'm interested in a lot of things, often broadly related to physics, energy and computing.

website

github

linkedin

- High Performance Tsunami Forecasting

Vaibhav is involved in building analysis tooling in the SciML ecosystem in Julia and one of the developers of Pumas (https://pumas.ai).

- Global Sensitivity Analysis for SciML models in Julia

- Calculating a million stationary points in a second on the GPU

PhD Student at MIT

- GPU programming in Julia BoF
- Julia in High-Performance Computing
- Scaling of Oceananigans.jl on multi GPU and CPU systems
- GPU programming in Julia
- Enzyme.jl -- Reverse mode differentiation on LLVM IR for Julia

Valerio is a student in Physics (Bachelor) at the University of Turin. He is interested in electronics, embedded systems, computing and signal processing as tools for investigating physics, such as the technology of the detectors employed in high energy physics.

- Physics-Informed ML Simulator for Wildfire Propagation

My expertise is in applied mathematics, computer science and engineering. My research is in the general area of data analytics, model diagnostics and machine learning. I am the inventor and lead developer of a series of novel theoretical methods and computational related to machine learning, data analytics, model diagnostics, and data inference tools. I am also a co-inventor of LANL-patented machine-leaning methodology. Over the years, I have been the principal investigator of several projects for machine learning, model development, model analyses, uncertainty quantification and decision support

- GeoThermalCloud: Fusion of Big Data and Multi-Physics Models
- SmartTensors: Unsupervised Machine Learning
- ML4Geo: Machine Learning for Geosciences

Developer of Ahorn and similar tools. Using Julia professionally since 2017.

- Julia and deploying complex graphical applications for laypeople

- Julia Developer Survey Results

I am a postdoc researcher in the mechanical engineering department at the Massachusetts Institute of Technology. I develop interpretable machine learning for modeling dynamics in thermal fluids and biomedical applications.

- Arrhenius.jl: A Differentiable Combustion Simulation Package

Recent graduate from the University of Kentucky in Computer Science and Mathematics. Passionate about graphs, machine learning, and logic programming.

- SuiteSparseGraphBLAS.jl

PhD Candidate @ MIT

- Enzyme.jl -- Reverse mode differentiation on LLVM IR for Julia

I am a PhD student at the University of Victoria and Canada's National Research Council working on astronomy instrumentation and the science of exoplanet direct imaging.

- Soft Realtime Control of an Exoplanet Imaging Instrument

I'm a PhD student in the Machine Learning group in Cambridge.

I primarily work on Gaussian processes -- how to scale them to large data sets, how to use them in climate science, and how best to write software that implements them.

- ParameterHandling.jl

PhD student at Johns Hopkins University, studying computational linguistics.

- Yawipa: a comprehensive and extensible Wiktionary parser

Full Professor in Operations Research and Computer Science, Université de Nantes (France).

- vOptSolver: an ecosystem for multi-objective linear optimization

Xuan (Sh-YEN, IPA: ɕɥɛn) is a PhD student at MIT in the Computational Cognitive Science and Probabilistic Computing research groups. Their current research focuses on inferring the hidden structure of human motivations by modeling agents as probabilistic programs, in the hope of aligning AI with the higher-order goals, values, and principles that humans strive (in part) to live by.

- Julog.jl: Prolog-like Logic Programming in Julia
- Improving Gender Diversity in the Julia Community
- Discussing Gender Diversity in the Julia Community
- Genify.jl: Transforming Julia into Gen for Bayesian inference

Associate Professor Yoni Nazarathy from the University of Queensland Australia, specializes in data science, probability and statistics. His specific research interests include scheduling, control, queueing theory, and machine learning. He has been at The University of Queensland for nearly a decade, teaching courses in the Masters of Data Science program and working on research. Prior to his previous academic positions in Melbourne and the Netherlands, he worked in the aerospace industry in Israel. In recent years, he has also been heavily involved with primary and secondary mathematics education and is the co-founder of an EdTech mathematics organization called One on Epsilon. He is also the co-author of a data science book, "Statistics with Julia: Fundamentals for Data Science, Machine Learning and Artificial Intelligence". Recently his research has also focused on epidemics and he leads the Safe Blues program dealing with finding efficient and ethical methods to track social mobility with a goal of prediction and control of epidemics.

- Statistics with Julia from the ground up

- B.S. in Mathematics and Computer Science, Pohang University of Science and Technology, 2007
- M.S. in Computer Science, Pohang University of Science and Technology, 2009
- Ph.D. in Computer Science, University of Wisconsin-Madison, 2017
- Postdoctoral Appointee, Argonne National Laboratory, 2018-Current

- ExaTron.jl: a scalable GPU-MPI-based batch solver for small NLPs

Ph.D. Senior Scientist, Japan Atomic Enegy Agency

- LatticeQCD.jl: Simulation of quantum gauge fields

Assistant Professor of Aerospace Engineering at the University of Colorado

- POMDPs.jl and Interactive Assignments in Julia

- Julia in VS Code - What's New

Zenna Tavares is a postdoctoral researcher at MIT under the supervision of Armando Solar Lezama. His interests are in probabilistic and causal inference, programming languages, and human-inspired artificial intelligence.

- Running Programs Forwards, Backwards, and Everything In Between

PhD student @ TU-Darmstadt

- hPF-MD.jl: Hybrid Particle-Field Molecular-Dynamics Simulation

- Modeling Marine Ecosystems At Multiple Scales Using Julia

Zoe McCarthy is a research engineer with a background in robotics, deep learning, reinforcement learning, and virtual reality. She is currently working at the MIT Julia Lab to make extensions and maintenance in the SciML ecosystem.

- Easy and Customizable PINN PDE Solving with NeuralPDE.jl