JuliaCon 2022 (Times are UTC)

Adrian Hill

Adrian Hill is a PhD student in the Machine Learning Group at TU Berlin.

  • ExplainableAI.jl: Interpreting neural networks in Julia
  • Dithering in Julia with DitherPunk.jl
Adrian Salceanu

Computer Scientists and software developer with over 20 years of experience creating full stack web and data centric applications. Creator of Genie, the highly productive Julia web application. Julia open source contributor since 2017. Author of "Julia Programming Projects" (Packt, 2018) and co-author "Julia Programming Complete Reference Guide" (Packt, 2019).

  • Interactive Julia data dashboards with Genie
Agustin Covarrubias

Estudiante de ingeniería en UC | Chile que hace un poco de todo, nada especialmente bien. Trabajo como Jefe de Plataformas Digitales en la Fundación América Transparente.

  • Juliacon Experiences
Agustín Covarrubias

I'm a student, open sourcerer and engineering student studying at UC | Chile.

I currently work as the Digital Platforms Lead at the América Transparente Foundation, using Julia to fight corruption.

  • BoF - JuliaLang en Español
Aidan Gleich

Sr. Research Analyst at NYFRB

  • Bayesian Estimation of Macroeconomic Models in Julia
Ajay Shah

Ajay Shah studied at IIT, Bombay and USC, Los Angeles. He has held positions at Centre for Monitoring Indian Economy (CMIE), Indira Gandhi Institute for Development Research (IGIDR), Department of Economic Affairs at the Ministry of Finance and National Institute for Public Finance and Policy (NIPFP). He is now part of xKDR Forum and Jindal Global University. His research is at the intersection of economics, law and public administration. His second book, co-authored with Vijay Kelkar, "In service of the republic: The art and science of economic policy", featured in Bloomberg's global "2020 Best Books on Business and Leadership". His work can be accessed on his home page (http://www.mayin.org/ajayshah).

  • Statistics symposium
Albert de Montserrat
  • GPU4GEO - Frontier GPU multi-physics solvers in Julia


  • HPC sparse linear algebra in Julia with PartitionedArrays.jl
Alessio Quaresima

Ph.D. in Cognitive Computational Neuroscience at the Max Planck Institute for Psycholinguistics.

Interested in dendrites, spikes, and sequences.

  • Simulating neural physiology & networks in Julia
Alexandre A. Renchon

Alexandre A. Renchon, currently postdoctoral appointee at Argonne National Laboratory, has a PhD in Terrestrial Ecology (2019, Western Syndey University), and Master degree in Bioengineering, Environmental Sciences and Technology (2013, Liege University). Alexandre is a multidisciplinary scientists with experience as an empiricist, modeler, and programmer. His interests are to understand how climate change will impact terrestrial ecosystems.

  • CUPofTEA, versioned analysis and visualization of land science
Alex Jones

From a background in electronic engineering, radar and electromagnetics to working developing PDE tooling in Julia.

Languages - English, German

  • Automated PDE Solving in Julia with MethodOfLines.jl
Ander Murua
  • SIMD-vectorized implementation of high order IRK integrators
Andrea Vigliotti

Researcher at the Italian Aerospace Research Center. My interests are in solid mechanics at large, both numerical and experimental.

  • Automatic Differentiation for Solid Mechanics in Julia
Andre Macleod

My name is Andre Macleod, 25, born in Sweden, raised in Italy, moved to New Zealand as I am half-kiwi. Passionate in mathematics, I recently completed a Masters degree in Applied Data Science, and have been working on various data science projects, including some in Julia, which I would be excited to share at JuliaCon if given the chance.

  • Using SciML to predict the time evolution of a complex network.
Andrew Winters

I am an Assistant Professor in the Department of Mathematics, Division of Applied Mathematics at Linköping University in Linköping, Sweden.

  • From Mesh Generation to Adaptive Simulation: A Journey in Julia
Anika Luo

I am a Biochemistry major and Music minor at Wellesley College, and I plan to pursue a Ph.D. in Biomedical Sciences. My career goal is to conduct research in biomedical science and advance the field of pharmaceutical medicine. As an undergraduate researcher in the Klepac-Ceraj Lab, I have worked on various engineering and computational projects with Dr. Kevin Bonham in which I have built tools to study microbial communities and to streamline analysis of metagenomic data. My current project investigates a method of using gut microbes to restore normal function in neurotransmitter deficient Caenorhabditis elegans, which may have important therapeutic implications for neurological conditions.

  • Microbiome.jl & BiobakeryUtils.jl for analyzing metagenomic data
Annelle Kayisire Abatoni

I am a Biology and Media Arts and Sciences double major, and I am particularly interested in the intersection of computational design and biological concepts. I am currently working on finding out and creatively exhibiting the microbial composition of Wellesley’s greenhouse, the Global Flora and exploring their different functions. In the past, I’ve worked on developing a software package that manipulates and analyzes microbial community data. After college, I hope to keep working with computational modeling tools to better understand biological systems. Outside of lab and school, I enjoy playing tennis and spending time with my friends.

  • Microbiome.jl & BiobakeryUtils.jl for analyzing metagenomic data
Anthony Blaom

Anthony Blaom Anthony Blaom is a mathematician, publishing in areas of pure mathematics, and a scientific computing consultant. He is a co-creator and lead contributor for MLJ, an open-source machine learning platform written in Julia.

Dr. Blaom was initially trained as a mechanical engineer at the University of Melbourne in 1991. After completing a MSc in Aeronautics and a PhD in Mathematics at Caltech in 1998, he joined the University of Auckland as a Lecturer. For a while he switched to adjunct teaching, focusing on his young children, whom he homeschooled while living on the small island of Waiheke.

Dr. Blaom is currently a Senior Research Fellow in the Department of Computer Science, University of Auckland.

  • Getting started with Julia and Machine Learning
Argel Ramírez Reyes
  • BoF - JuliaLang en Español
Arturo Erdely

Profesor de tiempo completo en la Universidad Nacional Autónoma de México (UNAM), miembro nivel 1 del Sistema Nacional de Investigadores (CONACYT - México), Actuario y Doctor en Ciencias Matemáticas (UNAM).

  • Juliacon Experiences
Ashwani Rathee


  • Working with Firebase in Julia
Avik Pal
  • Lux.jl: Explicit Parameterization of Neural Networks in Julia
Bart Janssens

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 stabilized finite element methods, and he recently started a new study on the topic where for the first time the main focus will be on using Julia and Gridap rather than the legacy C++ code.

  • Automated Finite Elements: a comparison between Julia and C++
Ben Arthur

Principal Software Engineer in Scientific Computing at Howard Hughes Medical Institute's Janelia Research Campus

  • Training Spiking Neural Networks in pure Julia
Benoît Legat

Benoît Legat is a postdoc at MIT with Prof. Pablo Parrilo in the Laboratory for Information and Decision Systems (LIDS).

  • Multivariate polynomials in Julia
  • Complex number support in JuMP
Bernardo Freitas Paulo da Costa

Professor of Mathematics at UFRJ, Brazil

  • Risk Budgeting Portfolios from simulations
Bogumił Kamiński

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

For development I mostly use Julia language.

I am one of the maintainers of DataFrames.jl.

  • A Complete Guide to Efficient Transformations of data frames
Boris Kaus

Computational geodynamicist at the University of Mainz, Germany

  • GPU4GEO - Frontier GPU multi-physics solvers in Julia
  • Differentiable Earth system models in Julia
Bradley Carman

Brad Carman is a Mechanical Engineer at Instron specializing in System Modeling and Thermal Fluids with focus on model and software development for the Crash Simulation and Structural Durability products.

  • Modeling a Crash Simulation System with ModelingToolkit.jl
Cailin Winston
  • Large-Scale Machine Learning Inference with BanyanONNXRunTime.jl
  • Large-Scale Tabular Data Analytics with BanyanDataFrames.jl
Caleb Winston

I'm Caleb. I'm currently studying Computer Science at the University of Washington and will be doing research at Stanford next year. My research interests are quite broad and I have published work in areas including both brain-computer interfaces and wet lab automation and I would be happy to chat about these things. I'm also currently working on https://BanyanComputing.com. Outside of CS, I love composing music and playing the alto sax in an ensemble group with my siblings.

  • Large-Scale Machine Learning Inference with BanyanONNXRunTime.jl
  • Large-Scale Tabular Data Analytics with BanyanDataFrames.jl
Carleton Coffrin

Carleton Coffrin is a staff scientist in Los Alamos National Laboratory’s Advanced Network Science Initiative. His research interests focus on how optimization methods can be used to solve applications in infrastructure networks. His background spans many forms of optimization including mathematical programing, constraint programming, and local search. Recently Carleton has been exploring the potential of novel computing architectures such as, quantum computers, neuromorphic processors and memristors to solve optimization applications.

  • Benchmarking Nonlinear Optimization with AC Optimal Power Flow
Carl Julius Martensen

Julius is currently a PhD candidate at the Otto-von-Guericke University in Magdeburg and an Intern at Pumas-AI. His research evolves around data-driven system identification using scientific machine learning.

  • How to recover models from data using DataDrivenDiffEq.jl
Carsten Bauer

Theoretical Physicist - Scientific HPC Advisor - National High Performance Computing (NHR) - Paderborn Center for Parallel Computing (PC²)

  • Julia for High-Performance Computing
  • Monitoring Performance on a Hardware Level With LIKWID.jl
  • The JuliaCon Proceedings
Charlie Kawczynski

Charlie earned his Ph.D. in mechanical engineering at UCLA, where he studied and developed software to simulate computational liquid metal magnetohydrodynamic flows for magnetic confined fusion energy reactors. Since then, he's been developing a climate model, in Julia, from the ground up at Caltech in the CliMA project. For more details, see https://clima.caltech.edu/.

  • Juliacon Experiences
Chelsea Sidrane
  • Verifying Inverse Model Neural Networks Using JuMP
Chiel van Heerwaarden

I am an atmospheric scientist trying to understand the interactions between turbulence, clouds, radiation and the land surface with 3D simulation and field observations (see chiel.ghost.io). The main tool of our research lab is MicroHH, our in-house C++/CUDA 3D simulation code. Recently, I have ported the dynamical core of MicroHH to Julia to make the code more accessible to students, as C++ is often too complex to learn for a short project, and have a tool for future SciML projects.

  • Simulation of atmospheric turbulence with MicroHH.jl
Chris Coey

MIT PhD student graduating May 2022, starting postdoc at MIT Sloan.

  • Pajarito's MathOptInterface Makeover
Chris Elrod

Chris Elrod is a frequent commenter on the Julia Discourse, Slack, and Zulip, as well as a contributor to the ecosystem, known in particular for LoopVectorization.jl and JuliaSIMD.

  • Multivariate polynomials in Julia
  • Simple Chains: Fast CPU Neural Networks
Chris Foster

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 or as Chris Foster/c42f on the julialang Zulip, slack or discourse.

  • JuliaSyntax.jl: A new Julia compiler frontend in Julia
Chris Hill

Chris Hill is a computational scientist at MIT who has developed ocean and planetary models and modeling tools that are used by thousands of researchers yearly. He has been working with members of the Julia community from its earliest days.

  • Hands-on ocean modeling and ML with Oceananigans.jl
  • Differentiable Earth system models in Julia
Chris Rackauckas

Research Affiliate and Co-PI of the Julia Lab at the Massachusetts Institute of Technology
Director of Modeling and Simulation at Julia Computing and Creator / Lead Developer of JuliaSim
Director of Scientific Research at Pumas-AI and Creator / Lead Developer of Pumas
Lead Developer of the SciML Open Source Software Organization

Chris Rackauckas

Chris' research and software is focused on Scientific Machine Learning (SciML): the integration of domain models with artificial intelligence techniques like machine learning. By utilizing the structured scientific (differential equation) models together with the unstructured data-driven models of machine learning, our simulators can be accelerated, our science can better approximate the true systems, all while enjoying the robustness and explainability of mechanistic dynamical models.

Chris's recent work is focused on bringing personalized medicine to standard medical practice through the proliferation of software for scientific AI. Chris is at the cutting edge of mathematical methods for scientific simulation. He is the lead developer of the DifferentialEquations.jl solver suite along with over a hundred other Julia packages, earning him the inaugural Julia Community Prize, an outstanding paper award at the IEEE-HPEC conference on computational derivation for the efficient stochastic differential equation solvers, and front page features on many tech community sites. Chris' work on high performance differential equation solving is the engine accelerating many applications from the MIT-CalTech CLiMA climate modeling initiative to the SIAM Dynamical Systems award winning DynamicalSystems.jl toolbox (of which DifferentialEquations.jl was the runner-up). His work is credited for the 15,000x acceleration of NASA Launch Services simulations and recently demonstrated a 60x-570x acceleration over Modelica tools. For these achievements Chris received the United States Department of the Air Force Artificial Intelligence Accelerator Scientific Excellence Award.

Chris brought these enhanced numerical approaches to the domain of pharmaceutical modeling and simulation as the creator and lead developer of Pumas. Pumas is scientific AI in clinical practice. Pumas makes it possible to predict the optimal medication dosage for individuals, reducing the costs and potential complications associated with treatments. Pumas is being used by many major pharmasceuticals to predict personalized safe dosage regimens by incorporating realistic biological models (quantitative systems pharmacology) and deep learning into the traditional nonlinear mixed effects (NLME) modeling framework. 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 with Pfizer on GPU-accelerated quantitative systems pharmacology to accelerate preclinical analysis by 175x. Notably, Moderna adopted Pumas in 2020 to accelerate crucial clinical trials, noting "Pumas has emerged as our 'go-to' tool for most of our analyses in recent months". For these achievements, Chris received the Emerging Scientist award from ISoP, the highest early career award in pharmacometrics.

Chris started this work while completing his Masters and Ph.D. at the University of California, Irvine where he was awarded the Mathematical and Computational Biology institutional fellowship, the Graduate Dean's Fellowship, the National Science Foundation's Graduate Research Fellowship, the Ford Predoctural Fellowship, the NIH T32 Predoctural Training Grant, the Center for Complex Biological Systesms Opportunity Award, and the Data Science Initiative Summer Fellowship. His research with his advisor, Dr. Qing Nie, focused on the methods for simulating stochastic biological models and detailing how the randomness inherent in biological organisms can be controlled using stochastic analysis. Chris bridged the gap between theory and practice by having a "wet lab bench" in Dr. Thomas Schilling's lab, where these methodologies were tested on zebrafish. Fluorescence Light Microscopy (FLIM) measurements of retinoic acid in the zebrafish hindbrain showed that the predicted control proteins could attenuate inherent biological randomness. The result was a verified mathematical theory for controlling the randomness in biological signaling. Chris received the Kovalevsky Outstanding Ph.D. Thesis Award from the Department of Mathematics upon graduation and was showcased in an interview "Interdisciplinary Case Study: How Mathematicians and Biologists Found Order in Cellular Noise" in Cell Press's iScience.

As an undergraduate at Oberlin College, Chris was awarded the NSF S-STEM scholarship and the Margaret C. Etter Student Lecturer Award by the American Crystallographic Association, an award usually given for PhD dissertations, for his work on 3+1 dimensional incommensurate crystal structure identification of H-acid. This award was given for Service Crystallography for its potential impact on industrial dye manufacturing.

  • LinearSolve.jl: because A\b is not good enough
  • How to debug Julia simulation codes (ODEs, optimization, etc.!)
Christine Flood

Christine Flood has worked in academia, industry, and government. She's worked on commercially successful programming language implementations like java and academically interesting ones like Fortress, Lisp, and Id She's now focused on improving memory management performance in Julia.

  • Garbage Collection in Julia.
Christopher J Geoga

PhD student at Rutgers University, Dept. of Statistics

  • `BesselK.jl`: a fast differentiable implementation of `besselk`
Christopher Kim
  • Training Spiking Neural Networks in pure Julia
Curtis Vogt

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.

  • Production Data Engineering in Julia
Daniel Molina

I am tenure in Computer Science at the University of Granada, Spain. I strongly support free software in my life and use it daily in my teaching. I learned Julia more than a year ago, mainly for research, in Machine Learning and Optimization, but also for teaching.

  • Teaching with Julia (my experience)
Dave Kleinschmidt

Research scientist at Beacon Biosignals, recovering academic.

  • RegressionFormulae.jl: familiar `@formula` syntax for regression
David Anthoff

David Anthoff is an environmental economist who studies climate change and environmental policy. His research has appeared in Nature, Science, the American Economic Review, Nature Climate Change, the Journal of the Association of Environmental and Resource Economists and other academic journals. He is an associate professor in the Energy and Resources Group at the University of California, Berkeley.

  • Juliaup - The Julia installer and version multiplexer
  • Julia in VS Code - What's New
David Gleich

David Gleich is an associate professor of computer science at Purdue University.

  • Writing a GenericArpack library in Julia.
David Gomez-Cabeza

I am a Bioengineering PhD student at the University of Edinburgh working on optimal experimental design for automated model calibration and selection, both computationally and experimentaly. Coming from a pure experimental background (Microbiology), I discovered how powerfull modeling can be in not just predicting, but designing new biological systems, hence my transition to a hybrid type of work. I discovered Julia a couple of years ago, looking for faster environments to do my computational research (mostly Bayesian based), and now I completely shifted all my work to it!

  • An introduction to BOMBs.jl.
Dean Markwick

I've been using Julia user since 2015 and maintain a number of packages from HawkesProcesses.jl to a number of data API wrappers.

In my day job I’m currently an electronic trading quant working on both principal and algo execution. I build models, analyse data and construct algorithms to try and get the best prices in the market with the lowest impact.

Outside of my day job I enjoy writing about technology and sports on my blog.

  • Using Hawkes Processes in Julia: Finance and More!
  • Optimising Fantasy Football with JuMP
Deleted User

Albert recently received his PhD from MIT AeroAstro and is now a postdoc in the Julia Lab within MIT CSAIL. His research is focused on improving airborne magnetic anomaly navigation using machine learning-based aeromagnetic compensation approaches (and the Julia programming language). Albert received his B.S. degree in mechanical engineering from UW–Madison in 2015 and S.M. degree in aeronautics and astronautics from MIT in 2018. Albert previously worked on electric aircraft design as an NSF graduate research fellow, and he earned his private pilot license in 2020.

  • MagNav.jl: airborne Magnetic anomaly Navigation
Dhairya Gandhi

I am a data scientist at Julia Computing, and also the core developer in the FluxML ecosystem.

  • Scaling up Training of Any Flux.jl Model Made Easy
Dilum Aluthge
  • Build, Test, Sleep, Repeat: Modernizing Julia's CI pipeline
Diogo Netto

Masters student at MIT Julia Lab.

  • Parallelizing Julia’s Garbage Collector
Dmitry Bagaev

My research interests lie in the fields of computers science, machine learning and probabilistic programming. Currently I am a PhD candidate in the SPS group of Electrical Engineering department in Eindhoven University of Technology. I’m working on a high-performant implementation of message passing-based Bayesian inference package in the Julia programming language. My research project focuses on Signal Processing and Active inference applications, but is also aimed to expand the scope of possible applications for message passing in general.

  • GraphPPL.jl: a package for specification of probabilistic models
Dominique Orban

I am computational mathematician. My scientific interests span computational optimization, numerical analysis, numerical linear algebra, scientific computing, and modeling environments. I have a keen interest in the interplay between computational science and programming languages.

My research focuses on the design, convergence analysis, numerical properties, practical implementation, and testing of algorithms for continuous optimization and their linear algebra kernels. I am equally interested in applying algorithms that I design to problems that arise in engineering and science.

My research activities thus comprise tightly interconnected theoretical analyses of computational methods and high-quality implementations to aid in the modeling and solution of practical problems.

  • The JuliaSmoothOptimizers (JSO) Organization
Dr. Vikas Negi

I currently work as a Metrology Design Engineer at ASML in the Netherlands. I love coding, and my language of choice is Julia. Besides that, I occasionally tinker with my Raspberry Pi. My other hobbies include listening to podcasts (big fan of Lex Fridman) during long walks, running and watching new shows/documentaries on Netflix. I am also a proud owner of a custom built PC and a Xbox One S. Whenever time permits, I dabble with Web 3.0 and blockchain based technologies. Curious to know more? Feel free to visit my web3 powered site.

  • Juliacon Experiences
Eduardo M. G. Vila

PhD Student at Imperial College London

  • Progradio.jl - Projected Gradient Optimization
Eirik Brandsaas

Economist at the Federal Reserve Board of Governors. Primary research area is computational macroeconomics, with a focus on household finance, housing, and family economics.

  • Du Bois Data Visualizations: A Julia Recipe
Eirik Brandsaas & Kyra Sadovi

Eirik Brandsaas is an economist at the Board of Governors of the Federal Reserve System. Kyra Sadovi is a research assistant at the Board of Governors.

  • Du Bois Data Visualizations: A Julia Recipe
Elliot Saba

Elliot Saba is a senior research engineer at Julia Computing, where he design next-generation tools for the Julia programming language. He received his Ph.D. from the University of Washington in Electrical Engineering in 2018, specializing in Digital Signal Processing and Machine Learning. Elliot received the Julia community prize at JuliaCon 2018, recognizing his open source contributions to the Julia project. When he is not building fundamental infrastructure for the Julia language, he enjoys dreaming up ever more complex strategies to automate watering his houseplants.

  • Build, Test, Sleep, Repeat: Modernizing Julia's CI pipeline
Eric B. Ford

Eric Ford is a Professor of Astronomy & Astrophysics at the Pennsylvania State University, where he is active in its Institute for Computational & Data Sciences, Center for Astrostatistics, and Center for Exoplanets & Habitable Worlds. Ford’s research focuses on detecting and characterizing planetary systems around other stars. This often involves using Julia to apply modern Bayesian methods to improve the interpretation of exoplanet observations. Ford has taught a graduate-level class on High-Performance Computing for Astrophysics using Julia since 2014.

  • Julia in Astronomy & Astrophysics Research
  • RVSpectML: Precision Velocities from Spectroscopic Time Series
Erich Focht

Erich has worked on optimizing CFD and structural mechanics algorithms for parallel vector supercomputers, did Linux kernel development and research in distributed systems software and parallel file systems. Currently he leads a research and development group at NEC HPC Europe, his work topics cover system software and compilers for heterogeneous computing with NEC's SX-Aurora Vector Engine, augmenting HPC simulations with AI and integrating cloud technologies into HPC clusters.

  • Julia to the NEC SX-Aurora Tsubasa Vector Engine
Erin LeDell

Dr. Erin LeDell is the Chief Machine Learning Scientist at H2O.ai, where she develops the open source, distributed machine learning platform, H2O, and is the founder of the H2O AutoML project. She has a Ph.D. in Biostatistics with a Designated Emphasis in Computational Science and Engineering from University of California, Berkeley. Her research focuses on automatic machine learning, ensemble machine learning and statistical computing. She also holds a B.S. and M.A. in Mathematics.

Before joining H2O.ai, she was the Principal Data Scientist at Wise.io and Marvin Mobile Security, and the founder of DataScientific, Inc. She is also founder of the Women in Machine Learning and Data Science (WiMLDS) organization (wimlds.org) and co-founder of R-Ladies Global (rladies.org).

  • Keynote- Erin LeDell
Fábio Rodrigues Sodré

Analista programador web, gamer, apaixonado por leitura e futebol
Gestor da Unidade de Gestão da Informação | Secretaria Adjunta da Tecnologia da Informação do Maranhão - SEATI / MA - Brasil

  • Juliacon Experiences
Felix Wechsler

Felix Wechsler is a PhD student at the Leibniz Institute of Photonic Technology and the Friedrich Schiller University of Jena. Before that, Felix obtained Bachelor degrees in physics and informatics where he worked on Light Field Microscopy and Schlieren Imaging.
In his master thesis, he developed a novel kaleidoscopic microscope, the Kaleidomicroscope.
His recent work is implemented in Julia Lang and he is maintainer of several microscopy related packages written in Julia Lang.

  • PointSpreadFunctions.jl - optical point spread functions
  • PtyLab.jl - Ptychography Reconstruction
Flemming Holtorf

Flemming is a PhD student at MIT working on computational techniques for uncertainty quantification and optimization under uncertainty.

  • Dynamical Low Rank Approximation in Julia
  • Stochastic Optimal Control with MarkovBounds.jl
Frames Catherine White

Frames White is the lead of the research software engineering group at Invenia.
She is also the lead of the ChainRules project, and a major developer of many other Julia projects.

  • Tricks.jl: abusing backedges for fun and profit
Francesco Fucci

Lead software-engineer @ ASML, passionate about algorithm design, software engineering and programming languages. Besides, I love to make electronic music and experiment with sound-design.

  • Towards Using Julia for Real-Time applications in ASML
Francesc Verdugo

Assistant Professor at the Computer Science Department at VU Amsterdam.

  • HPC sparse linear algebra in Julia with PartitionedArrays.jl
Francisco Heron de Carvalho Junior

DSc in Computer Science from the Federal University of Pernambuco, Recife, Brazil

Associate Professor, Department of Computing, Federal University of Ceará, Fortaleza, Brazil

Visiting researcher at Northeastern University, Boston, USA.

Main areas of interest: programming languages and high performance computing

Most recent project: http://www.hpcshelf.org

Curriculum: http://lattes.cnpq.br/4164818158160492

LinkedIn: https://www.linkedin.com/in/francisco-heron-de-carvalho-junior-6bb58949/

  • Platform-aware programming in Julia
Francis Poulin

Professor of Applied Mathematics at the University of Waterloo.

  • Hands-on ocean modeling and ML with Oceananigans.jl
Francis Smart

Data Scientist at Censeo Consulting currently supporting GSA.

  • BlockDates: A Context-Aware Fuzzy Date Matching Solution
François Pacaud

Postdoc at Argonne National Labt

  • Streamlining nonlinear programming on GPUs
Fredrik Bagge Carlson

I received my MSc and PhD 2019 from the Dept. Automatic Control in Lund, Sweden, working within the fields of control, machine learning and robotics. I have since spent a year with the Acoustic Research Laboratory at NUS and subsequently made the transition to industry, working with dynamic modeling, control and programming-language design in a robotics context. I am now working with Julia Computing on software tools for acausal modeling, simulation, optimization and control in the Julia programming language.

  • Control-systems analysis and design with JuliaControl
Gabriel Gobeil

I am a research associate at Polytechnique Montréal in the group of Jonathan Jalbert.

  • Extreme Value Analysis in Julia with Extremes.jl
Garrek Stemo

PhD candidate in physical chemistry and molecular science at the Nara Institute of Science and Technology.

  • Juliacon Experiences
Gaspard Kemlin

I am 3rd year PhD student at CERMICS, ENPC and Inria Paris, team MATHERIALS. I work on numerical analysis of PDEs for quantum chemistry, and in particular electronic structure calculations. Part of my work uses the Density Functional ToolKit (DFTK.jl), a Julia package developed by Michael F. Herbst and Antoine Levitt.

  • Automatic Differentiation for Quantum Electron Structure
Geoffroy Leconte

Phd student at Polytechnique Montréal supervised by Dominique Orban. I am developing RipQP.jl, a package for solving convex quadratic problems and I also contribute to the organization JuliaSmoothOptimizers.

  • A multi-precision algorithm for convex quadratic optimization
George Gkountouras

George Gkountouras (MSc ECE) is the founder of Arthurian Audio, an AI startup operating in the audio software industry. Additionally, he has invented and published a quantum sequencer for modular environments. During his academic career, George regularly taught DSP to undergraduate students. He's worked on compilers, circuit simulators and audio plug-ins. He is also interested in embedded systems.

  • Exploring audio circuits with ModelingToolkit.jl
Giacomo Torlai

I am a research scientists at the Amazon Web Services Center for Quantum Computing, Pasadena (California). Previously I was a research fellow at the Center for Computational Quantum Physics of the Flatiron Institute (New York), and earned a PhD in physics at the University of Waterloo and the Perimeter Institute for Theoretical Physics, Waterloo (Canada). I am the lead developer of PastaQ.jl.

  • Quantum computing with ITensor and PastaQ
Giovanni Pagliarini

PhD Student in Mathematics, Logic & Computer Science @ University of Ferrara & Parma, Italy.

Developing, studying and testing new symbolic learning methods.

Checkout ModalDecisionTrees.jl at: https://github.com/giopaglia/ModalDecisionTrees.jl

#AI, #Interpretability, #ModalDecisionTrees!

  • ModalDecisionTrees: Decision Trees, meet Modal Logics
Giulio Benedetti

Bioengineering student at Rhine-Waal University, Germany, and former research trainee at Turku University, Finland, where he contributed to FdeSolver.jl and MicrobiomeAnalysis.jl under the supervision of the Turku Data Science Group. Interested in bioinformatics and data science.

  • A Data Integration Framework for Microbiome Research
Graham Stark

Graham teaches economics at the Open University, UK and runs Virtual Worlds Research (http://virtual-worlds.scot) where he builds microsimulation economic models. Previously he worked for 20 years at the Institute for Fiscal Studies (www.ifs.org.uk). He lives in Glasgow, Scotland.

  • A Tax-Benefit model for Scotland in Julia
Gregory Wagner

Physical oceanographer working on approximate models for ocean turbulence

  • Hands-on ocean modeling and ML with Oceananigans.jl
Guilherme Bodin

Guilherme is an engineer at PSR and an avid contributor to packages in the JuMP ecosystem since the beginning of his master's degree.

  • Recent developments in ParametricOptInterface.jl
Guilherme Fahur Bottino

Computational Chemist (Ph.D. Candidate) @ University of Campinas, Brazil; incoming Postdoc Researcher @ Wellesley College, USA. Chemistry teacher, Julia developer, Scientific Computing and Machine Learning enthusiast, casual MMORPG gamer, bartender and home cook. Programming makes Science even cooler! (He/Him/His)

  • TintiNet.jl: a language model for protein 1D property estimation
Guilherme Gomes Haetinger

I am a Computer Science MSc. 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. I'm currently working at Julia Computing developing visualizations to help ML workflows.

  • Visualization Dashboards with Pluto!
Guillaume Baudart

Researcher at Inria Paris and École normale supérieure.
Previously research staff member at the IBM T.J. Watson research center.

  • OnlineSampling : online inference on reactive models
Guillaume Dalle

PhD student at École des Ponts (France), working on machine learning and operations research with applications to railway planning.

  • InferOpt.jl: combinatorial optimization in ML pipelines
  • ImplicitDifferentiation.jl: differentiating implicit functions
Harsha Nagarajan

Harsha Nagarajan is currently a staff scientist in the “Applied Mathematics and Plasma Physics” group at Los Alamos National Laboratory (LANL). His research interests include development of efficient formulations and algorithms for modeling, design and control of complex physical systems.

  • QuantumCircuitOpt for Provably Optimal Quantum Circuit Design
Hector D. Perez
  • Generalized Disjunctive Programming via DisjunctiveProgramming
Helge Eichhorn

I am working on reimagining space exploration with Open Source at JuliaAstro, JuliaSpace, and OpenAstrodynamics.

Currently serving as Head of Product Innovation at Telespazio Germany.

  • Julia for Space Engineering
Helmut Hänsel

I am a data scientist for process development at Merck KGaA (Darmstadt, Germany). In this function I use Genie/Stipple in two major projects. This allows me to contribute to the Stipple packages from time to time.

  • Interactive Julia data dashboards with Genie
Hendrik Ranocha

I am interested in numerical analysis and scientific computing with applications in science and engineering. In particular, I like to analyze and develop numerical methods for differential equations, focusing on stability, mimetic properties, structure preservation, and efficiency. I started with the common mix of C, C++, Fortran, Python, Matlab, Mathematica etc. Nowadays, I am using Julia nearly exclusively for my work. Currently, I am an Assistant Professor in Applied Mathematics at the University of Hamburg. If you want to know more about me, please visit my website.

  • Julia for High-Performance Computing
Husain Attarwala

Husain Attarwala is a clinical pharmacologist, pharmacometrician and a researcher in drug development. Currently, he is serving as Head of Clinical Pharmacology and Pharmacometrics at Moderna. His research focus on developing predictive models to guide clinical dose decisions for mRNA vaccines and therapeutics. Previously, Husain was a Principal Scientist at Alnylam Pharmaceuticals where his research helped guide dose selection for various novel siRNA therapeutics, 5 of which have received global regulatory approvals. He has obtained PhD and MS degrees in Pharmaceutical Sciences and Drug Delivery Systems from Northeastern University, and a Bachelors in Pharmacy from Al-Ameen college of pharmacy.

  • Keynote - Husain Attarwala
Ifihanagbara Olusheye

Ifihan is a Python/Julia developer and Technical Writer. She has a passion for communities and new technologies.

  • Contributing to Open Source with Technical Writing.
Jacob Quinn
  • Production Data Engineering in Julia
Jacob Zelko

I am a graduate of Georgia Institute of Technology with a BS in biomedical engineering. I currently work at Georgia Tech Research Institute in the Health Emerging and Advanced Technologies division (HEAT-D) as a Health Data Analytics and Informatics Researcher as well as being a Contractor for the Centers for Disease Control.

  • Using Julia for Observational Health Research
Jakub Mitura

I am a student in my last year of MSc in Computer Science - Big Data Specialization (graduation June 2022 r.) also a physician in the last year of nuclear medicine residency working with various modalities of medical imaging. Additionally for the last 4 years I have been a lecturer in international programmes teaching subjects like Anatomy and Radiology in English . Simultaneously I am a junior research assistant in Medical University of Lublin and in the final steps of acquiring a PhD in Nuclear Medicine. I already passed all examinations, and have preliminary positive reviews, formally I will acquire PhD probably on 14.04.2022

  • GPU accelerated medical image segmentation framework
Jameson Nash

I work for Julia Computing on Julia compiler technology.

  • which(methods)
Janis Erdmanis

I own a PhD degree titled "Quantum effects of superconducting phase" at TU Delft. Since then, I have found my passion in programming and designing cryptosystems. I like to expand boundaries and build frames where complexity becomes manageable. May be excited about job opportunities using Julia as the main driver.

  • Zero knowledge proofs of shuffle with ShuffleProofs.jl
Jan Siml

I'm Head of Data and Product Insight at LexisNexis.

  • Optimize your marketing spend with Julia!
Jan Verschelde

Jan Verschelde obtained his PhD in Computer Science in 1996 at the Katholieke Universiteit Leuven. After postdoctoral studies at Michigan State University and the Mathematical Sciences Research Institute in Berkeley, he joined the Department of Mathematics, Statistics and Computer Science at the University of Illinois at Chicago, where he teaches courses in symbolic computing, numerical analysis, computational geometry, industrial math & computation, scientific software, and supercomputing. He is the main developer of PHCpack, a software package to solve polynomial systems by homotopy continuation.

  • PHCpack.jl: Solving polynomial systems via homotopy continuation
Jarrett Revels
  • Production Data Engineering in Julia
Jayesh K. Gupta

I am a Researcher at Microsoft Autonomous Systems where I work on improving simulations with data-driven methods.

  • PyCallChainRules.jl: Reusing differentiable Python code in Julia
Jean-Michel Campin

Working with Oceananigans.jl

  • Hands-on ocean modeling and ML with Oceananigans.jl
Jeffrey Sarnoff

Julia Innovator, author of DoubleFloats.jl, NamedTupleTools.jl, SaferIntegers.jl, RollingFunctions.jl, and others.

  • Dates with Nanoseconds
Jeffrey Sun

I am a graduate student in economics at Princeton University. I am interested in dynamic heterogeneous-agent spatial models and reinforcement learning techniques to solve them.

  • Automating Reinforcement Learning for Solving Economic Models
Jeffrey Vetter
  • Building Julia proxy mini apps for HPC system evaluation
  • Julia for High-Performance Computing
Jeremiah Lasquety-Reyes

Jeremiah Lasquety-Reyes is a digital market analyst based in Hamburg, Germany. He uses R and Python on a daily basis, but has recently started to turn his sights on Julia, especially for the purpose of agent-based modeling.

  • Juliacon Experiences
Jeremy Howard

Jeremy Howard is a data scientist, researcher, developer, educator, and entrepreneur. Jeremy is a founding researcher at fast.ai, a research institute dedicated to making deep learning more accessible, and is an honorary professor at the University of Queensland. Previously, Jeremy was a Distinguished Research Scientist at the University of San Francisco, where he was the founding chair of the Wicklow Artificial Intelligence in Medical Research Initiative, the founding CEO of Enlitic, President and Chief Scientist of Kaggle, and CEO of FastMail as well as Optimal Decisions Group.

  • Keynote - Jeremy Howard
Jesús-Adolfo Mejía-de-Dios

Jesús Mejía is a Ph.D. student from the Artificial Intelligence Research Institute at the University of Veracruz (IIIA-UV). He received a BSc degree in mathematics from the University of Veracruz and obtained a master’s degree with an honorific mention in Artificial Intelligence from CIIA-UV. His research interests include Numerical Analysis, Bilevel Optimization, and Intelligent Computing.

  • Metaheuristics.jl: Towards Any Optimization
J.J. Allaire

J.J. Allaire is the founder of RStudio and the creator of the RStudio IDE. J.J. is an author of several packages in the R Markdown publishing ecosystem including rmarkdown, flexdashboard, learnr, and distill. J.J. is now the technical lead of the Quarto project, which aims to apply the lessons learned from 10 years of R Markdown to create a new system that is fundamentally multi-language and multi-engine.

  • Reproducible Publications with Julia and Quarto
Joaquim Dias Garcia

Researcher and developer at PSR. Based in Brasil. Working with Power Systems, Stochastic Optimization, Bilevel Optimization, Reinforcement Learning. JuMP developer.

  • DiffOpt.jl differentiating your favorite optimization problems
Johannes Blaschke
  • Julia in HPC
  • Julia for High-Performance Computing
Johnny Chen

I'm a Ph.D. student in East China Normal University, I also maintain the JuliaImages ecosystem and the JuliaCN community. More details on GitHub @johnnychen94.

  • Build an extensible gallery of examples
Jonathan Doucette

PhD candidate studying MRI physics at the University of British Columbia.

  • Calling Julia from MATLAB using MATDaemon.jl
Jorge A. Pérez-Hernández

I'm a Software Engineer at Telespazio Germany GmbH. In 2021 I graduated from the Physics PhD from the National Autonomous University of Mexico, UNAM. I'm interested in astrodynamics, celestial mechanics, orbit determination, and Solar System dynamics.

  • Julia for Space Engineering
Joseba Makazaga
  • SIMD-vectorized implementation of high order IRK integrators
José Pereira

José M. S. Pereira is a Biochemistry PhD student at CICECO-University of Aveiro Institute of Materials since 2018. He finished his Master’s on Biotechnology in the University of Aveiro, where the focus of his thesis was on the subject of bioremediation of waste water sources by filtration with activated bio-carbons. As a product of his Master’s thesis, José Pereira developed http://carbgen.web.ua.pt/, a peer-reviewed online tool for the design of atomic carbon models. Starting his PhD, José Pereira shifted his focus for the computational design of peptides, while continuing to pursue scientific software development. He participated in the Board of European Students of Technology 2017 Winter Course, in Paris, France, was awarded a Fulbright scholarship for a 4-month student exchange at Rutgers University, New Jersey, USA, and won the TOP3 award at European Innovation Academy 2021 for his work on ProtoSyn (https://github.com/sergio-santos-group/ProtoSyn.jl), the developed software on the scope of his PhD thesis. He authored 2 peer-reviewed papers and participated in over 20 conferences.

  • ProtoSyn.jl: a package for molecular manipulation and simulation
Jose Storopoli

Associate Professor and Researcher of the Department of Computer Science at Universidade Nove de Julho - UNINOVE located in São Paulo - Brazil.
Lead on Education and Training at Pumas-AI.

Teaches undergraduate and graduate courses in Data Science, Statistics, Bayesian Statistics, Machine Learning and Deep Learning using Julia, R, Python, and Stan. Contributor to Julia, R and Stan ecosystems. Proficient in C/C++ and Rust.
Has published Julia, Rust, R, and Python packages in official repositories/registries.

Researches, publishes and advises PhD candidates on topics about Bayesian Statistical Modeling and Machine Learning applied to Decision Making.
Principal Investigator of LabCidades - Smart City Research Lab at UNINOVE.

Coauthor of Julia Data Science book.
Leads the development of education and training materials for Pumas users in Julia.
Member of the Stan Governing Body - SGB.
Member of the Turing.jl Developer Team.
Certified RStudio Tidyverse Instructor.

  • TuringGLM.jl: Bayesian Generalized Linear models using @formula
Jose Storopoli
  • Introduction to Julia
Josh Day

Dr. Josh Day (PhD Statistics, NC State) is a Senior Research Scientist at Julia Computing where he develops technical R&D software. He's motivated by unsolved problems and his research interests are on-line algorithms (OnlineStats.jl), numerical optimization, and data visualization. He maintains many Julia packages which can be viewed on Github.

  • State of JuliaGeo
Joshua Pulsipher

I am postdoc at Carnegie Mellon University specializing in infinite-dimensional optimization techniques.

  • Advances in Transformations and NLP Modeling for InfiniteOpt.jl
Julia Frank

Undergraduate physics student (starting an MSc Physics degree in May 2022) from Canada.
Blogging about Julia Language and physics.

  • Juliacon Experiences
Julia Gender Inclusive

An initiative to promote gender diversity and inclusion within the wider Julia community. We aim to do this through a combination of community building, targeted outreach, education, mentorship, and mutual support.

  • Discussing Gender Diversity in the Julia Community
Julia Müller

Kyla McConnell and Julia Müller are Ph.D. students at the University of Freiburg, where
they conduct quantitative psycholinguistic research and teach graduate-level statistics
and data skills. They co-organize two groups for gender inclusivity in programming: Julia
Gender Inclusive (@juliainclusive) and R-Ladies Freiburg (@RLadiesFreiburg).
Through these groups, they have fostered a passion for data science and statistical
education, particularly for underrepresented genders. You can find their many
workshops for beginners and more experienced programmers alike on the Julia
Programming Language and R-Ladies Global Youtube channels, and by following us on
Twitter (@McConnellKyla & @JuliaMuellerFr).

  • Building an inclusive (and fun!) Julia community
Julian Hall

I have been developing software for linear optimization since my time as a PhD student with Roger Fletcher in the late 1980's. A lecturer at the University of Edinburgh since 1990, my research has focused on serial and parallel computing techniques for implementing the simplex algorithm for linear programming. This has resulted in the development of HiGHS, the world's best open-source software for linear optimization.

  • JuMP and HiGHS: the best open-source linear optimization solvers
Julian P Samaroo

Research Software Engineer at MIT's JuliaLab.

I'm the maintainer of Dagger.jl, AMDGPU.jl, and BPFnative.jl, and am dedicated to making Julia's heterogeneous computing support powerful and productive.

  • Dagger.jl Development and Roadmap
Julius Krumbiegel

Julius is a psychologist-turned-programmer who enjoys transforming raw data into visualizations that are both aesthetically pleasing and easy to understand.

  • Interactive data visualizations with Makie.jl
Justin Mimbs

Justin Mimbs is a software engineer at ISEA TEK (Industrial & Systems Engineering Analysis Technologies) in Maitland, Florida.

  • Validating a tsunami model for coastal inundation
Kento Kawasaki

Researcher in natural language processing

  • Text Segmentation with Julia
Kevin Bonham

Senior research scientist at Wellesley College, studying the human microbiome and its effects on cognitive development.

  • Microbiome.jl & BiobakeryUtils.jl for analyzing metagenomic data
Kiran Shila

Kiran received the B.S. and M.S degrees in electrical engineering from the University of South Florida, Tampa, FL in 2018 and 2020, respectively. He is currently a Ph.D. student in the electrical engineering department at the California Institute of Technology (Caltech) in Pasadena with a research appointment in the department of astronomy. His current research interests include radio astronomy instrumentation, room-temperature and cryogenic low noise amplifiers, and radio astronomy software. In his free time, he plays the jazz vibraphone, bikes around LA, and contributes to open source software.

  • Finding Fast Radio Bursts, Faster
Kristopher Brown

Postdoctoral researcher at UF working with James Fairbanks.

  • Declarative data transformation via graph transformation
Krystian Guliński


  • DTables.jl - quickstart, current state and next steps!
Kyla McConnell

Kyla McConnell and Julia Müller are Ph.D. students at the University of Freiburg, where
they conduct quantitative psycholinguistic research and teach graduate-level statistics
and data skills. They co-organize two groups for gender inclusivity in programming: Julia
Gender Inclusive (@juliainclusive) and R-Ladies Freiburg (@RLadiesFreiburg).
Through these groups, they have fostered a passion for data science and statistical
education, particularly for underrepresented genders. You can find their many
workshops for beginners and more experienced programmers alike on the Julia
Programming Language and R-Ladies Global Youtube channels, and by following us on
Twitter (@McConnellKyla & @JuliaMuellerFr).

  • Building an inclusive (and fun!) Julia community
Kylash Viswanathan

PhD Candidate UIC (Department of Mathematics, Statistics and Computer Science)

  • PHCpack.jl: Solving polynomial systems via homotopy continuation
Kyungdahm Yun

Postdoctoral scholar at the University of Washington in Seattle.

  • Cropbox.jl: A Declarative Crop Modeling Framework
Lars Hellemo

Lars Hellemo is a Senior Research Scientist at SINTEF, working on optimization and decision support, mainly in the energy and health care sectors.

  • SparseVariables - Efficient sparse modelling with JuMP
Lars Loetgering
  • PtyLab.jl - Ptychography Reconstruction
Léo Baty
  • InferOpt.jl: combinatorial optimization in ML pipelines
Letícia Madureira

I'm Letícia Maria (she/her/hers), a final year Chemistry student in Brazil (@geem-lab). Currently, I work with projects involving the development of graphical interfaces, linear and polynomial algebra tools for quantum calculations of molecular electronic structure. I also implement tools for kinetic analysis of chemical reactions (@JuliaChemicalReactions). My main programming language is Julia, but I also program in Python, Rust and JavaScript (depends on the occasion and the project). I advocate free, open and clean code.

Incoming PhD student at CMU in Fall 2022 (@gomesgroup)

  • GapTrain: a faster and automated way to generate GA potentials
Lilith Hafner

I live in Grinnell Iowa :)

  • Julia's latest in high performance sorting
Logan Kilpatrick

Logan is the developer community advocate for the Julia programming language and was formerly the community manager. He is also on the Board of Directors at NumFOCUS and DEFNA. Outside of the Julia community, Logan is a senior technology advocate at PathAI leading ML and OSS advocacy.

  • How to be an effective Julia advocate?
  • 2022 Update: Diversity and Inclusion in the Julia community
Louis Bouvier

PhD student in Machine Learning and Operations Research at CERMICS, Ecole des Ponts.

  • InferOpt.jl: combinatorial optimization in ML pipelines
Luca Ferranti

I am a phd student in computer science. I am enthusiastic about maths, computation, Julia and computational maths in Julia. More details on my github page, if you share some of interests and want to collaborate or chat, do not hesitate to contact me, I hang out fairly often on the Julia slack and zulip channels.

  • Automated Geometric Theorem Proving in Julia
Luca Reale

Currently a student in mathematics at the University of Canterbury in Christchurch New Zealand

  • Universal Differential Equation models with wrong assumptions
Ludger Paehler

Grad Student at TU Munich

  • Fast Forward and Reverse-Mode Differentiation via Enzyme.jl
Ludovic Räss

Geoscientist with strong interests in Julia, HPC, GPUs, and supercomputing. Applications to resolve multi-physics processes in ice dynamics and geodynamics across scales.

  • Distributed Parallelization of xPU Stencil Computations in Julia
  • GPU4GEO - Frontier GPU multi-physics solvers in Julia
  • High-performance xPU Stencil Computations in Julia
  • Teaching GPU computing, experiences from our Master-level course
Luis Eduardo de Souza Amorim

With a broad interest in programming language design and implementation, I'm currently a PostDoc at the Australian National University working on memory management and virtual machines. My previous work from my PhD at Delft University of Technology focused on syntax definition formalisms and parsing.

  • Unbake the Cake (and Eat it Too!): Flexible and Performant GC
Maarten Pronk

GeoData Scientist working on elevation modelling @Deltares. External PhD candidate at @tudelft3d

  • State of JuliaGeo
marc lelarge

Dr. Lelarge is a researcher at INRIA in the DYOGENE Research team which is part of the computer science department of Ecole Normale Superieure, (Paris, France). He is also a lecturer in deep learning at Ecole Polytechnique (Palaiseau, France) and Ecole Normale Superieure. He graduated from Ecole Polytechnique, qualified as an engineer at Ecole Nationale Superieure des Telecommunications (Paris) and received a PhD in Applied Mathematics from Ecole Polytechnique in 2005. His research interests include machine learning, deep learning, graphs and data analytics.
Dr. Lelarge received the NetGCoop 2011 Best Paper Award with his PhD student E. Coupechoux, was awarded the 2012 SIGMETRICS rising star researcher award and the 2015 Best Publication in Applied Probability Award with Mohsen Bayati and Andrea Montanari for their work on compressed sensing.

  • OnlineSampling : online inference on reactive models
Marco Bonici

I am a PostDoctoral Researcher at INAF-IASF in Milano. My research interest lies in the field of Cosmology and, specifically, I am involved in Euclid, a mission of the European Space Agency. I am involved in several scientific working group within Euclid, with a particular focus on the analysis of the final data of the mission.

  • Cosmological Emulators with Flux.jl and DifferentialEquations.jl
Marina Cagliari

I am a PhD student who works in cosmology and the analysis of cosmological surveys.

  • Juliacon Experiences
Mark Kittisopikul, Ph.D.

I am a Software Engineer II in Scientific Computing at the Janelia Research Campus of the Howard Hughes Medical Institute. My stated opinions are my own and not of my employer.

I earned my PhD at UT Southwestern Medical Center studying Molecular Biophysics. I have done postdoctoral work in Cellular Biology.

I enjoy cycling and being a parent.

  • ArrayAllocators.jl: Arrays via calloc, NUMA, and aligned memory
Markus Towara


  • Automatic Differentiation for Quantum Electron Structure
Martin Roa Villescas

Martin Roa-Villescas received his B.Sc. degree in Electronic Engineering from the National University of Colombia, Manizales, Colombia in 2010, and his M.Sc. degree in Embedded Systems from the Eindhoven University of Technology (TU/e), Eindhoven, The Netherlands, in 2013. He is currently pursuing a Ph.D. degree in Bayesian Machine Learning with a special track in education at TU/e. From 2013 to 2018, he worked as an embedded software designer in Philips Research, Eindhoven, The Netherlands. His research interests include probabilistic graphical models, probabilistic programming, and embedded systems.

  • JunctionTrees: Bayesian inference in discrete graphical models
Martin Smit

Hello, my name is Jacobus Smit, but you can call me Martin (derived from my second name). My pronouns are he/him. I just finished the Oxford Master's in Mathematical Sciences (OMMS) at St Cross college and will be starting my PhD in the Socially Intelligent Artificial Systems group at the University of Amsterdam.

I love computational mathematics and statistics, especially their applications to social sciences such as economics and sociology. I author and maintain the TernaryPlots.jl.

  • Juliacon Experiences
Mathieu Besançon

Mathieu Besançon is a researcher at the Zuse Institute Berlin, in the AI in Society, Science, and Technology department, associated with the MODAL-SynLab project and a member of the MATH+ Berlin Mathematics Research Center.

His research interests span solution methods and software in MI(N)LP and convex optimization and in particular the SCIP framework and Frank-Wolfe related approaches.

  • A matrix-free fix-propagate-and-project heuristic for MILPs
  • The JuliaCon Proceedings
Mathieu Morlighem
  • Differentiable Earth system models in Julia
Mathieu Tanneau

Mathieu is currently a Post-doctoral fellow at Georgia Tech, where he is part of the Risk-Aware Market Clearing (RAMC) project (https://ramc.isye.gatech.edu/). His interests are in mixed-integer linear and nonlinear optimization, and their applications to Power Systems.

  • A user’s perspective on using JuMP in an academic project
Matteo Manzi

Matteo is an aerospace engineer with a strong interest in dynamical systems theory and complex systems theory. After conducting research in the Horizon2020 network Stardust Reloaded, working on the use of Artificial Intelligence for Uncertainty Quantification in Orbital Mechanics, and working as a Flight Dynamics Software Engineer for the Space Debris Office of the European Space Agency, he is currently the CEO of MOD SRLS, a company focused on quantitative DeFi, stochastic modelling and uncertainty quantification in space engineering, but also on the interplay between Artificial Intelligence and Blockchain technology for the development of research protocols promoting transparency and reproducibility of software and methodologies, including academic publishing, in the context of DeSci.

  • Interplay between chaos and stochasticity in celestial mechanics
Matthew Fishman

Associate Data Scientist (Research Software Engineer) at the Center for Computational Quantum Physics (CCQ) at the Flatiron Institute in New York. I'm lead developer of ITensors.jl (co-developed with Miles Stoudenmire), a software library for easily developing and running efficient tensor network calculations. Co-developer of PastaQ.jl with Giacomo Torlai.

  • Quantum computing with ITensor and PastaQ
Matthew Wigginton Bhagat-Conway

Matthew Bhagat-Conway is an Assistant Professor in the Department of City and Regional Planning. His research interests are in travel behavior, urban transportation, and statistical methods for transportation data analysis. He is also jointly appointed in the Odum Institute for Research in the Social Sciences, where he is available to assist researchers with statistics and data analysis.

Dr. Bhagat-Conway has a PhD and MA in Geography from Arizona State University, and a BA in Geography from the University of California, Santa Barbara. Prior to graduate school, he was a software developer and project manager for Conveyal, a public transport planning consulting firm, and a fellow in the Data Science for Social Good fellowship at the University of Chicago.

  • Random utility models with DiscreteChoiceModels.jl
Matthijs Cox

Born in The Netherlands. MSc. and PhD. at TU Eindhoven on Applied Physics.

A physicist who loves to code. I taught myself data science and software development.
Currently I work at ASML on the R&D of sensor and algorithms software.

  • Help! How to grow a corporate Julia community?
Mauro Werder

Glaciologist and Julia programmer

  • Teaching GPU computing, experiences from our Master-level course
Max Hawkins

Max is an undergraduate Computer Engineering student at the University of Alabama interested in helping scientists easily and effectively utilize their computing hardware.

  • Metal.jl - A GPU backend for Apple hardware
Michael Schlottke-Lakemper

Michael is a group leader and research software engineer at the High-Performance Computing Center Stuttgart of the University of Stuttgart, Germany. His research focus is on numerical methods for adaptive multi-physics simulations, high-performance computing with Julia, and scientific machine learning.

  • Julia in HPC
  • Julia for High-Performance Computing
Michel Schanen
  • Streamlining nonlinear programming on GPUs
Miguel Marcelino

I am a Master Thesis student at Instituto Superior Técnico and I am currently working on a transpiler to translate Python libraries into Julia. I also have experience in Java, Python, TypeScript, C, a hint of Haskell and, most recently, Julia, which surprised me for how fast and simple programming can be.
Besides my programming activities, I am also a fan of photography, sports and writing.

  • Extending PyJL to Translate Python Libraries to Julia
Miguel Raz Guzmán Macedo

Miguel Raz es un estudiante de física de la UNAM.

  • BoF - JuliaLang en Español
  • Julia REPL Mastery Workshop
Mikael Fremling

My name is Mikael Fremling, and I am working as a postdoc in physics at Utrecht University, The Netherlands.
I study the fascinating properties that develop when a material is prevented from exploring the whole three-dimensional world around us.

In my research, I routinely perform various types of numerical simulations. For a few years, the Julia language has been my go-to choice for numerics.

  • MathLink(Extras): The powers of Mathematica and Julia combined

Bachelor of Computer Science (1992) and Doctorate (2017) at the UPV / EHU. 2011-2012, professor in the Department of Computer Science and Artificial Intelligence. Since 2017, professor of the School of Engineering of Gipuzkoa in the Department of Applied Mathematics.
Within the field of Computer Science, he has developed the following lines of research: efficient implementation of numerical integration methods applied to the simulation of the solar system.

  • SIMD-vectorized implementation of high order IRK integrators
Milan Klöwer

Post-Doctoral Research Assistant, University of Oxford, UK

  • SpeedyWeather.jl: A 16-bit weather model with machine learning
Miles Lubin

Miles Lubin is the benevolent dictator for life (BDFL) of JuMP.

  • JuMP 1.0: What you need to know
Moein Khalighi

PhD candidate in Turku Data Science Group, Department of Computing, at University of Turku, Finland.
Working on Identification and characterization of memory effects in experimental time-series data.
ORCID: 0000-0001-8176-0367
Interested in: Ecological Memory, Fractional Calculus, Differential Equations, Dynamic Modelling, Data Analysis.

  • FdeSolver.jl: Solving fractional differential equations
Mohamed Tarek

Scientist at PumasAI Inc.

  • ImplicitDifferentiation.jl: differentiating implicit functions
Nathan Daly

Software Engineer at RelationalAI

  • Hunting down allocations with Julia 1.8's Allocation Profiler
Nicolau Leal Werneck

Electrical Engineering PhD from Brazil specializing in computer vision and pattern recognition. Julia programmer since v1.0 and scruffy functional programmer.

  • `do block` considered harmless
Niklas Hackelberg

I'm a PHD student working on Magnetic Particle Imaging at the Institute for Biomedical Imaging at the University Medical Center Hamburg-Eppendorf and the Hamburg University of Technology in Germany.

  • Real-Time, I/O, and Multitasking: Julia for Medical Imaging
Niklas Schmitz

Computer science student in the ML group at TU Berlin. Interested in physics, differentiable programming, abstractions and programming languages.

  • Automatic Differentiation for Quantum Electron Structure
Nora Loose
  • Differentiable Earth system models in Julia
Olga Eleftherakou

Born in 1999 in Athens, Greece. A postgraduate student in Applied Statistics (fields of Data Science and Biostatistics) with a Bachelor's degree in Statistics and Actuarial Science, University of Piraeus. Passionate about Machine Learning. Currently learning Julia language by myself.

  • Juliacon Experiences
Oriol Colomes

Oriol Colomes is Assistant Progessor at TU Delft, in the Offshore Engineering section at the Civil Engineering and Geosciences faculty.

  • Solving transient PDEs in Julia with Gridap.jl
Oscar Dowson

Oscar Dowson is a core contributor to JuMP.

  • Improving nonlinear programming support in JuMP
Oscar Smith

I graduated from Carleton College and studied math and computer science, and now work for JuliaComputing on analog circuit simulation. I also make math go vroom.

  • Optimizing Floating Point Math in Julia
Owen Lynch

I'm a master's student at Utrecht University, studying probability and thermodynamics, and I also have been contributing to AlgebraicJulia for the last two years.

  • Compile-time programming with CompTime.jl
Pamela Alejandra Bustamante Faúndez

Pamela Bustamante Faúndez is a PhD candidate from Pontificia Universidad Católica de Chile (Chile). She holds a Master in Industrial Engineering and a BSc degree with Distinction in Industrial Engineering from the Universidad del Bío-Bío.
She has been using Julia since her undergraduate days at Universidad del Bío-Bío, Chile. Co-author of IntroAJulia.jl

  • BoF - JuliaLang en Español
Patrick Altmeyer

I am an economist and computer scientist currently studying for a PhD in Trustworthy Artificial Intelligence (AI) at Delft University of Technology. My research is on the intersection of AI and Financial Economics. In particular, I'm interested in Explainable AI, Counterfactual Explanations, Bayesian ML and Causal Inference and their applications to Financial Economics.

Previously, I worked as an economist for Bank of England where I was involved in research, monetary policy briefings and market intelligence. I hold bachelor's and master's degrees in Economics, Finance and Data Science.

  • Explaining Black-Box Models through Counterfactuals
  • Effortless Bayesian Deep Learning through Laplace Redux
  • Juliacon Experiences
Patrick Fournier

PhD candidate in mathematics @ STATQAM (Université du Québec à Montréal). Website

  • JCheck.jl: Randomized Property Testing Made Easy
Patrick Heimbach

I am a computational oceanographer, professor in the Jackson School of Geosciences, and W. A. “Tex” Moncrief, Jr., chair III in Simulation-Based Engineering and Sciences in the Oden Institute at the University of Texas at Austin. At UT, I direct the CRIOS-UT.github.io group.

My research focuses on ocean and ice dynamics and their role in the global climate system. A computational focus is the use of inverse methods and automatic differentiation applied to ocean and sea ice model parameter and state estimation, uncertainty quantification and observing system design. I earned my Ph.D. from the Max-Planck-Institute for Meteorology and the University of Hamburg, Germany. Prior to joining UT, I spent 16 years at MIT. I am the lead-PI of an NSF CSSI project DJ4Earth.github.io (since 08/2021).

  • Differentiable Earth system models in Julia
Paul Goulart

Paul Goulart joined the University of Oxford in 2014 as an Associate Professor in Engineering Science and a Tutorial Fellow in Engineering Science. He received his SB and MSc degrees in Aeronautics and Astronautics from the Massachusetts Institute of Technology (MIT). Following his undergraduate studies he was a software developer in the flight operations centre for the Chandra X-Ray Observatory at the Harvard-Smithsonian Centre for Astrophysics, and later an engineer in the Autonomous Systems research group at the Charles Stark Draper Laboratory.

In 2003 he was selected as a Gates Scholar at the University of Cambridge, where he received a PhD in Control Engineering in 2007. From 2007 to 2011 he was a Lecturer in control systems in the Department of Aeronautics at Imperial College London, and from 2011 to 2014 a Senior Researcher in the Automatic Control Laboratory at ETH Zurich. He is currently a member of the Control Group in the department of Engineering Science.

His research interests are in high speed optimisation and control for embedded systems, data-driven and robust optimisation, and machine learning.

  • Interior-point conic optimization with Clarabel.jl
Paulito Palmes

I am a research scientist at the IBM Research Europe (Dublin Research Lab) working in the areas of analytics, datamining, machine learning, reinforcement learning, automated decisions, and AI.

I finished my Doctor of Engineering degree from the Toyohashi University of Technology in Japan (2005). I have a Master's degree in Computer Science majoring in Artificial Intelligence (Ateneo de Manila University, 1995) and a Bachelor's degree in Applied Mathematics (cum laude, valedictorian) at the University of the Philippines in the Visayas (1991).

I created and maintain the following Julia packages:
- AutoMLPipeline (Automated Machine Learning Pipeline)
- TSML (Time Series Machine Learning)
- Julia wrapper for Lale in Python

  • Distributed AutoML Pipeline Search in PC/RasPi K8s Cluster
Paul Tiede

Paul Tiede obtained his Ph.D. degree at the University of Waterloo and Perimeter Institute in 2021. Afterward, he joined the Harvard & Smithsonian | Center for Astrophysics and the Black Hole Initiative. He is interested in the intersection of accretion modeling and statistical modeling. As a member of the Event Horizon Telescope, he has developed modeling and simulation techniques for analyzing time-variable emission or "flares" that could enable high-precision measurements of gravity. Additionally, he is a core developer of numerous software packages for the EHT written in Julia, C++, and Python.

  • Comrade: High-Performance Black Hole Imaging
Pedro Xavier

My name is Pedro and I'm from Brasil. I'm a Computer and Information Engineering student at the Federal University of Rio de Janeiro (UFRJ) where I also pursue a Pure Mathematics degree as double major.
I'm intersted in many research topics concerning Maths and it's applications, even those which apply to purely theoretical fields. I've been spending most of my time in the University studying Logic, Compilers, Optimization, Computer Graphics, Quantum Computing and Artificial Intelligence.
Apart from that, I've been into other adventures such as Public Healthcare management systems at FIOCRUZ (Viva o SUS!) and Generative Design in architecture at FAU-UFRJ.
I'm currently building amazing stuff at PSR.

  • JuMP ToQUBO Automatic Reformulation
Peter Cheng

A graduate student working on deep learning and natural language processing.

  • Transformer models and framework in Julia
Pete Vilter

Works at RelationalAI.

  • Hunting down allocations with Julia 1.8's Allocation Profiler
Philip Fackler

Research Software Engineer at Oak Ridge National Laboratory

  • Building Julia proxy mini apps for HPC system evaluation
Philippe Gras

Philippe Gras is a physicist working at the Institute of Research of the Fundamental Laws of the Universe (Irfu). He is using Julia in the context of his research, to analyze data from High Energy Physics experiments.

  • Automatic generation of C++ -- Julia bindings
Phillip Alday

Phillip is a neuroscientist and contributor to the MixedModels.jl ecosystem. Additionally, he has contributed substantially to Effects.jl and StandardizedPredictors.jl

  • RegressionFormulae.jl: familiar `@formula` syntax for regression
Pietro Vertechi

I completed my PhD in neuroscience at Champalimaud Research. There, my research work revolved around the inference of hidden states in tasks performed by both biological and artificial agents. Currently, I am working on novel methods for intelligible artificial intelligence.

An overview of my open source work can be found on my GitHub page.

  • Data Analysis and Visualization with AlgebraOfGraphics
Prem Chintalapudi

M. Eng. student at MIT

  • Unlocking Julia's LLVM JIT Compiler
Przemysław Szufel

Przemysław Szufel is an Assistant Professor at SGH Warsaw School of Economics, Adjunct Professor at Ryerson University, Toronto, co-owner at StatXplorer.com - company offering custom made optimization and machine learning models and Founding Partner of Nunatak Capital - a VC fund that specializes in investing in startups that build their value on data analytics. His main research focus is applying advanced analytics methods, and in particular, machine learning, simulation and optimization in modelling in bringing new value to business processes. He is a co-author of several tools and algorithms for optimal and cost efficient collection and analysis of large data sets in the cloud. He is a co-author of over 40 publications, including handbooks and journal papers, in the area of applying advanced analytics, machine learning and simulation methods to making optimal business decisions. He is an active member of the Julia language community - maintains 3 official Julia packages and has 3rd place in the world answering Julia-related questions on StackOverflow. He is a co-author of book “Julia 1.0 Programming Cookbook: Over 100 numerical and distributed computing recipes for your daily data science workflow”. Przemyław is also co-managing SilverDecisions.pl project (that aims for representing and supporting business decisions), which has been elected by the European Commission to the Innovation Radar programe, grouping the best innovations financed by the EU funds. Przemyslaw has been awarded by the Polish Ministry of Science and Higher Education for implementing data science innovations to business environment. Recently, in a survey by SGH Student Council he has been selected the best teaching professor at SGH Warsaw School of Economics scoring the highest number of student votes among the entire faculty.

  • Optimization of bike manufacturing and distribution (use-case)
Qi Huangfu

Qi Huangfu is the developer of COPT and has worked on many different optimization solvers, including HiGHS and FICO-Xpress.

  • COPT and its Julia interface
Qingyu Qu

Developer and maintainer of SciFracX, interested in differential equations and fractional order modeling.

  • Fractional Order Computing and Modeling with Julia
Rachel Kurchin


  • JuliaMolSim: Computation with Atoms
  • Reaction rates and phase diagrams in ElectrochemicalKinetics.jl
Rafael Diaz

I am a post-doc at "La Sapienza" University of Rome, working in the group of Giorgio Parisi. I mostly study disordered systems like amorphous solids, but I am interested in several topics related to statistical physics. I am Mexican and obtained my BSc and MSc degrees in the National University of Mexico, and then moved to Rome for my PhD.

  • CALiPPSO.jl: Jamming of Hard-Spheres via Linear Optimization
Rafael Schouten
  • State of JuliaGeo
Rainer Heintzmann

Rainer Heintzmann works as a research head and university professor at the Leibniz Institute of Photonic Technology and the Friedrich Schiller University Jena.
His research focuses on imaging cellular function at high resolution. His group develops techniques to measure multidimensional information in small biological objects such as cells, cellular organelles or other small structures of interest. A further interest is in computer-based reconstruction methods.
Software packages in Julia and other languages are developed for scientific computing and visualization with a special focus on optics and deconvolution.

  • PointSpreadFunctions.jl - optical point spread functions
Ranjan Anantharaman

I am a PhD candidate at the Julia Lab at MIT.

  • Adaptive Radial Basis Function Surrogates in Julia
  • The JuliaCon Proceedings
Rasmus Kjær Høier

I am a PhD student at Chalmers University of Technology. My research interests are biologically motivated learning algorithms and energy based models.

  • Bender.jl: A utility package for customizable deep learning
Rik Huijzer

I'm a PhD student at the University of Groningen and co-author of the Julia Data Science book. I think that Julia solves a lot of problems that other languages have, so that's why I like contributing to the language ecosystem. To this end, I have created the Books.jl, PowerAnalyses.jl, Skans.jl and PlutoStaticHTML.jl packages and I contributed to Turing, MLJ, Pluto, julia-actions and more.

  • Reducing Running Time and Time to First X: A Walkthrough
Rodrigo Duran


  • Hands-on ocean modeling and ML with Oceananigans.jl
Ronny Bergmann

I am a mathematician and computer scientist working on optimization on manifolds.

  • Manopt.jl – Optimisation on Riemannian manifolds

Ph.D. student in Materials Science at Columbia University in the City of New York

  • Building workflows for materials modeling on HPC Systems
Sam Buercklin

Sam Buercklin is a research software engineer at Metalenz.

At Metalenz, Sam develops computational E&M tools for optical metasurfaces. His work touches on high performance computing, numerical optimization, and user-facing tools to specify and solve complex technical problems.

Sam has previously worked in various computational domains, including quantum computing, optics, and neuroscience.

  • ChainRules.jl meets Unitful.jl: Autodiff via Unit Analysis
  • Getting started with Julia and Machine Learning
Samuel Isaacson
  • Modeling of Chemical Reaction Networks using Catalyst.jl
Samuel Omlin

Computational Scientist and responsible for Julia computing at the Swiss National Supercomputing Centre (CSCS), ETH Zurich

  • A Fresh Approach to Open Source Voice Assistant Development
  • Distributed Parallelization of xPU Stencil Computations in Julia
  • GPU4GEO - Frontier GPU multi-physics solvers in Julia
  • High-performance xPU Stencil Computations in Julia
  • Teaching GPU computing, experiences from our Master-level course
Sarah Williamson
  • Differentiable Earth system models in Julia
Saranjeet Kaur Bhogal

Saranjeet is a Statistician based in India. She has written the first draft of the R Development Guide under the mentorship of Heather Turner and Micheal Lawrence, funded by the R Foundation. Furthermore, she is supporting Heather Turner in the work on the outreach of the R Development Guide at the Digital Infrastructure Incubator at Code for Science & Society. Saranjeet has also worked with the Julia Language organization for Google Summer of Code 2020. She is eager to learn about open source and open science practices. Saranjeet co-founded the Research Software Engineering (RSE) Asia Association during her participation in the Cohort 4 of the Open Life Science program, to promote the RSE community and profession in the Asia region. She is being mentored by Michelle Barker to build the RSE Asia community. Recently she has been selected in the founding committee of NumFOCUS Project Incubator. This Incubator is designed to support the growth of open source scientific projects and communities.
Personal website: https://saranjeetkaur.github.io/About-Me/

  • Juliacon Experiences
Sebastian Pfitzner
  • Julia in VS Code - What's New
Siddharth Bhatia


  • Building an Immediate-Mode GUI (IMGUI) from scratch
Simeon Schaub

I am currently a master's student in Computational Science and Engineering at the MIT Julia Lab. I have been a Julia user since 2018 and am one of the maintainers of the Julia language. Among other parts of the language, I work on Julia's front end and contribute to packages such as Cthulhu.jl, JuliaInterpreter.jl, and ArtifactUtils.jl.

  • Making Abstract Interpretation Less Abstract in Cthulhu.jl
Simon Danisch

Simon is a freelance software engineer who has been part of the Julia community for more than 9 years and is the author of many Julia packages: * Makie * GeometryBasics * GPUArrays * PackageCompiler * JSServe * FileIO

  • Interactive data visualizations with Makie.jl
Simone Silvestri
  • Hands-on ocean modeling and ML with Oceananigans.jl
Sri Hari Krishna Narayanan

Sri Hari Krishna is a Computer Scientist at Argonne National Laboratory. He conducts research in automatic differentiation, develops AD tools, and applies them to different scientific domains.

  • Differentiable Earth system models in Julia
Stephan Sahm

Stephan Sahm founded Jolin.io, an IT consultancy for high-performant data/ml pipelines powered by Julia. He also organises the biggest Julia meetup in Germany, Julia-User-Group-Munich.
With 10 years experience in data science and 5 years in IT consultancy and data-startups, he strives to bring tomorrows best practice into todays business.

Julia packages developed by Stephan Sahm: Continuables.jl, WhereTraits.jl, ExprParsers.jl, TypeClasses.jl, ExtensibleEffects.jl and more.

  • WhereTraits.jl has now a disambiguity resolution system!
Suyash Bire
  • Hands-on ocean modeling and ML with Oceananigans.jl
Takuya Kitazawa

Takuya Kitazawa is a product developer and data ethicist, working at the intersection of technological and societal aspects of data-driven applications. He professionally serves as a full-stack software & machine learning engineer, data scientist, and product manager, while advocating ethical product development as an OSS developer and technical evangelist.

  • Recommendation.jl: Modeling User-Item Interactions in Julia
Tangi Migot

Postdoctoral student at Polytechnique Montréal

  • PDE-constrained optimization using JuliaSmoothOptimizers
Theo Diamandis

Optimization PhD student at MIT

  • Fast optimization via randomized numerical linear algebra
Tim Besard

Tim Besard is a software engineer at Julia Computing, working on GPU support for the Julia language. He holds a Ph.D. in computer science engineering from Ghent University, Belgium, for research on abstractions to program hardware accelerators in high-level programming languages.

  • JuliaGPU
  • Metal.jl - A GPU backend for Apple hardware
  • oneAPI.jl: Programming Intel GPUs (and more) in Julia
Tim Gymnich

Tim is a postgraduate student at TU Munich, where he is studying for his M.Sc. in Computer Science. His main interests are in compiler optimizations for high performance computing and programming languages.

  • Fast Forward and Reverse-Mode Differentiation via Enzyme.jl
Tim Holy & Valentin Churavy

Tim Holy is the Alan A. and Edith L. Wolff Professor of Neuroscience at Washington University in St. Louis. Valentin Churavy is a Ph.D. student in MIT's Computer Science & Artificial Intelligence Laboratory. Both are long-time contributors to Julia and its package ecosystem.

  • Improvements in package precompilation
Tobias Knopp

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.

  • Fast, Faster, Julia: High Performance Implementation of the NFFT
Tomas Chor

I'm a postdoctoral research at the University of Maryland, Dept of Atmospheric and Oceanic Science

  • Hands-on ocean modeling and ML with Oceananigans.jl
Tom Kwong

Tom Kwong currently works at Meta. He is an experienced software engineer with almost 30 years of industry programming experience. 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.

  • Using contexts and capabilities to provide privacy protection
Torkel Loman

Torkel Loman is a PhD student at the University of Cambridge, working on mathematical modelling of biochemical reaction networks in bacterial stress response.

  • Modeling of Chemical Reaction Networks using Catalyst.jl
Truls Flatberg

Truls Flatberg is a researcher at the research institute SINTEF. With a background from applied mathematics and informatics, he develops decision support tools for industrial problems based on optimization models.

  • UnitJuMP: Automatic unit handling in JuMP
Tushar Chauhan

Tushar Chauhan is a neuroscientist with a keen interest in bio-inspired AI. His work focusses on understanding computations in sensory cortices - both for placing sensory computation in an evolutionary context, as well as drawing inspiration from biological solutions to create highly efficient, robust artificial systems. His methodology is versatile, and an important part of his toolkit includes simulations of neural circuits at various levels of abstraction.

He is a Postdoctoral Research Associate at the Bear Lab, Picower Institute of Learning and Memory, MIT.

  • Simulating neural physiology & networks in Julia
Vaibhav Dixit

I am a Software Engineer at Julia Computing where I am involved in building tools for pharmaceutical industry. I am also a maintainer in the SciML ecosystem of packages for parameter estimation and global sensitivity analysis. I would love to talk to people about bayesian statistics and scientific machine learning as well as building software for EHRs and healthcare in general.

  • Using Optimization.jl to seek the optimal optimiser in SciML
Valentin Churavy


  • JuliaGPU
  • Fast Forward and Reverse-Mode Differentiation via Enzyme.jl
  • Julia in HPC
  • Hands-on ocean modeling and ML with Oceananigans.jl
  • Julia to the NEC SX-Aurora Tsubasa Vector Engine
  • The JuliaCon Proceedings
Valeria Perez

Valeria Pérez is a 24 year-old mexican programmer living in Monterrey, México. She studied Applied Mathematics at the Tecnológico Autónomo de México (ITAM). She graduated in 2020 and worked at the Instituto Mexicano del Seguro Social (IMSS) the largest health provider in México as a junior developer helping with models regarding the COVID-19 pandemic. Currently, she is working in her bachelor thesis and looking to work developing software for techonology companies.
Valeria knows how to program in R, Python and Julia. She is a fluent speaker and writer in English and Spanish. Her passions include gender equality, dance, running and reading.

  • Juliacon Experiences
Valeri Vasquez

PhD candidate, University of California Berkeley
MS, Electrical Engineering and Computer Sciences
MS, Energy and Resources

  • GeneDrive.jl: Simulate and Optimize Biological Interventions
Víctor Álvarez Aparicio

Hi! I'm Víctor Álvarez Aparicio, math and scientific programming enthusiast. I'm currently working as a research fellow in University of La Rioja (Spain), studying applications of Topology in the field of Iteration of Rational Maps and Complex Dynamics. My colleagues and I mainly develop our algorithms in Julia Language.

My interests are Algebraic Topology, Differential Topology, Complex Dynamics and Ergodic Theory, Iterative Proccesses, Scientific Programming, Julia Language, TDA (Topological Data Analysis), among others. I'm really glad and excited to join this community and to share our contributions with everyone interested!

  • Cycles and Julia Sets: Novel algorithms for Numerical Analysis
Victor Boussange

I’m Victor, a fourth year Ph.D candidate in the Landscape Ecology Group at ETH Zürich and at the Swiss Federal Institute for Forest, Snow & Landscape (WSL), Switzerland. I am interested in understanding evolutionary processes that affect the dynamics of ecosystems and economic systems. I conduct my investigations with mathematical models capturing eco-evolutionary dynamics. In parallel, I develop machine learning methods to combine these models with empirical data and infer scientific knowledge. I believe that the combination of mechanistic models and machine learning provides a powerful approach to better understand and forecast the dynamics of real ecosystems and economies.

  • HighDimPDE.jl: A Julia package for solving high-dimensional PDEs
Viral B Shah
  • The State of Julia in 2022
Waïss Azizian

Phd student at ENS Paris & Université Grenoble Alpes

  • OnlineSampling : online inference on reactive models
Weishi Wang

Weishi Wang is a Ph.D. student studying quantum chemistry and quantum physics at the department of physics and astronomy at Dartmouth College. His current research interests are classical and quantum computing applications for electronic structure problems.

  • Quiqbox.jl: Basis set generator for electronic structure problem
Wiktor Phillips

Postdoc in the Julia Lab at MIT

  • Simulating neural physiology & networks in Julia
William F Godoy

Senior Computer Scientist in the Computational Science and Mathematics Division at Oak Ridge National Laboratory. Interests in High-Performance Computing (HPC) infrastructure, computational physics and large scale simulations. Julia aficionado.

  • Building Julia proxy mini apps for HPC system evaluation
William Moses

William S. Moses is a Ph.D. Candidate at MIT, where he also received his M.Eng in electrical engineering and computer science (EECS) and B.S. in EECS and physics. William’s research involves creating compilers and program representations that enable performance and use-case portability, thus enabling non-experts to leverage the latest in high-performance computing and ML. He is known as the lead developer of Enzyme (NeurIPS ’20, SC ’21), an automatic differentiation tool for LLVM capable of differentiating code in a variety of languages, after optimization, and for a variety of architectures and the lead developer of Polygeist (PACT ’21), a polyhedral compiler and C++ frontend for MLIR. He has also worked on the Tensor Comprehensions framework for synthesizing high-performance GPU kernels of ML code, the Tapir compiler for parallel programs (best paper at PPoPP ’17), and compilers that use machine learning to better optimize. He is a recipient of the U.S. Department of Energy Computational Science Graduate Fellowship and the Karl Taylor Compton Prize, MIT’s highest student award.

  • Fast Forward and Reverse-Mode Differentiation via Enzyme.jl
William Thompson

Astronomy PhD candidate and Julia Enthusiast at the University of Victoria.
Maintainer of PairPlots.jl

  • Visualizing astronomical data with AstroImages.jl
Will Tebbutt

I'm a PhD student in the Machine Learning Group at Cambridge, supervised by Richard E. Turner. I'm generally interested in probabilistic modelling and (approximate) inference, how Gaussian processes should feature in probabilistic programming, and how to scale GPs for large time series and spatio-temporal problems.

  • Julia Gaussian Processes
Xiu-zhe (Roger) Luo


  • Comonicon, a full stack solution for building CLI applications
Xuan (Tan Zhi Xuan)

PhD student studying AI, cognitive science, automated planning, and probabilistic programming.

  • PDDL.jl: A fast and flexible interface for automated planning
Yadong Li

Yadong Li is the CTO and co-founder of Julius Technologies Inc. He has over 17 years of experience in quantitative finance, and has held a number of senior leadership roles at Lehman Brothers and Barclays. Yadong has published multiple papers on derivative pricing/risk, capital allocation and optimization etc. He also taught at the Courant Math Finance Master program at NYU. Yadong also has a Ph.D. in Physics, and Master degrees in Computer Science and Financial Engineering.

Yadong is a pioneer in the graph computing space. He created Julius' low-code, auto-scaling and visual graph computing platform that delivers the power of graph computing to every developer!

  • Introduction to Graph Computing
Yijun Xie

Yijun is currently a Senior Data Scientist at Shopify. Prior to joining Shopify, Yijun also worked as a Data Scientist at the Royal Bank of Canada. Yijun obtained his Ph.D. in Statistics from the University of Waterloo, and his research focuses on functional data analysis and dimension reduction.

  • Time to Say Goodbye to Good Old PCA
Yoni Nazarathy

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 over 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. He is the co-author of a data science book, Statistics with Julia: Fundamentals for Data Science, Machine Learning and Artificial Intelligence as well as an ongoing book with drafts available The Mathematical Engineering of Deep Learning.

  • Introduction to Julia with a focus on statistics (in Hebrew)
Zachary Morrell

I am a Postbac working at Los Alamos National Laboratory researching Quantum Annealing. I recently graduated from the University of New Mexico with a double major in Computer Science and Computational Mathematics.

  • Simulating and Visualizing Quantum Annealing in Julia