JuliaCon Local Paris 2025

Research Software Engineer at the Netherlands eScience Center.

PhD student in the Machine Learning Group at TU Berlin.
Interested in in automatic differentiation, explainability and dynamical systems.

• Personal website: adrianhill.de
• GitHub: @adrhill
• Project spotlight

I’m a Junior Researcher at the CENTAI Institute, specializing in statistical and simulation methodologies.

Hello everyone! My name is Alberto Paparella, and I am currently a PhD student in Mathematics at the University of Ferrara. My main interests are Mathematical Logic, specifically Many-Valued and Modal Logics, and Machine Learning. In the last few years, I have been working with the Applied Computational Logic and Artificial Intelligence Laboratory on the SOLE framework for Symbolic Learning in Julia, where my main contributions have been a sub-module for the SoleLogics.jl core package to work with Many-Valued Logics and a package for satisfiability and authomated theorem proving for Many-Valued Multi-Modal Logic based on analytic tableau technique, namely SoleReasoners.jl.

Antonello Lobianco, PhD, is a research engineer employed by a French grande école (polytechnic university). He works on the biophysical and economic modeling of the forest sector and is responsible for the lab models portfolio. He programs in C++, Perl, PHP, Visual Basic, Python, and Julia. He teaches environmental and forest economics at the undergraduate and graduate levels and modeling at the PhD level. For a several years, Antonello has been following the development of Julia, as it fits his modeling needs. He is the author of a few Julia packages, particularly on data analysis and machine learning

Assistant Professor for Computational Cognitive Science
University of Stuttgart

Benoît Legat is an Assistant Professor at UCLouvain in the Mathematical Engineering department (INMA) of the ICTEAM. He is working in optimization and is a core contributor of JuMP.

Cédric is an applied mathematician and a programmer, enjoying developing tools for graphics applications on his free time.
He currently works at JuliaHub as part of the Compiler team.

Dr. Chris Rackauckas is the VP of Modeling and Simulation at JuliaHub, the Director of Scientific Research at Pumas-AI, Co-PI of the Julia Lab at MIT, and the lead developer of the SciML Open Source Software Organization. For his work in mechanistic machine learning, his work is credited for the 15,000x acceleration of NASA Launch Services simulations and recently demonstrated a 60x-570x acceleration over Modelica tools in HVAC simulation, earning Chris the US Air Force Artificial Intelligence Accelerator Scientific Excellence Award. See more at https://chrisrackauckas.com/. He is the lead developer of the Pumas project and received a top presentation award at every ACoP from 2019-2021 for improving methods for uncertainty quantification, automated GPU acceleration of nonlinear mixed effects modeling (NLME), and machine learning assisted construction of NLME models with DeepNLME. For these achievements, Chris received the Emerging Scientist award from ISoP.

Currently a research engineer at Inria Paris developing symbolic computation software. I hold a PhD in Mathematics from Sorbonne Université (Paris 6).

Clément is leading the Technology Cluster for Digital Mechatronics at Siemens Healthineers. He is responsible for building up a team of experts in digitalization, and trigger and lead technological projects to enhance the development of Siemens Healthineers mechatronic products. This role leverages the past experiences of Clément as a Team Lead and Model-based Development expert at Modelon and at other industry leaders such as Airbus Helicopters and Dassault Systèmes. Clément holds two MSc - in France and Spain - in System Engineering and Mechanical Engineering, and a PhD on model-based hydraulic actuation system design for helicopters. Clément is a happy husband and father of two amazing boys - who are making his life even more exiting than his work.

I'm a PhD student in Computer Science at Université Côte d’Azur, working within the COATI team, a joint group between Inria and CNRS. My research focuses on machine learning and graph theory, and I enjoy working at the intersection of theory and practice. As a 2025 Google Summer of Code contributor with the Julia organization, I'm working on integrating GPU-accelerated sparse operations into the GraphNeuralNetworks.jl package to support more efficient implementations of graph neural network layers.

I am permanent researcher at INRAE Montpellier since 2023. I work in Applied Mathematics and Physics. My latest research interests focus on statistical models e.g. Hidden Markov Models, Deep Learning to tackle environmental, and climate (change) problems. I also work on practical Robust statistics. Previously, I did a PhD and half a postdoc in theoretical physics on mean field dynamics of particles systems, looking at as bifurcations, synchronization, instabilities, partial differential equations, etc. I am a Julia enthusiast, and I am working on a few packages (see my GitHub profile.).

I am currently a PhD student at Inria, supervised by Jean-Baptiste Caillau and Ivan Beschastnyi. My research topic is in quantum control theory, with a focus on nearly optimal pulse control of quantum systems. The aim of this project is to develop both theoretical and numerical methods for the fast and efficient manipulation of quantum systems, which are known to be highly sensitive to noise and decoherence.

I am a postdoctoral fellow at Università della Svizzera italiana (USI) in Lugano, Switzerland. The focus of my research is centered around algorithms for graph learning and combinatorial optimization for graph clustering and anomaly detection. Currently, I am leading the project “Directed acyclic graph partitioning for scheduling tasks“, financed by the Huawei Research Center Zürich. I have an MSc and PhD in Computational Science from USI, and a Degree of Physics from the Aristotle University of Thessaloniki, Greece.


Personal website: https://dmspas.github.io/

I engage with scientific computing and computational biology through Julia lang development, with applications in High-Energy Physics, Cryo-ET, and HPC. This includes two Google Summer of Code projects with The Julia Language (2024 & 2025). I am also an O'Reilly DEIJ Scholarship Recipient and a Microsoft Learn Student Ambassador.

Doctorant en première année sous la direction d'Éric Cancès et Mathieu Lewin

I am currently a research engineer at the INRAE Occitanie-Montpellier, working on the WOc-WoD project with Jérôme Harmand and Alain Rapaport. The main objective is to develop optimal control laws for membrane filtration systems. My fields of interests are optimal control, artificial intelligence and optimization.

I originally studied chemistry in Heidelberg, Germany gaining a PhD in Theoretical Chemistry. My extended postdoc time was spent in the US, back in Germany (Dresden) and then at Massey University Albany, transitioning more and more into physics while also taking care of and time off for the education of my children. I am now a Senior Lecturer in physics at the University of Auckland. My research lies in computational modelling from more fundamental topics like melting of matter in extreme conditions or exploring ground and excited states of quantum phases to more applied modelling of percolating carbon-elastomer composites.

🌼 Main developer of Pluto.jl, currently working at TU Eindhoven to develop the course Bayesian Machine Learning.

Come talk to me at the conference! I would love to learn more about what you are working on :) If you are teaching using Julia, definitely come talk to me!

I’m a postdoc at the Max Planck Institute for the Physics of Complex Systems in Dresden, with research interests in machine learning, chaos, and nonlinear time series. My current work focuses on using ML to forecast chaotic dynamics.

I’ve been a Julia user since 2019 and have contributed to the ecosystem with packages like ReservoirComputing.jl and CellularAutomata.jl.

You can find out more about my work on my website.

3nd year PhD student at IRISA (Institute for Research in Computer Science and Random Systems) interested in compilers, MLIR and FPGA.

Ghislain Blanchard is a research engineer in fluid dynamics at ONERA’s Department of Multi-Physics for Energetics since 2015. His research interests include the development of numerical methods for multi-physics simulations and high performance computing.

• PhD in Mathematics from Moscow State University in 2016;
• Postdoc in Johannes Kepler University (Linz, Austria) in 2016-2017 and in New York University in 2017-2019;
• Assistant Professor in Computer Science at the Higher School of Economics (Moscow) in 2019-2020
• Since 2020: Assistant Professor in Computer Science at École Polytechnique, Institute Polytechnique de Paris

Research interests: symbolic computation for differential and difference equations

I am a PhD student in the research group for analysis and applications at TU Berlin. My research focuses on the numerical solution of scattering problems, primarily using boundary integral equation methods.

Grigory Neustroev as a postdoctoral researcher at Delft University of Technology. His research interests lie at the intersection of AI and optimization, with application to energy problems.

I was trained as a theoretical physicist and complex systems researcher, with a heavy focus on interdisciplinary research. After working mostly on the complexity of human mobility, I now study ways in which we can use physics to build learning metamaterials.

I am a PhD student in physics, working as a researcher with my main specialty being supercapacitors and electric measurements. I got into Julia because I believe it's the right programming language for the scope of my research, and, well, I also like it more than other programming languages, so there's that.

Ivan Borisov is a software developer at InSysBio CY. His work focuses on the development and enhancement of mathematical and computational methods in Systems Biology and Quantitative Systems Pharmacology.

I'm an applied mathematician working in the field of computational glaciology. My interests include GPU computing, supercomputing, computational fluid dynamics, numerical analysis, to name a few.

Ivet Galabova is the Development and Integration Manager of HiGHS, the world's leading open-source optimization software. Ivet is a mathematician and research software engineer with a strong interest in linear (LP), mixed integer (MIP) and quadratic (QP) programming problems, build systems and interfaces. Along with completing a PhD in Optimization and Operations Research at the University of Edinburgh, Ivet has been closely involved in the development of the HiGHS from the start of the project in 2017. HiGHS can be used via the HiGHS.jl package in Julia.

I work as a postdoctorial reseach fellow at UiT the Arctic University of Norway where I work on the Centre for New Antibacterial Strategies (CANS). In 2023, I graduated with a PhD in Biotechnology from the Norwegian University of Science and Technology.

My academic experience is centered around systems biology topics such as microbiome analysis, microbial metabolic modeling and gene expression analyses. In addition, I am passionate about scientific software engineering practices and high performance computing.

Professor of applied math at Université Côte d’Azur, CNRS, Inria, LJAD

Scientific interests - Optimisation and control: geometry, algorithms, applications

https://caillau.perso.math.cnrs.fr

Joachim is a theoretical and computational physicist interested in quantum many-body physics, quantum simulation, and quantum technology.

I am a research scientist at CNRS and at the LEGI laboratory in Grenoble, France. I work on modelling and simulation of various fluid dynamical systems, with a special interest in turbulent flows and in the use of fast and accurate numerical algorithms. In this context I also develop different tools in Julia. Over the years, I have contributed a small number of open-source Julia packages motivated by my research work. These include WriteVTK.jl, PencilArrays.jl, PencilFFTs.jl, BSplineKit.jl, NonuniformFFTs.jl and VortexPasta.jl.

Laura Grigori is a Professor at EPFL and former Director of Research at Inria, where she led the Alpines team. Her research focuses on numerical linear algebra, communication-avoiding algorithms, and scalable solvers for scientific computing. She has made influential contributions to high-performance computing with applications in physics and engineering.

Lauren is a Program Manager at TNO, where they lead the development of open-source energy system modelling tools to support Europe's energy transition.

Post-doctorate researcher at Collège de France in computational chemistry, and Julia teacher at École des Mines - PSL.

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Computational geoscientists with Earth science background. Julia GPU and HPC enthusiast.

I'm a PhD student in High Performance Computing at the Advanced Computing Laboratory, Università della Svizzera italiana. I hold a master’s degree in Finance from HEC, University of Lausanne. My research interests include graph theory, anomaly detection, and computational finance. In my free time, I enjoy all mountain sports, from hiking to paragliding.

Hi, my name is Marco Perrotta. I'm a computer science student at the University of Ferrara, where I also work as a collaborator at the Applied Computational Logic and Artificial Intelligence Lab. My main interest is how technology can be used to understand and study language.

I am a Senior Research Data Scientist at the Alan Turing Institute, working on Turing.jl development. In the past I have also contributed to the Julia ecosystem of tensor network packages.

PhD student at TU Braunschweig, Germany, interested in large-scale network control, PDE constrained optimization and nonlinear solvers in Julia.

Matt has been a part of the Julia community for over a decade and is the Director of Sales Engineering at JuliaHub.

I am a mathematical biologist from the University of Bristol, UK. I have previously worked on efficient parameterisation of cardiac ion channel models, uncertainty quantification and models of blood coagulation. I currently work on the software pillar of the EEBio synthetic biology grant.

Hi, I am Mauro Milella, and I am currently a master student at the University of Ferrara. In the last few years, I have been collaborating with the Applied Computational Logic and AI (ACLAI) Laboratory, where we have been developing the Sole framework for symbolic learning entirely in Julia.

Maxime Bouyges is a Research Engineer in Fluid Dynamics at ONERA's Department of Multi-Physics for Energetics. Commencing his career in 2013, he completed a PhD focusing on stability analysis of complex flows within solid rocket engines. Subsequently, he joined the Multiphase Flow Research Team, contributing to the development of the CEDRE-FILM solver - a parallel 3D surface solver tailored for shallow-water and icing applications. Currently, his work encompasses the advancement of physical models and numerical methods, primarily within the realm of icing phenomena.

First year PhD Researcher at the Max Planck Institute for Biogeochemistry with a background in theoretical physics. Julia user since 2017.

Research Summary: Parameterizing physical and other models using neural networks, applications to soil science.

https://github.com/Qfl3x

PhD student @ Technische Universität Braunschweig, Institute for Mathematical Optimization

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

Mykola Lukashchuk is a PhD candidate in Electrical Engineering at Eindhoven University of Technology, focusing on probabilistic inference and efficient Bayesian computation. His research develops flexible computational engines that trade precision for efficiency through message-passing algorithms and Riemannian manifold representations.

He holds dual Master's degrees in Statistics (Kyiv University) and Computer Science (Instituto Politécnico Nacional). His work contributes to the RxInfer ecosystem with particular focus on ExponentialFamilyManifolds.jl and efficient Bayesian inference methods.

I'm a postdoc researcher at the Weierstrass Institute in Berlin in the scientific computing group.
My day-to-day work is all about running finite element simulations for solid mechanics and quantum devices.
I came into touch with Julia two years ago and I love it since.
At WIAS, we have our own Julia PDE solver ecosystem WIAS-PDELib, where I am a core maintainer.
I'm interested in low-level solver routines, software architecture, coding quality, and experiments with new data types and programming features.

Interested about Julia and developer tools.

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Talk to me about: Jane Austen, Pokemon breeding, or classical music! (Or Turing.jl, I guess…)

Ranjan is a sales engineer at JuliaHub, where he works with JuliaHub's modeling and simulation customers. He has a PhD in Applied Mathematics from MIT.

Hi, I am Riccardo Pasini, and I am currently a student at the University of Ferrara. In the last few years, I have been collaborating with the Applied Computational Logic and AI (ACLAI) Laboratory, where we have been developing the Sole framework for symbolic learning entirely in Julia.

PhD student at Barcelona Supercomputing Center (BSC-CNS)

Master's student at KIT (Germany)

Interested in computational mathematics, programming language design, automatic differentiation and compilers.

GitHub: https://github.com/simeonschaub

I am a student at the Royal Military Academy, Belgium.
I am interested in thermodynamics and numerical techniques

Thibaut Cuvelier is currently a software engineer at Google Research, in the Operations Research team. He received a PhD in telecommunications from CentraleSupélec (université Paris-Saclay, France). He is currently working on applications of operations research and reinforcement learning in logistics.

Tim Besard is a software engineer at JuliaHub, where he leads GPU support and development for the Julia programming language. He holds a Ph.D. in computer science engineering from Ghent University, Belgium, and has been a key contributor to Julia's GPU ecosystem since 2014. Tim maintains several foundational GPU packages including CUDA.jl, GPUArrays.jl, GPUCompiler.jl, and LLVM.jl, which together form the backbone of GPU computing in Julia.

Valentin Bogad is a Software Engineer from Vienna, who has been writing Julia code for close to 9 years. With a keen interest in Programming Language Semantics and too many buggy programs in various languages (among which, Java, C#, C and C++) to be embarrassed about writing buggy code, he is always on the hunt for better techniques to write high-quality software.

I am a postdoc at the Alan Turing Institute in London, having previously been a postdoc and PhD student in the Machine Learning Group in Cambridge. I am interested in probabilistic programming, Gaussian processes, algorithmic differentiation, and machine learning for weather forecasting.

I have been a Julia user for a while. I have worked on the algorithmic differentiation ecosystem (Zygote.jl, ChainRules.jl, and Mooncake.jl), the various packages in the JuliaGaussianProcesses organisation. I have also been working closely with the Turing.jl team.