JuliaCon 2026

@juliacon.org

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Join the largest annual conference organized around the Julia programming language Mainz, Germany. August 10th–15th, 2026. https://juliacon.org/2025/

The Julia for High-Performance Computing (HPC) minisymposium at JuliaCon is one of the main events of the year for the Julia for HPC community, bringing together HPC and Julia experts to present and discuss recent advances that make Julia a powerful language for HPC.
This is a showcase of Julia across several industry verticals from engineering, life sciences and beyond. Speakers will outline case studies at their respective organizations and comment on the advantages and disadvantages of using Julia in their roles, or across teams or business units. The Julia community stands to benefit from increased adoption across the industry. This series of talks outline the strengths and weaknesses of Julia in the context of different industries, in addition to case studies and comments on using Julia in a production environment. Additionally, the group may touch upon using Julia in domains with regulatory constraints.
Julia is an increasingly established language for Earth and climate science due to interactivity, productivity, performance and a growing software stack for high-performance computing, big data analysis and visualisation. It empowers developers to build performant Earth-System model components in a composable way, thus allowing users to easily become developers themselves and fostering collaborative work. In this minisymposium speakers will present software projects used for and in Earth system science.
Computing has a rich history in biological discovery, and the needs of biologists are continuing to drive algorithm development in multiple domains. Close alignment between developers and deep biological domain expertise is crucial in this field and a programming language such as Julia provides an ideal platform for such tight collaborations that require a range of access points to the software. Julia provides interactive and notebook-based interfaces commonly used by experimentalists whilst also giving algorithm developers the opportunity create more complex workflows and structures, and optimize performance as needed. In this minisymposium, we aim to highlight ways in which computational biologists* are using Julia to advance our understanding of living systems, in academia and industry, while also contributing to the package ecosystem and core language on multiple fronts. "Computational biology" is a broad tent. Topics presented include algorithms for text matching and search (bioinformatics), modeling and machine learning (systems biology and quantiative pharmacology),statistics and data science (experimental analysis, epidemiology), and imaging and geospatial statistics (microscopy), among others.
In the last few years, the state of geospatial tooling in Julia has significantly improved. We now have first-in-class libraries with native algorithms that are the fastest that exist in the world. Today, Julia has capabilities to some degree or another over the full geospatial stack: file I/O, raster and vector data processing, visualization, and analytics. This minisymposium is meant for discussion of software projects in earth observation, geostatistics, geometry, or anything else geospatial/GIS related - with emphasis on how they can empower users to do interesting things!
Engineering is the cornerstone of our society, driving technological innovation and addressing complex engineering challenges across disciplines. The rapid advancement of computational tools has become essential for pushing the boundaries of engineering research and practice. Among them, Julia is emerging as a preferred solution, owing to its user-friendly syntax, high-performance capabilities, and ever-growing package ecosystem. Julia is transforming the way engineers approach modeling and analysis across diverse engineering disciplines. The Engineering with Julia minisymposium aims to bring together researchers, industry professionals, and educators to showcase Julia's contributions to engineering. We will explore its transformative potential for enhancing infrastructure, advancing reliability, and promoting sustainability in the context of modern engineering solutions. Additionally, we also aim to provide a platform for open discussion on the computational tools that engineers rely on in today’s research, practice, and education.
Partial differential equations describe the evolution of physical systems in space and time. Realistic models involve the nonlinear coupling of different physical fields, and require their self-consistent solution. Numerical simulation methods involve various space and time discretization approaches which almost certainly lead to sparse nonlinear and linear systems to be solved. Julia enables efficient composition of partial differential equations (PDEs) solvers through its multiple dispatch, while also offering access to parallel computing and hardware accelerators such as GPUs. The mini-symposium shall discuss various tools and approaches available in Julia which are relevant for PDEs like sparsity handling, automatic differentiation, mesh generation, linear and nonlinear system solvers, parallelization, pre- and post-processing, and visualization. It shall highlight applications from various fields of science and engineering. At the same time, issues like interoperability between different package ecosystems and missing functionality shall be discussed. An open panel will specifically discuss infrastructure needs, identify gaps, and coordinate development efforts to advance the ecosystem.
The adoption of differentiable modeling and simulation has gained significant traction in computational science and engineering (CSE) workflows, driving advancements in optimization, sensitivity analysis, uncertainty quantification, model discovery, and more. This minisymposium brings together scientists, researchers, practitioners, students, and software developers who are either utilizing or developing differentiable computational models. We also welcome those seeking inspiration to integrate these methodologies into their own work. Our goal is to provide a platform for knowledge exchange and learning from each other's experiences—highlighting both success stories and challenges encountered along the way. We invite contributions that share experiences in developing differentiable computational models—including specific challenges faced, innovative solutions found—and applications of these models across various domains. Attendees can look forward to learning from notable contributors within the Julia community who will present innovative use cases while fostering collaboration among participants. Through networking opportunities and shared insights, we aim to inspire both seasoned users and newcomers by demonstrating how differentiable modelling can enhance model-based CSE workflows!
Approximate computing techniques within numerical linear algebra algorithms are raising major interests in the context of exascale-era supercomputers and problems. By approximating all or certain strategic parts of the computation, approximate computing methods can substantially reduce the time, memory, and energy consumption of scientific computing algorithms. In this context, Julia has offered a fantastic playground for the development of approximate computing techniques, such as mixed precision algorithms, randomization and sketching, or low-rank approximations. This minisymposium features talks from researchers and practitioners describing their use of Julia for studying the numerical behavior or leveraging the computational benefits of approximate computing techniques.
The computational humanities and social sciences (CHSS) increasingly rely on large, text-rich datasets – from digital corpora and learner corpora to discourse-annotated datasets and historical archives – yet researchers often struggle with the limitations of existing tools for large-scale data processing, modeling, and reproducibility. This minisymposium introduces Julia as a powerful, expressive, and high-performance solution for CHSS research. We showcase how Julia’s strengths (speed, a solid type system, first-class multiple dispatch, and seamless interoperability with Python and R) enable both rapid experimentation and production-grade analysis. Through case studies ranging from corpus statistics and collocation networks to mixed-effects modeling of experimental data and large-scale language data pipelines, we highlight existing Julia packages and other emerging ones such as TextAssociations.jl and demonstrate how Julia can substantially expand what researchers in the humanities and social sciences can achieve. The minisymposium aims to build bridges between Julia developers and CHSS scholars while fostering a new community of users working with rich textual, linguistic, and sociocultural data.
Scientific machine learning (SciML) methods are techniques which incorporate machine learning with mechanistic modeling. The purpose of this minisymposium is to share improved methods and applications of SciML to showcase the ever advancing ecosystem in Julia. Examples of topics fit for this minisymposium include: New algorithms and software for physics-informed neural networks Tips, tricks, and techniques for improving convergence of universal differential equations Applications of fitting universal differential equations on real data and verification Methods which use neural networks with classical solvers in new ways Advancements in automatic differentiation for SciML applications Methods which use learning to accelerate numerical simulations (surrogates, metamodels, emulators, reduced order methods (ROMs)) Advancements in compiler and optimization techniques to improve learning in SciML scenarios.
The Computational Physics Minisymposium highlights numerical methods, algorithms, and software implementations—including testing and benchmarking—for modeling and simulation across a broad range of theoretical and computational physics subfields. It serves as a “trading port” for computational methods that connect diverse areas of physics. This year’s minisymposium will feature a special session spotlighting the JuliaQCD and JuliaFewBody ecosystems.
The JuliaGPU community has been a strong presence at JuliaCon for many years, and continues to be a strong foundation of Julia's overall computing ecosystem. In 2026, we propose to organize a minisymposium specifically focused on the usage and programming of GPUs (and other accelerators) in Julia. There is some overlap with an HPC minisymposium, however we intend to focus our track on very GPU-specific content or low-level details that make JuliaGPU tick. Additionally, material relating to non-GPU devices (such as TPUs, APUs, IPUs, etc.) are very welcome!
An advertisement for PumasAI: "by scientists, for science"
An advertisement for the software company CodeGlass: "bringing clarity to Julia's runtime"
A poster advertising cutting-edge satellite solutions by Eutelsat
Logos of JuliaCon Local Paris 2025 and Temple Capital
The JuliaCon Global 2025 Diversity, Equity, and Inclusion (DEI) Committee is excited to announce a Proprosal-A-Thon for writing your JuliaCon Global 2025 proposal! The call for proposals is out right now, and we are looking for both talks and posters for JuliaCon Global 2025. We will run the event during two days in different time zones Sunday January 26th at 4pm CET. If you are curious about the process of writing and submitting a proposal (you don’t need an idea yet!), we encourage you to attend! The event will start with a 30-minute presentation on the process, followed by an hour of office hours where you can ask individual questions. This event is intended to help community members who are first-time presenters.
JuliaCon 2025 | University of Pittsburgh & Carnegie Mellon University, July 21-26 2025
Keynote on July 11 @ 9AM GMT+2 by Maurice du Mee titled: Software at ASML: The Force behind making microchips Abstract: In a rapidly evolving landscape of semiconductor manufacturing, ASML’s advanced lithography technologies are pivotal in driving Moore’s Law forward. The focus of this talk is ASML’s holistic approach to Software development and acceleration of Software delivery to customers. In addition, we discuss how ASML engages and cultivates Software talents. At the end of this presentation the attendees will have an understanding of ASML’s software ecosystem and its critical role in advancing the future.
Keynote on July 10 5:40PM GMT+2: Materials Modeling: Bonding across atoms, code, and people Presented by Dr. Michael Herbst & Dr. Rachel Kurchin Abstract: Current solutions to key 21st-century challenges (such as climate change, food insecurity, healthcare, and communications) are fundamentally limited by the functional properties of known materials. Designing new materials increasingly relies on computational modeling with state-of-the-art workflows frequently interweaving first-principles with empirical modeling as well as data-driven approaches. To make advances, we often must establish novel connections across fields such as physics, chemistry
JuliaCon 2024 Poster for Dr Andrew Fitzgibbon's talk: AI Hardware and Real-world AI which takes place on July 11, 11:30 - 12:30 The talk abstract reads: AI is fast becoming a significant consumer of the world’s computational power, so it is crucial to use that power wisely and efficiently. Our approaches to doing so must span all levels of the research stack: from fundamental theoretical understanding of the loss surfaces and regularization properties of machine learning models, to efficient layout at the transistor level of floating-point multipliers and RAM.