PyCon Sweden 2026

Adam Gorgoń

I’m a Data Scientist with a strong foundation in Python and machine learning. I have great passion for NLP and statistics.

  • gRPC for Beginners
Ana Tanevska

Training Coordinator and Trustworthy AI expert at the Sweden AI Factory within NAISS at Linköping University.

  • Going from idea and data to production
André Eriksson
  • Why do we have to deploy to find out it's broken?
Ashwin Mohanan

Ashwin is the lead training coordinator for Sweden AI Factory (https://SwedenAIFactory.se/) project building compute and providing expert support for industry, public sector and academia at no cost. Ashwin has a Ph.D in Fluid Mechanics, and has engaged deeply with the ecosystem. He is a contributor to several active scientific Python projects such as FluidDyn, Transonic, Pythran to name a few. He has also participated as a speaker in PyCon Sweden and enjoys engaging with Python community through workshops, courses, conferences and meetups. Ashwin believes that we grow stronger through openness and by learning from each other.

  • Going from idea and data to production
Cheuk Ting Ho

After having a career as a Data Scientist and Developer Advocate, Cheuk dedicated her work to the open-source community. Currently, she is working as a developer advocate for JetBrains. She has co-founded Humble Data, a beginner Python workshop that has been happening around the world. Cheuk also started and hosted a Python podcast, PyPodCats, which highlights the achievements of underrepresented members in the community. She has served the EuroPython Society and the Python Software Foundation as board of directors.

  • Audit and evaluate AI generated Python code
David Vujic

My name is David and I'm a software developer. Colleagues and friends may know me as an early adopter of agile ideas and test driven development. I am passionate about things like that, and share the things I learn to the community and the people I work with. My favorite programming languages are Python and Clojure. On my spare time I practice outdoor Parkour & contribute to Open Source.

  • The Tools of an Agentic Engineer
Dawn Wages

Dawn Wages is a leader in the Python and open source community. She is the former Chair of the Python Software Foundation Board and former Director of Community and Developer Relations at Anaconda, and previously led Python community advocacy at Microsoft. A Wagtail core team member and co-founder of Djangonaut Space, Dawn champions inclusive, sustainable open source. She lives in Philadelphia with her partner and two dogs.

  • Keynote from Dawn Wages
Dror Asaf

I have over 15 years of experience across different domains: Healthcare, Automative, Music, Marketing.
I am a big believer in open source and contributing back to the community, as I have contributed to several open sources.
Most recently, cofounded Kovant, where I am the CTO, leading the technical team, including the tooling to ensure velocity of delivery, making developer's life easier and nicer.

  • One Word Faster: Parallelizing Your Pytest Suite Without Rewriting a Line
Elias Freider

Elias works as a member of technical staff at Modal (https://modal.com/) where he focuses on making dev tools that sparks of joy.
Original co-author of the Luigi workflow orchestration engine, and many other internal tools for data teams over the years.

  • Synchronicity - how to ship both sync and async APIs
Eric Rishmüller

Lead Data Engineer with 7 years of experience working in the data universe.

  • Do You Know What a Variable Is? Do You Really?
Farid Mirzayev

By day, he works as a Python Software Developer at Ørsted, helping automate simulation workflows for power engineers. By curiosity, he enjoys exploring Python internals, performance tools, and the strange ways developers convince themselves their code is fast before measuring it.

  • Profiling Python: From cProfile to Sampling
Fatemeh Rahimian

Fatemeh Rahimian is a Life Science coordinator for Sweden AI Factory (https://SwedenAIFactory.se/), a project building compute and providing expert support for industry, public sector and academia at no cost. She is also a Senior Researcher at RISE Research Institutes of Sweden and holds a PhD in distributed algorithms from KTH. Her current research focuses on continual learning on devices with limited resources. She welcomes researchers and companies with bold ideas, and would love to explore how AI can help bring them to life.

  • Going from idea and data to production
Fridtjof Stoldt

I'm a PhD student focussing on programming languages and compilers. Currently, I'm focussed on retrofitting concurrency to Python without breaking existing programs

  • Immutability: Safe and Fast Sharing of Data Across Threads
Harald Nezbeda

Hi, my name is Harald and I'm a passionate Python developer interested in development, DevOps and AI. I'm currently located in Austria working as a Senior Software Developer and Python Technical Leader for Anexia.

I maintain VibePod, an open-source CLI for running AI coding agents in isolated containers, along with other Open Source Projects. I speak regularly at conferences (PyCon DE & PyData, Grazer Linuxtage, WeAreDevelopers World Congress) and local meetups, teach as a part-time lecturer at universities in Klagenfurt, and write Articles and Tutorials on my blog.

  • From API to Agent Tool: Connecting Your Apps with MCP
Hugo van Kemenade

Hugo van Kemenade is a Python core developer and the release manager for Python 3.14 and 3.15. He maintains open-source projects such as Pillow, is a PSF Fellow and PEP editor, and organiser of NaNoGenMo, Helsinki Python and PyData Helsinki. As a Sovereign Tech Fellow, he's lucky to work on maintaining critical digital infrastructure full-time. Hugo lives in Helsinki and sometimes cycles on the frozen sea.

  • How to become a Python release manager
Igor Mosyagin

After doing two PhDs, one in Theoretical Physics and one in Materials Science, I decided that maybe there was such a thing as doing too much science.

As a recovering academic, these days I work across various data roles, doing a bit of everything: engineering, modelling, machine learning, and analytics. During my time in computational research, I picked up a few practical tricks that turned out to be just as useful in industry. I enjoy sharing them because I’ve found that some of them are not as widely known in the Python and data community as I expected.

  • Helping data roles understand each other
Inessa Pawson

Inessa Pawson is an open source maintainer, educator, and community builder. She contributes across the Python ecosystem, most notably to NumPy, PyOpenSci, the Scientific Python project, and helps organize the SciPy conference and the Maintainer Summit at PyCon US. In her role as Director of the Open Source Program Office at OpenTeams, Inessa leads initiatives that support the human infrastructure of open source, broaden pathways to participation, and lay the foundations for an open, distributed AI economy. As AI transforms how software is produced, her work in open source increasingly focuses on how we build technological systems that preserve autonomy, respect privacy, and enable individuals and organizations to retain meaningful ownership and control of their data, knowledge, and creative work. Inessa is perpetually fascinated by collaborative intelligence, incentive design, and jazz.

  • Of Humans and Agents: A Mostly Optimistic Inquiry into the Future of Open Source
Jonas Lindemann

Jonas Lindemann, Director at LUNARC. Jonas has a background in Structural Mechanics where he worked on distributed finite element applications, new user interface concepts for engineering application as well as visualisation of material behavior in mechanical simulations. Since 2004 he has been working at LUNARC designing, implementing and operating HPC resources for Lund University. He is also actively engaged in teaching scientific computing (Python, C++ and Fortran) for graduate as well as post graduate students. At LUNARC he has been the main developer of GfxLauncher and multiple other HPC related tools (ARC Storage Explorer, LUNARC Application portal and ml-browse a graphical module browser for lmod).

  • From Equations to Applications: AI-Assisted Engineering with Python
Kamil Kulig

💼 Building at CTHINGS.CO, 💻 senior backend developer, 🏆 leader, 🐍 python lover, 🎮 gamer, 🕺 king of disco, 🎾🏀⚽️🥊🏈 love sport in every form, 🇵🇱 from Poland

  • gRPC for Beginners
Linda Kolb

Linda has several years of experience using Python across automation, data science and modern tooling. If she is not busy building data flows, she is flowing on the yoga mat. She also organises the DevOpsDays Graz conference.

  • Ready, Set, Publish! Write your first Python Package with uv
Marcus Kohlberg

Founder encore.dev

  • Why do we have to deploy to find out it's broken?
Marcus Näslund

Has been tinkering with code in some form for the past 20 years, currently a software engineer at SSC Space, and a popular science author with his latest book "En Summa av Ögonblick" in stores now. Passionate about education, mathematics, chess, and opinionated style checkers.

  • Let's talk about ...
Nicolas Lara

Forward Deployed Engineer @ Modal

  • At Modal Scale. Building a Vibecoding Platform
Nikita Churikov
  • Opening by PyCon Chairperson
Phil Ewels

Phil Ewels is Product Manager for Open Source at Seqera. He holds a PhD in Molecular Biology from the University of Cambridge, UK and has a career that has spanned many disciplines from scientific lab work and computational bioinformatics research in the life sciences, through to software development and community engagement. He is passionate about open-source software and has a soft spot for tools with a focus on user-friendliness. He is author of MultiQC, co-founder of the nf-core Nextflow bioinformatics community and creator of many small plugins and pet projects with varying degrees of popularity.

  • Starlight Pydocs: Python API reference in Astro Starlight
Ravi Singh

I build Data & AI functions that turn fragmented foundations and isolated AI experiments into trusted platforms, reusable products and measurable business outcomes.

Across DanAds, Readly, Schibsted and HBO Max, I have led work spanning enterprise AI, data platforms, analytics, machine learning and governance. Outcomes include supporting a product initiative that achieved a 14% conversion uplift, reducing per-user LLM licensing costs by 90%, cutting projected annual feature-store costs from $450K to $230K, and supporting the HBO Max launch across 23 European markets.

  • Building a software factory with Python and AI agents
Rory Clear

Software Engineer specialising in computer vision and ML inference

  • Building self-hosted computer vision software with tinygrad
Tobias Wrigstad

I am a professor in computer science at Uppsala University where I do research on programming language design and implementation. In the last years, my main interests have been memory management and concurrency safety which I have explored through type systems and run-time systems. In the context of Python, I currently work on PEP795, and its intended continuation (see e.g. https://dl.acm.org/doi/10.1145/3729313), on garbage collection and data-race freedom in Java, secure compilation for Erlang, and more. Python user since 2000.

  • Concurrency with batteries included
Ulrik Södergren

Ulrik solves odd problems by using broad knowledge on software, electronics and image processing via his own consulting company called OddTech. He has worked for clients such as IKEA, Hasselblad and Öresundsbron. He is currently helping Luxbright to automate their X-ray tube factory and research labs.
Python is his favourite programming language – after to many years with Java, C and PHP.
Ulrik used to write for DatorMagazin and he also has a background as professional photographer and educator in photography.

  • Outsmarting the Power Grid: Python, Heat Pumps, and Day-Ahead Prices