Keynotes | PyCon TW 2026

We invite influential speakers from around the world to serve as our keynote guests at this year’s conference. They will be sharing deep insights from their practical experience and project journeys, along with their insightful observations and visions for future trends.

The keynote speeches are not only a transfer of knowledge and experience but also a conversation that broadens perspectives, inviting us to rethink the connection between technology and the world. Whether you are an emerging talent or an experienced developer, you will find inspiration and strength in these talks.

From CPython to PySpark

For people who have never worked on large open source projects, these projects can feel a little mysterious. We use them every day, but many people do not know how their developers joined the project, what they usually work on, or what someone can do to become part of the community. I first started to contribute to a large open source project in 2022 and became a Python Core Developer in 2024. In 2026, I became an Apache Spark Committer. Through my own story, I hope to make these large open source projects feel less mysterious. I also hope these experiences can give people who want to join similar projects a practical path to follow. In this talk, I will first look back at how I went from being just a programmer to a Python Core Developer. I will share how someone with no previous open source experience can start contributing to an open source project. Then I will talk about the work I have done on PySpark over the past year. Spark started as a Scala project, but its Python part, PySpark, is both important and still rough in many places. As a programmer brought in specifically to improve the Python experience, what kinds of things can I work on? Many of these tasks are things you may also be able to do, whether in your own project, in Spark, or in another large open source project. Understanding this kind of work can help you find a good place to start contributing. It can also help you improve the products built by you or your company.

About the Speaker

Databricks Engineer, Python Core Developer, pdb maintainer, Apache Spark Committer, Bilibili uploader, still write and review code with my own brain.

From Data Collection to Skill Training: Next-Generation Sports Technology Combining AI and VR

Tactical and skill training play a crucial role in athletic development. With the support of artificial intelligence (AI) technology, it is now possible to track the ball and players to detect fine-grained events, helping coaches collect detailed statistics and infer each team’s tactics. Additionally, virtual reality (VR) technology can be leveraged to enhance both the effectiveness and experience of tactical and skill-based training. This talk will introduce modern systems that utilize AI and VR to help athletes conveniently gather valuable sports data and improve a wide range of skills. Key Takeaways: To share the latest advancements in AI and XR technologies within sports technology, demonstrating how these innovations successfully bridge the gap between technical engineering and the sports industry through practical applications in athletes' training and tactical analysis. The audience will learn how modern systems can effectively collect and analyze sports data, and discover the tangible value and future potential of immersive technologies in enhancing athletes' skills and assisting coaches' decision-making.

About the Speaker

Dr. Min-Chun Hu received her Ph.D. from the Graduate Institute of Networking and Multimedia, National Taiwan University in 2011. After graduation, she worked as a postdoctoral researcher at the Research Center for Information Technology Innovation in Academia Sinica, and later served as an assistant/associate professor in the Department of Computer Science and Information Engineering at National Cheng Kung University. She is currently a professor in the Department of Computer Science at National Tsing Hua University. Dr. Hu has been recognized with numerous awards, including Exploration Research Award of Pan Wen Yuan Foundation (2015), Outstanding Young Researcher Award from the Computer Society of the Republic of China (2017), IEEE Tainan Section Best Young Professional Member Award (2018), Google Research exploreCSR Award (2021-2024), CES Innovation Awards (2023), and NSTC Ta-You Wu Memorial Award (2023). Her research interests encompass computer vision, robotic AI, multimedia information retrieval, computer graphics, virtual reality and augmented reality. As a passionate basketball enthusiast, she has long been dedicated to developing sports technology that assists athletes in training and performance analysis. Dr. Hu previously served as Deputy Executive Director of the Taiwan Institute of Sports Science and is also the co-founder of NeuinX, a startup specializing in AI technology for sports analysis. She currently also serves as the Director of the Sports Technology Center at National Tsing Hua University. While her core expertise lies in computer science, her work truly excels in the synergy between technology, athletics, and creative expression. By leveraging immersive AR/VR/MR technologies, she develops transformative tools that bridge the gap between technical engineering and the nuanced demands of the sports and arts industries. - Professor, Department of Computer Science, National Tsing Hua University - Website: https://mislab.cs.nthu.edu.tw/ - Facebook: https://www.facebook.com/trimy.hu/

Accelerating Algorithm Autoresearch

Optimizing software has never been easier with the advent of agentic AI... right? It turns out it's not quite that simple! Autoresearch is a powerful technique for optimization; an agent iteratively modifies, tests, and benchmarks changes to the codebase with the goal of maximizing the benchmark score. While powerful, this process faces challenges, especially at scale: - Cheating / reward hacking (just as in reinforcement learning). - Overfitting to benchmark's inputs. - Tradeoffs between input breadth and build/test/benchmark cost. - Local maximums. In this talk, we'll discuss some of these challenges and how to overcome them, based on examples from the open source GPUMODE kernel competitions and infrastructure. We'll explore how to take autoresearch results from "cool idea" to "shipped in production".

About the Speaker

Bryce Adelstein Lelbach has spent over a decade developing programming languages, compilers, and libraries. He is passionate about parallel programming and strives to make it more accessible for everyone. Bryce is a Principal Engineer at NVIDIA, where he founded the CUDA Core Compute Libraries team and now leads the Vanguard Programming group that drives NVIDIA's roadmap for programming languages, compilers, and core libraries. He is a leader of the systems programming language community, having served as chair of the C++ Library Evolution and the US programming language standards committee. He has been an organizer and program chair for many conferences over the years. On the C++ committee, he has worked on concurrency primitives, parallel algorithms, senders, and multidimensional arrays. He previously worked at Lawrence Berkeley National Laboratory and Louisiana State University. He is one of the founding developers of the HPX parallel runtime system. Outside of work, Bryce is passionate about airplanes and watches. He lives in Midtown Manhattan with his girlfriend and dog.