Keynote Speech

Dr. Tica Lin holds a Ph.D. in Computer Science from Harvard University and is currently a Senior Data Visualization Scientist at Dolby Laboratories. She also serves as a technology advisor to Taiwan Institute of Sports Science Center. Her work focuses on sports data analytics, human-computer interaction, and mixed-reality applications, with a mission to develop innovative SportsXR systems that combine AI and data visualization to advance human-centered sports technology. Tica has collaborated with NBA teams including the Philadelphia 76ers and Minnesota Timberwolves, U.S. Olympic coaching staff, and NCAA Division I athletic teams to build interactive data systems that support decision-making for coaches and athletes. Her research has been published at top international venues such as ACM CHI and IEEE VIS, earning multiple Best Paper Awards. She previosuly held research and design roles at Visa, Apple, Meta, and Adobe, and co-founded Athleo.ai in 2024, an AI sports tech startup that empowers intelligent and accessible sports video analysis and storytelling. She is also the author of the book My 76ers Story, which offers insights from her frontline experience in basketball analytics and cross-disciplinary innovation. Tica believes technology can amplify the passion and impact of sports—connecting, inspiring, and empowering more people through the power of play. ------------------------------------- Personal website: https://ticalin.com/ Facebook: https://www.facebook.com/SportsXR

In the 21st century, data and technology are fundamentally reshaping how sports are trained, managed, and experienced. This talk will guide the audience through the evolution of sports data analytics and explore its crucial role in today’s industry—from professional leagues like the NBA and NFL establishing dedicated analytics departments to the rapid growth of the global sports tech market. From talent scouting and strategy planning to athlete training and injury prevention, data science and AI are becoming deeply integrated into the sports ecosystem. Drawing from firsthand experience collaborating with NBA teams, national teams, and sports organizations, the speaker will showcase how modern sports data technologies leverage computer vision, real-time tracking, machine learning, and immersive interaction to build the next generation of intelligent, data-driven decision systems. The talk will also highlight emerging trends and explore how interdisciplinary research can combine sports science, data science, and human-computer interaction design. Looking ahead, the session will examine the challenges and opportunities of sports technology in the age of AI. Through the fusion of technology and human-centered design, we are entering a new era of sports that is more real-time, precise, and personalized. —------------------------ I’ve always believed that the ultimate goal of technology is not to replace humans, but to help us live more deeply and meaningfully. Even in an age where AI can generate text, write code, and predict game outcomes, what stays with us when we look back at a game are still the human moments—a breakthrough layup past defenders, a heartfelt post-game embrace, or a play custom-designed by coaches for their players. Sports remind us that the human body, mind, and emotion remain the most powerful algorithms of all. As a long-time researcher and practitioner in human-computer interaction and sports technology, I care not just about using AI to improve data efficiency, but about using visualization and interaction design to truly understand the needs of athletes, coaches, and fans. My goal is to make technology a bridge that deepens human connection. In this talk, I’ll draw from my hands-on experience collaborating with NBA teams, national squads, and top-level coaches to explore how sports can become a vital arena for human-AI collaboration. Beyond the challenges and opportunities of integrating AI and interactive technologies in sports, I want to invite us all to reflect: In this AI era, how can we harness technology to amplify what is most human—our values, our emotions, and our potential?

Donghee Na is a CPython Core Developer and a 2025 Python Steering Council member. He contributes to improving CPython's performance, maintenance, and internal implementations. He pursues shaping Python’s future by ensuring its efficiency, stability, and long-term growth. He is also passionate about fostering CPython activities in the APAC region, organizing local Core Sprints, and encouraging developer engagement in open-source contributions.

Let's talk about the past, present, and future of CPython. We'll review the past efforts of the Python core team and take a look at the current status of projects like Free-threading and Faster CPython. Then, we'll discuss the current state of CPython and explore what the future holds for it. ------------------------------------- Keynote for those who are interested in CPython implementation.

Hey! 👋 I'm Sebastián Ramírez (tiangolo), the creator of FastAPI, Typer, SQLModel, Asyncer, and other open source tools. I've worked with companies and teams across the world, from Latin America to the Middle East, going through Europe and the USA. Always building different types of products and custom solutions involving APIs, data processing, distributed systems, and Machine Learning. And now I've been working full time on FastAPI and friends. 🤓 ------------------------------------- Personal website: https://tiangolo.com/

Imagine you could learn the key ingredients in FastAPI, Typer, SQLModel, etc., to apply them to your product and your code. ✨ (Let me know later if the clickbait worked. 👆️) You can already learn how to use FastAPI and friends in the docs, so I won't teach you that. But you know what you would not see in other places? The history behind my open source tools, including my peculiar background, points of view, and objectives. The key ideas I consider when building things. 🤓 Maybe only philosophical principles would be boring, so I'll also give you very specific tips you can apply to your product. I'll also share some of the things you can learn from building open source projects used by lots of people, including the counterintuitive ideas you wouldn't expect. As a dessert, a random mix of extra tips I would consider. 🍪 Imagine you sat with me for 45 minutes, to give you all the random tips I could think could be useful. That's pretty much this talk. The "years of experience" in FastAPI I have, packed in a single talk, as a giant brain dump. All made of my very subjective opinions (the same as my open source projects), so take everything with a grain of salt, and a lot of coffee. ☕️ ------------------------------------- Share all the tips I could give, which are not necessarily obvious, after building FastAPI and friends, so that people can apply some ideas to their projects and products.