Organizers

Anbang Xu is a Director at NVIDIA, where he leads a machine learning team focused on developing enterprise AI solutions. His research lies at the intersection of applied machine learning and human-computer interaction (HCI). He serves as an Associate Editor for ACM Transactions on Interactive Intelligent Systems. Anbang has published over 50 research articles, holds more than 25 patents, and has received over 4,000 citations. He earned his Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign.

Min Du is a Manager in the Enterprise AI team at NVIDIA. She received her Ph.D. from the University of Utah, followed by a postdoctoral position at UC Berkeley. Her research in AI, security, and privacy has been published in top venues and has received over 4,000 citations. She has served on the program committees of multiple workshops and conferences, including ICLR and IEEE S&P. Min received the Best Poster Award at SoCC 2017 and the Best Paper Award at ICPE 2022. She was recognized as a Rising Star in EECS in 2019.

Tan Yu is a Senior Staff Machine Learning Engineer in the Enterprise AI team at NVIDIA. His research focuses on information retrieval, recommendation systems, and multimodal understanding. He has published over 40 research articles in top-tier conferences and journals, including SIGKDD, CIKM, SIGIR, CVPR, ICCV, IJCV, ICLR, ECCV, EMNLP, NAACL, AAAI, and IJCAI. Prior to joining NVIDIA, he was a Staff Machine Learning Engineer at TikTok, working on advertisement recommendation, and a Senior Research Scientist at Baidu USA.

Meghana Puvvadi is a Director of Engineering for AI Products & Platforms at NVIDIA. With over a decade of experience in software engineering and machine learning, she specializes in artificial intelligence, large language models, and scalable distributed systems. Her work in inference engines, generative AI applications using agentic and retrieval-augmented generation (RAG) frameworks, and AI infrastructure has driven advancements in AI-powered applications and developer productivity tools. She holds multiple patents in natural language understanding and AI applications and has served as a technical reviewer for top conferences, journals, and engineering books.

Tao Yu is an Assistant Professor of Computer Science at The University of Hong Kong and a director of the XLANG Lab (as part of the HKU NLP Group). His research aims to develop embodied AI agents that empower users to use language to interact with digital and physical environments to carry out real-world tasks. He was a pioneer in text-to-sql domain, and co-hosted EMNLP 2024 Tutorial: Language Agents: Foundations, Prospects, and Risks. He completed his Ph.D. in Computer Science from Yale University.

Yufan Guo is an Applied Science and Engineering Manager at Amazon, building foundation models to improve online shopping experience. Prior to Amazon, she was a Research Staff Member at IBM, where her work combined natural language processing, medical image analysis, healthcare informatics, and insights from cognitive computing. Yufan holds a PhD in Computation, Cognition and Language and an MPhil in Computer Speech, Text and Internet Technology from the University of Cambridge.

Justin "Goju" Gottschlich is the founder, CEO, and chief scientist of Merly, a company aimed at redesigning the very fabric of software development using state-of-the-art machine programming (MP) systems. Goju has an adjunct position in Stanford’s computer science department, where he researches and teaches graduate-level MP and AI. Previously, he was a principal AI scientist and the founder and director of Machine Programming Research at Intel Labs and an adjunct professor at University of Pennsylvania. He received his PhD in Computer Engineering from the University of Colorado-Boulder. He created his first start-up when he was 25, where he wrote millions of lines of C++ code and learned large scale software design. Goju has 45+ peer-reviewed publications, 100+ issued patents, with dozens pending. He and his collaborators’ MP research has been highlighted in venues like The New York Times, The Wallstreet Journal, and was recently highlighted in MIT Technology Review (January 2025) as one of the most disruptive AI software start-ups.

Xinyun Chen is a Senior Research Scientist at Google DeepMind. She received her Ph.D. from UC Berkeley. Her research focuses on large language models, reasoning, code generation, and trustworthy machine learning. Her work SpreadsheetCoder for spreadsheet formula prediction was integrated into Google Sheets, and her work AlphaCode was featured as the front cover in Science Magazine. She has co-organized 14 workshops and tutorials at ICLR, ICML, CVPR, ECCV, ICCV, AAAI, etc. In particular, she co-organized the LLM agents workshop at ICLR 2024, and she is a co-chair of AISec 2022 and 2023.