Organizers

Min Du is an AI Manager in Enterprise AI at NVIDIA, where she leads multiple AI agents initiatives for IT and business operations, translating advances in LLMs and agentic AI into production-grade enterprise solutions. Previously, she was a Principal Researcher at Palo Alto Networks, focusing on machine learning for cybersecurity. She holds a Ph.D. from University of Utah, and conducted postdoctoral research in AI security at University of California, Berkeley under Prof. Dawn Song. Min is recognized for driving high-impact, cross-functional AI initiatives. Her research in AI, security, and privacy has been published in top venues. She has served on the program committee and organization board of multiple top-tier conferences and workshops. 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.

Anbang Xu is a Director in Enterprise AI at NVIDIA, where he drives the strategy, architecture, and execution of scalable AI agent platforms that power a wide range of enterprise use cases. He is known for translating cutting-edge AI technologies into production-grade platforms, leading cross-functional initiatives, and delivering high-impact solutions that improve efficiency, reliability, and automation across the organization. Previously, 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 5,000 citations. He earned his Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign.

Jasmine Jaksic is a Senior Director of Products at NVIDIA, where she leads Enterprise AI Agents product development and management. Previously, she worked at Google, Stripe and SambaNova where she was instrumental in building and launching several pioneering products and technologies. She is a founding member of Istio, the leading open-source service mesh that helps organizations run distributed, microservices-based applications anywhere. She co-founded Posture Monitor, an application for posture correction that won Intel’s innovation award. She is also a contributing writer for The New York Times, Wired, NPR, Huffington Post, Newsweek and InfoQ. She is the author of “Life of a Silicon Valley Hipster” — a parody of all things Silicon Valley. 

Xinyun Chen is a research scientist at Meta (Meta Superintelligence Labs), where she works on advanced AI systems with a focus on large language model reasoning, code generation, and AI safety. Previously, she was a Staff Research Scientist at Google DeepMind, contributing to frontier models such as Gemini with an emphasis on reasoning and deep research capabilities. She received her Ph.D. in Computer Science from University of California, Berkeley, where her research focused on neural program synthesis, adversarial machine learning, and trustworthy AI systems. She has co-organized tens of 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.

Yufan Guo is a Manager of Applied Science at Amazon, where she works on advancing large-scale AI systems, including agentic AI, security applications, and conversational technologies. Her research focuses on large language models, reinforcement learning, and simulation of human behavior, with recent work exploring LLM-based agents for online environments and decision-making. Prior to Amazon, she was a researcher at IBM, contributing to applied machine learning and AI systems. Her academic background includes research in natural language processing and computational linguistics, with publications in top venues such as ICLR and a strong citation record in NLP and text mining. Her work broadly aims to build intelligent, scalable AI systems that improve reasoning, robustness, and real-world applicability of machine learning models.

Tao Yu is an Assistant Professor of Computer Science at The University of Hong Kong and director of the XLANG Lab within the HKU NLP group, where he leads research at the intersection of natural language processing and AI agents. His work focuses on building embodied and conversational AI systems that enable users to interact with data, software, and real-world environments through natural language, including applications such as text-to-SQL, computer-use agents, and human-AI collaboration. He received his Ph.D. in Computer Science from Yale University and was a postdoctoral researcher at the University of Washington NLP group. Prof. Yu has received honors including the Google Research Scholar Award and Amazon Research Award, and has published extensively in top-tier venues such as ACL, EMNLP, and ICLR, contributing influential datasets and systems like Spider for semantic parsing.

May Wang is the CTO of IoT Security at Palo Alto Networks, where she leads AI-driven innovations for cybersecurity at scale. She is the co-founder and former CTO of Zingbox, an AI-powered IoT security company acquired by Palo Alto Networks in 2019, and previously served as a Principal Architect in the Cisco CTO Office. Her expertise spans machine learning, network security, and data analytics, with numerous patents and industry recognitions including VentureBeat’s AI Entrepreneur of the Year. Dr. Wang is also an active board member, speaker, and advocate for women in technology, and holds a Ph.D. in Electrical Engineering from Stanford University and a B.S. in Physics from Peking University.