NYU Shanghai 2025 AI Summer School Program

Guo Li

Professor Guo has spent years researching mathematical statistics, computer vision, and deep learning. Her work emphasizes machine learning models' mathematical foundations and innovative applications, achieving significant breakthroughs in advanced fields such as multimodal perception and intelligent decision-making. As a former data scientist at Alibaba DAMO Academy, she successfully implemented various innovative technologies in key areas like smart shopping and web search. Professor Guo earned her PhD from the University of California, Riverside.

Mathieu Laurière

Professor Laurière's primary research areas include mean-field optimal control and mean-field games, numerical methods, partial differential equations, stochastic analysis, and machine learning. Over the past three years, he has published nearly 50 papers in top-tier international journals and conferences. Previously, he worked as a postdoctoral researcher at Princeton University and was a visiting scholar at Google Brain. Professor Laurière holds a PhD in Mathematics and Computer Science from the University of Paris.

Nasir Memon

Professor Memon has 25 years of teaching and research experience at New York University in the US and is a fellow of IEEE, IAPR, and SPIE. Before joining NYU Shanghai, he held various leadership roles at NYU Tandon’s School of Engineering, including Department Chair of Computer Science and Engineering, Associate Dean for Online Learning and Global Programs, and Vice Dean for Academic and Student Affairs. Professor Memon holds several international patents and has published over 300 papers in prestigious journals and conference proceedings. His work has significantly impacted media security, biometric security, behavioral biometrics, and the intersection of security and human behavior.

Tan Qiaoyu

Professor Tan specializes in advanced fields such as generative AI, multimodal large language models, and graph neural networks, backed by extensive research experience in social media, recommendation systems, and healthcare. Over the past five years, he has published over 30 papers in leading international conferences and journals. In 2023, the American Medical Informatics Association (AMIA) nominated him for an award for Best Student Paper Finalist. Professor Tan earned his PhD from Texas A&M University.

Wilson Tam

Professor Tam's research focuses on natural language processing and AI application development. He has served as the Chief Natural Language Processing Scientist at WeChat AI and Senior Natural Language Processing Scientist at Microsoft in Suzhou. He has accumulated many years of valuable research experience at renowned institutions in the US, such as SRI and Nuance. In 2019, he led the WeChat AI team to victory in the Dialog System Technology Challenge (DSTC9). The "Natural Language Processing course he designed and taught was named a 2022 Shanghai Outstanding Undergraduate Course by SMEC. Professor Tam earned his PhD from Carnegie Mellon University.

Wang Shengjie

Professor Wang's research encompasses various areas of machine learning, including deep learning, artificial intelligence, submodular optimization, computer vision, and natural language processing. In recent years, he has achieved significant advancements in these fields and has published several high-impact papers in top international academic journals and conferences. Professor Wang obtained his bachelor's degree from the University of Illinois at Urbana-Champaign and his Ph.D. from the University of Washington.

Wang Zhaonan

Professor Wang's research focuses on the interdisciplinary field of AI and urban science, specifically the modeling of spatiotemporal data. He earned his bachelor's degree from Peking University and his PhD from the University of Tokyo. During his PhD studies, he worked at the Artificial Intelligence Research Center (AIRC) in Japan and received the MEXT Scholarship from the Japanese government. He conducted postdoctoral research on spatial intelligence at the University of Illinois.

Wen Hongyi

Professor Wen’s research emphasizes human-in-the-loop machine learning, personalized algorithms, and human-AI interaction. During his PhD, he was mentored by National Academy of Engineering member Deborah Estrin. His current work focuses on Multimodal Adaptive Personalized Systems (MAPS), aiming to enhance the development and application of personalized intelligent technologies. Professor Wen received his bachelor's degree from Tsinghua University and his PhD from Cornell University.

Gene Wen

Professor Wen is a globally recognized expert in multimedia streaming technology, dedicated to advancing its standardization and commercialization. He holds over 100 granted patents worldwide, and the products embodying the technologies he invented and developed under his leadership currently serve more than 2 billion users globally. Previously, he was a tenured professor at Tsinghua University and a visiting professor at Princeton University. In 2011, he was elected a Fellow of the IEEE and named to the 2023 Forbes Global Chinese 100 list. Professor Wen received his BS, MS, and PhD degrees with honors from Tsinghua University and is a highly influential leader bridging academia and industry.

Zhao Chen

Professor Zhao's research centers on natural language processing, focusing on understanding the inner workings of large language models and improving their ability to collaborate with external tools. He has published numerous papers at top international conferences and gained extensive research and practical experience through internships with leading teams, including Microsoft Research in the US during his PhD studies. Professor Zhao received his bachelor's degree from Zhejiang University, his PhD from the University of Maryland, and later conducted postdoctoral research at New York University.