Dr. Jindong Wang is a Tenure-Track Assistant Professor at William & Mary. Previously, he was a Senior Researcher in Microsoft Research Asia for over 5 years. His research interest includes machine learning, large language models, and AI for social science. He has published over 60 papers with 14000+ citations at leading conferences and journals such as ICML, ICLR, NeurIPS, TPAMI, IJCV etc. He serves as the associate editor of IEEE Transactions on Neural Networks and Learning Systems (TNNLS), guest editor for ACM Transactions on Intelligent Systems and Technology (TIST), area chair for ICML, NeurIPS, ICLR, KDD, ACMMM, and ACML, SPC of IJCAI and AAAI. His research is reported by Forbes and other international media. In 2023 and 2024, he was selected by Stanford University as one of the Worldâs Top 2% Scientists and one of the AI Most Influential Scholars by AMiner. He received the best paper award at ICCSEâ18 and IJCAIâ19 workshop. He published a book Introduction to Transfer Learning. He gave tutorials at IJCAIâ22, WSDMâ23, KDDâ23, and AAAIâ24. He leads several impactful open-source projects, including transferlearning, PromptBench, torchSSL, and USB, which received over 16K stars on Github.
He obtained his Ph.D from University of Chinese Academy of Sciences in 2019 with the excellent PhD thesis award and a bachelorâs degree from North China University of Technology in 2014.
Research interest: (See this page for more details)
Machine learning: Iâm generally interested in designing algorithms and applications to make machine learning systems more robust, trustworthy, and responsible. Related topics include: robust machine learning, OOD / domain generalization, transfer learning, semi-supervised learning, federated learning, and related applications.
Philosophy of language models: We mainly focus on understanding the potential and limitation of large foundation models. Related topics: LLM evaluation and enhancement.
AI for social sciences: How to measure the impact of generative AI on different domains? How to assist interdisciplinary domains using powerful AI models? How to use existing social science knowledge to help us better understand AI behaviors?
News
Dec 7, 2024
Invited to be an area chair (AC) for ICML 2025 and senior program committee (SPC) for IJCAI 2025.
Sep 28, 2024
We have one collaborative paper accepted by NeurIPS 24 dataset and benchmark track as a spotlight! [paper]
Sep 26, 2024
We have 5 papers accepted by NeurIPS 2024, including a spotlight! Congrats to the students!
Sep 20, 2024
Our new work AgentReview: Exploring Peer Review Dynamics with LLM Agents is accepted by EMNLP main track! [paper]
Aug 30, 2024
Our vision paper âOn Catastrophic Inheritance of Large Foundation Modelsâ is accepted by DMLR! [arxiv]
Aug 20, 2024
Invited to be an Area Chair for ICLR 2025 and senior program member (SPC) of AAAI 2025.
Highlights
6 of my papers are highly cited and ranked top 20 globally in recent 5 years in Google scholar metrics. See here. I also have 6 papers featured by Hugging Face.