Email: di.wang@kaust.edu.sa
Website: [中文主页] [PRADA Lab][Google Scholar]
CV: CV (last updated in January, 2022)
Address:
Al Khawarizmi Building 1, Room 4243
Division of CEMSE
King Abdullah University of Science and Technology
Thuwal, Saudi Arabia, 23955-6900
I am currently an Assistant Professor of Computer Science and an affiliated faculty of Statistics in the Division of Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) at the King Abdullah University of Science and Technology (KAUST), start from Spring 2021. I am also the PI of Provable Responsible AI and Data Analytics (PRADA) Lab, and a member of Center of Excellence on Generative AI.
Before that, I got my Ph.D degree in Computer Science at the State University of New York (SUNY) at Buffalo in 2020 under supervision of Dr. Jinhui Xu. Before my Ph.D study I took my Master degree in Mathematics at University of Western Ontario in 2015, and I received my Bachelor degree in Mathematics and Applied Mathematics at Shandong University in 2014.
Broadly speaking, I am interested in trustworthy machine learning, large models. Specifically, I am focusing on making Machine Learning and Generative AI have controllable and editable memorization (such as data, concept, and knowledge). Based on different projects, I am also working on AI for Science. Please see my Publications and Research for details.
Opening Positions : I am always looking for visiting scholars, Postdocs, PhD students, (remote) interns, and visiting students. If you are interested in working with me, please send me your CV and transcripts before applying. Also check our website for details!
News (December 2024) : Two papers have been conditionally accepted at The USENIX Security Symposium (USENIX Security 2025)!
News (December 2024) : Three papers have been accepted at The Annual AAAI Conference on Artificial Intelligence (AAAI 2025)!
News (November 2024) : One paper have been accepted at The International Conference on Computational Linguistics (COLING 2025)!
News (September 2024) : Four papers have been accepted at The Conference on Neural Information Processing Systems (NeurIPS 2024)!
News (September 2024) : Two papers have been accepted at The Conference on Empirical Methods in Natural Language Processing (EMNLP 2024)!
News (September 2024) : One paper has been accepted at Neural Computation!
News (September 2024) : One paper has been accepted at Information and Computation (IANDC)!
News (August 2024) : Two papers have been accepted at IEEE Transactions on Computational Social Systems (TCSS) and ACM Transactions on Knowledge Discovery from Data (TKDD)!
News (July 2024) : Two papers have been accepted at The 1st Conference on Language Modeling (COLM)!
News (June 2024) : Our paper "Private Over-the-Air Federated Learning at Band-Limited Edge" has been accepted at IEEE Transactions on Mobile Computing!
News (May 2024) : One paper has been accepted at The 62nd Annual Meeting of the Association for Computational Linguistics (ACL)!
News (May 2024) : Three papers have been accepted at The 41st International Conference on Machine Learning (ICML)!
News (April 2024) : Our paper "Faster Rates of Differentially Private Stochastic Convex Optimization" has been accepted at Journal of Machine Learning Research!
News (April 2024) : Our research proposal "Rigorous Node-level Privacy-preserving Approaches for Graph Neural Networks" has been awarded! Thanks Google and KAUST!
News (March 2024) : Our paper "Persistent Local Homology in Graph Learning" has been accepted at Transactions on Machine Learning Research (TMLR)!
News (March 2024) : Our paper "Privacy Amplification via Shuffling: Unified, Simplified, and Tightened" has been accepted at International Conference on Very Large Data Bases (VLDB 2024)!
News (March 2024) : Our paper "Preserving Node-level Privacy in Graph Neural Networks" has been accepted at The 45th IEEE Symposium on Security and Privacy (IEEE S&P 2024)!
News (March 2024) : Our paper "A Multi-classification Division-aggregation Framework for Fake News Detection" has been accepted at IEEE Transactions on Big Data!