I am on the advisory board of the Center for Artificial Intelligence Innovation (CAII) at Illinois, and I am a member of the Information Trust Institute (ITI). I am also affiliated with several research centers aiming to broaden the research collaboration and bridge different communities, such as the Advanced Digital Science Center (ADSC), the Center for Cognitive Computing Systems Research (C3SR), and the Quantum Information Science and Technology Center (IQUIST). I also serve in the Accelerated Learning and Engineering Research Training (ALERT) program.

My research focuses on trustworthy machine learning, with an emphasis on robustness, privacy, generalization, and their interconnections. We believe that closing today's trustworthiness gap in ML requires us to tackle these grappled problems in a holistic framework, driven by fundamental research focusing on not only each problem but also their underlying interactions.

The long-term goal for our group, Secure learning lab (SL2), is to make machine learning systems robust, private, and generalizable with guarantees for different real-world applications. We have worked on exploring different types of adversarial attacks, including evasion and poisoning attacks in digital and physical worlds, under various constraints. We have developed and will continue to explore robust learning systems based on game-theoretic analysis, knowledge-enabled logical reasoning, and properties of learning tasks. Our work directly benefits applications such as computer vision, natural language processing, safe autonomous driving, and trustworthy federated learning systems.

For Prospective Students: Prospective PhDs and postdocs who are interested and experienced in machine learning, security, and optimization, please fill out the form.

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