Multiple papers accepted by top conferences such as NeurIPS, EMNLP, CCS, ACL, ICML, NAACL, USENIX, ICLR, AAAI, CIKM, KDD, UAI, WWW, etc.; organized several workshops; recipient of Cisco Faculty Research Award.
Research Experience
Currently an Assistant Professor in the College of Information Sciences and Technology at Penn State University.
Education
Received Ph.D. from the Department of Computer Science at UCLA in 2021, under the supervision of Prof. Quanquan Gu; received B.E. from the Department of Electrical Engineering and Information Science at the University of Science and Technology of China in 2015.
Background
Research interests broadly include the theory and applications in different aspects of machine learning, with particular interests on building efficient and trustworthy machine learning models. Recently, research topics include: trustworthiness and safety issues in Large Language Models (LLM alignments, LLM robustness, etc.), security and privacy issues for other emerging machine learning models (multimodal foundation models, federated learning, diffusion models, etc.), and efficient optimization strategies for training large scale foundation models/federated learning (adaptive gradient optimizers, parameter-efficient training, etc.).
Miscellany
Looking for highly motivated PhD/intern students to join his group.