Jinghui Chen
Scholar

Jinghui Chen

Google Scholar ID: mKia7Y4AAAAJ
Assistant Professor of Information Sciences and Technology, Penn State University
Machine LearningTrustworthy Machine LearningLarge Language Models
Citations & Impact
All-time
Citations
4,110
 
H-index
29
 
i10-index
44
 
Publications
20
 
Co-authors
20
list available
Resume (English only)
Academic Achievements
  • 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.