Faculty
Anshuman Chhabra
Assistant Professor
BEH 307 | 8133960688
Office Hours: Tuesday & Thursday 9.30am-10:00am
Email | | | | |
Biography
Dr. Anshuman Chhabra is an Assistant Professor of Computer Science and Engineering at the 色色研究所 where he leads the Pioneering Advancements in Learning Methods (PALM) Lab. Prior to joining USF, he received his PhD in Computer Science from UC Davis. His research focuses on: (1) methods for auditing/augmenting the trustworthiness and safety properties of AI/ML models (e.g. LLMs); (2) developing scalable data-centric and parameter-centric learning approaches that improve model interpretability, performance, and safety; and (3) utilizing these methods for improving AI adoption and usage in real-world interdisciplinary domains. He has held research positions at Lawrence Berkeley National Laboratory (2017), the Max Planck Institute for Software Systems, Germany (2020), and the University of Amsterdam, Netherlands (2022). His research has been recognized as oral talk acceptances at ICML 2025 and ICLR 2024, as well as a spotlight talk acceptance at AAAI 2020.
Research Interests
AI/ML Safety, Multimodal Generative AI, Large Language Models, Agentic AI, Data-Centric Learning
Teaching Interests
AI/ML, Ethics in Computing, NLP, Data Structures, Algorithms, Theory of Computing
Education
- PhD in Computer Science, UC Davis, 2023.
- B.E. in Electronics and Communications Engineering, Netaji Subhas Institute of Technology, University of Delhi, 2018.
Honors and Awards
- Invited Talk: Improving LLM Safety and Performance Using Data-Centric and Parameter-Centric Learning, University of California-Davis, 2026 (Host: Prof. Muhao Chen)
- Invited Talk on Robust Clustering, Brandeis University, 2022 (Host: Prof. Hongfu Liu)
- Invited Talk on Fair Hierarchical Clustering, Data Skeptic Podcast, 2022 (Host: Kyle Polich)
- Invited Talk on Adversarial Clustering, Uber AI, 2018 (Host: Ryan Turner)
- Awarded UC Davis Graduate Fellowship (2018)
- Received Undergraduate Research Excellence Award by NSIT (2022)
- Awarded Scholarships for NeurIPS'18, AAAI'20, NeurIPS'22, ICLR'23
Key Activities
- Area Chair for ICLR 2026
- Area Chair for ACL ARR 2025
- Reviewer for ICLR 2025-2023
- Reviewer for ICML 2026-2023
- Reviewer for NeurIPS 2025-2022
- Reviewer for ACL ARR 2026-2024
- Reviewer for TMLR
- Reviewer for KDD 2023
- Reviewer for APPROX 2023
- Reviewer for IEEE Transactions on Artificial Intelligence
- Reviewer for AFCR Workshop, NeurIPS 2021/2022
- Reviewer for European Conference on Machine Learning (ECML-PKDD) 2021
- Reviewer for IEEE Internet of Things Journal
- Reviewer for IEEE Transactions on Mobile Computing
- Reviewer for IEEE Systems Journal
- Reviewer for Ad-hoc Networks Journal (Elsevier)
- Reviewer for IEEE Access
- Reviewer for Information Sciences (Elsevier)