About
I am an Assistant Professor in the Department of Computer Science at Florida State University, where I serve as the founder and director of RAI (Responsible AI) Lab. I obtained my Ph.D. degree from the University of Virginia, where I was fortunate to work with Prof. Jundong Li.
[Recruiting PhDs & Interns]: I am actively seeking ambitious students for Ph.D. or research intern roles. Please email me with your CV, transcripts, and brief descriptions of your preferred research topics. Kindly mark the subject with [PhD Application] or [Research Intern Application]. Magic Word: Please add appoggiatura in the email subject to ensure attention and to show that you have read this carefully.
Research Summary: My research interest mainly lies in achieving responsible AI that directly contributes to critical AI infrastructures and enhances collaborative innovations for the industry, with a particular focus on Machine Learning as a Service (MLaaS). I have abundant research works under related topics with a particular focus on relational data, including 60+ published research papers (17 first-author ones) in the following areas [see full list]:
- AI Security & Privacy: Model Extraction Attack and Defense; Privacy Certification
- AI Robustness: Generalization; Invariant Learning
- AI Explainability: Mechanistic Interpretability; Graph-Based Explaination
- AI/ML+X (Applications): Healthcare; Disaster Resilience; Social Science
News
- March 2026: We are open-sourcing one of our recent work, LangSkills, with 101K+ structured skills distilled from 62K+ research papers and 23K+ tech sources, packaged for fast offline search. Check our webpage here and our GitHub here!
- March 2026: One paper accepted by ICLR 2026 Workshop on Principled Design for Trustworthy AI - Interpretability, Robustness, and Safety across Modalities.
- Feb. 2026: We are open-sourcing our interactive AI demo site How AI Works under Encyclopedia World! See our GitHub repo here!
- Feb. 2026: We are open-sourcing our geospatial visualization site GeoLive under Encyclopedia World! See our GitHub repo here!
- Jan. 2026: One paper accepted by ICLR 2026.
- Jan. 2026: One paper accepted by TKDE 2026.
- Nov. 2025: One paper accepted by SIGKDD 2026.
- Nov. 2025: Received the Second Prize Award in BlueSky Track of ICDM, 2025
- Nov. 2025: Two papers accepted by AAAI 2026.
- Nov. 2025: Received the Best Short Paper Award at ACM SIGSPATIAL 2025.
- Oct. 2025: One paper accepted by AACL 2025.
- Oct. 2025: One paper accepted by WSDM 2026.
- Oct. 2025: One paper accepted by IEEE BigData.
- Oct. 2025: Featured interview by WCTV (CBS News)!
- Oct. 2025: Invited talk at National Science Foundation PATh CICI Presentation Series.
- Oct. 2025: Awarded the FSU Honors in the Major Mentor Materials Grant.
- Oct. 2025: Awarded Featured AI Researcher by Campus Partners at Florida State University.
- Sept. 2025: One paper accepted by ICDM 2025 Bluesky Track.
- Sept. 2025: One paper accepted by NeurIPS 2025.
- Sept. 2025: Our lab was featured in FSU news! Check it out here.
- Aug. 2025: We published a brand new library focusing on the model extraction attack & defense for graph machine learning! Check our Github Repo and our Official Website!
Invited Talks (Selected)
- 02/2026, FSU-FAMU College of Engineering: Graph-Based Machine Learning as a Service
- 11/2025, Invited panelist at ACM SIGSPATIAL 2025
- 10/2025, University of Delaware: Unleashing the Power of Graph-Based Machine Learning as a Service
- 10/2025, National Science Foundation PATh CICI Presentation Series: Toward Secure Machine Learning as a Service for Collaborative Scientific Research
- 08/2025, Harvard University: Secure Machine Learning as a Service & Interdisciplinary Applications in Healthcare
- 07/2025, Florida State University: Navigating Secure Machine Learning as a Service
- 06/2025, Harvard University: Model Extraction Attacks on Large Language Models
- 04/2025, Rice University: Political-LLM
- 03/2025, UIIC Summit @DistribuTech: AI in Utility Operations
- 02/2025, Harvard University: Model Extraction Attacks Against Graph Learning Models
- 10/2024, INFORMS: Responsible Graph Machine Learning
- 10/2024, Case Western University: Algorithmic Fairness
