| Jun 25, 2025 | Check out our new survey of AI for materials science, covering foundation models, LLM agents, datasets and tools to develop AI foundation models for materials science tasks A Survey of AI for Materials Science: Foundation Models, LLM Agents, Datasets, and Tools  |
| Jan 22, 2025 | One paper Soft Prompting for Unlearning in Large Language Models is accepted to main conference at NAACL-2025. Congratulations!  |
| Jan 15, 2025 | I will server as reviewers for WWW’25, PAKDD’25 and IJCNN’25. |
| Sep 24, 2024 | Minh-Hao was awarded the Reginald R. ‘Barney’ & Jameson A. Baxter and EECS Graduate Fellowship for the academic year 2024-2025. Congratulations! |
| Jun 30, 2024 | Check out our new works on addressing machine unlearning in LLM via soft prompting Soft Prompting for Unlearning in Large Language Models and effective influence analysis for selecting in-context demonstration examples In-Context Learning Demonstration Selection via Influence Analysis |
| Mar 15, 2024 | One co-authored paper Evaluating the Impact of Local Differential Privacy on Utility Loss via Influence Functions was accepted at IJCNN’24. Congratulations! |
| Feb 16, 2024 | Our paper On Large Visual Language Models for Medical Imaging Analysis: An Empirical Study was accepted at IEEE CHASE’24 as a short paper. Congratulations! Hao is awarded IEEE/ACM CHASE’24 NSF Student Travel Award to present his paper at the conference. Congratulations! |
| Jan 30, 2024 | Our paper Robust Influence-based Training Methods for Noisy Brain MRI was accepted at PAKDD’24 as a full paper with an oral presentation. Congratulations! |
| Sep 15, 2023 | Our paper HINT: Healthy Influential-Noise based Training to Defend against Data Poisoning Attacks was accepted at 2023 IEEE International Conference on Data Minng as regular paper (acceptance rate 9.37%). Congratulations! [Code] |