Hello! I am Lijie Hu, a fourth-year Ph.D. student in Computer Science at King Abdullah University of Science and Technology (KAUST) since Spring 2021, and I am very fortunate to be advised by Prof. Di Wang in PRADA Lab (Provable Responsible AI and Data Analytics Lab). Before that, I received my Master’s degree in Mathematics from Renmin University of China.

My research interests are Explainable AI and Privacy-preserving ML. Specifically, my research goals are to develop Usable XAI-as-a-Service systems (Usable XAI) and Useful Explainable AI toolkits (Useful XAI). Here usable refers to providing a service for model understanding characterized by faithfulness. Useful means the toolkit can serve as a guide for boosting performance and enhancing the trustworthiness of deep learning models. My research has helped to realize these goals by making progress in the following three directions:

• Theoretical Foundations of Usable XAI: stability([ICML’24 Spotlight],[ICLR’24],[AAAI’23 Oral]), controllability([ArXiv1],[ArXiv2]), consistency([NeurIPS’24],[EMNLP’24])
• Towards Useful XAI in Large Models: cognitive neuroscience, hallucination([COLM’24],[ArXiv3]), bias([ArXiv4],[COLM’24]), jailbreaking, privacy([EMNLP’24 Oral]), copyright
• Towards Usable XAI for Science: healthcare([ICLR’24],[NeurIPS’24]), traffic, material science, marine science

For privacy-preserving machine learning, I mainly focused on private statistical estimation([JMLR,a],[JMLR,b],[ECAI’23],[AISTATS’23],[TKDE],[PODS’22],[ACL’22]) and its application to natural language models([EMNLP’24 Oral],[EACL’24]).

I actively seek opportunities in the 2024-2025 job market and would be pleased to connect with those interested in my work. Please feel free to reach out!

🎖 Honors and Awards

• ICLR 2024 Travel Award.
• AISTATS 2023 Top Reviewer.
• AAAI 2023 Travel Award.
• CEMSE Dean’s List Award, KAUST, 2022, 2024.
• Invited to The ACM Transactions on Database Systems special issue on Best of PODS 2022.
• Beijing Honored Graduates (Top 5%), 2017.
• Merit Student of Beijing (Top 1%), 2016.
• China National Scholarship (Top 2‰), 2014, 2015.

🔥 News

• 2024.09:  🎉 Our paper “Towards Multi-dimensional Explanation Alignment for Medical Classification” has been accepted at The Conference on Neural Information Processing Systems (NeurIPS 2024)!
• 2024.09:  🎉 Three papers (2 Main, 1 Findings) have been accepted at the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP 2024)!
• 2024.07:  🎉 Our paper “SATO: Stable Text-to-Motion Framework” has been accepted at The 32nd ACM Multimedia Conference (ACM MM 2024)!
• 2024.07:  🎉 Two papers have been accepted at The 1st Conference on Language Modeling (COLM 2024)!
• 2024.05:  🎉 Our paper “Improving Interpretation Faithfulness for Vision Transformers” has been accepted at The 41st International Conference on Machine Learning (ICML 2024)!
• 2024.04:  🎉 Our paper “Faster Rates of Differentially Private Stochastic Convex Optimization” has been accepted at Journal of Machine Learning Research (JMLR)!
• 2024.03:  🎉 I am honored to receive the ICLR 2024 Travel Grant.
• 2024.02:  🎉 I am honored to have been elected to the AAAI Student Committee!
• 2024.01:  🎉 Our paper “Differentially Private Natural Language Models: Recent Advances and Future Directions” has been accepted at The 18th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2024)!
• 2024.01:  🎉 Our paper “Faithful Vision-Language Interpretation via Concept Bottleneck Models” has been accepted at The 12th International Conference on Learning Representations (ICLR 2024)!
• 2023.10:  🎉 Our paper “Nearly Optimal Rates of Privacy-preserving Sparse Generalized Eigenvalue Problem” has been accepted at IEEE Transactions on Knowledge and Data Engineering (TKDE)!
• 2023.07:  🎉 Our paper “Finite Sample Guarantees of Differentially Private Expectation Maximization Algorithm” has been accepted at The 26th European Conference on Artificial Intelligence (ECAI 2023)!
• 2023.05:  🎉 Our paper “Generalized Linear Models in Non-interactive Local Differential Privacy with Public Data” has been accepted by the Journal of Machine Learning Research (JMLR)!
• 2023.05:  🎉 Our proposal “Towards Faithful Transformers and Attention Mechanisms,” Co-PIs with Prof. Di Wang, has been granted by SDAIA-KAUST Center of Excellence in Data Science and AI (SDAIA-KAUST) $53,326 USD. Thanks to SDAIA-KAUST!