Hi, I am Lijie Hu! I am an Assistant Professor in the Machine Learning Department at Mohamed bin Zayed University of Artificial Intelligence (MBZUAI). I received my Ph.D. in Computer Science from King Abdullah University of Science and Technology (KAUST) in 2025, where I had the privilege of being advised by Prof. Di Wang, who leads the PRADA Lab (Provable Responsible AI and Data Analytics Lab). Prior to that, I obtained my Master’s degree in Mathematics from Renmin University of China.

My research interests are responsible AI, particularly in explainable AI (XAI) and privacy-preserving machine learning. For XAI, specifically, my research is to develop Usable XAI-as-a-Service systems (Usable XAI) and Useful Explainable AI toolkits (Useful XAI). The ultimate goal of my research is to advance XAI that enables trust, control, and meaningful human–AI interaction.

Here, Usable XAI refers to human-centric explanation services that support model understanding with strong faithfulness and practical utility. The central question is: “How can models explain themselves in terms that people can actually understand and use?” Useful XAI focuses on model-centric interpretability, where explanation toolkits reveal the model’s underlying computational graph and provide actionable insights for improving performance and trustworthiness. This line of work asks: “What computation is actually implemented inside large models?” Building on Usable XAI and Useful XAI, my research further explores Interactive XAI, which treats explanations as interfaces for human–AI interaction. By grounding human-centric explanations in model-centric computational understanding, Interactive XAI enables a progression from trust, to control, and ultimately to sustained human–AI interaction. My research helps realize these goals by making progress in the following five directions:

• Theoretical Foundations of Usable XAI: stability([ICML’24 Spotlight],[ICLR’24],[AAAI’23 Oral],[TMLR]), controllability([ICML’25,a],[ICLR’26,b]), consistency([ICCV’25],[NeurIPS’24],[EMNLP’24,a])
• Useful XAI in Large Models: enhance safety([AAAI’25 Oral,a],[ICML’25,b],[NAACL’25],[AAAI’25 Oral,b],[COLM’24,a],[COLM’24,b],[EMNLP’24 Oral,b]), boost model performance([ArXiv]), steer model behavior([WWW’26],[ArXiv])
• System for XAI: acceleration([ICLR’26,b],[ICLR’26,c],[ICLR’26,d]), reproducibility, accessibility
• Interactive XAI: alignment(WWW’26), interaction, co-adaptation
• XAI for Science: protein([ICLR’26,a]), healthcare([ICLR’24],[NeurIPS’24],[ECML-PKDD’25]), autonomous driving([ICRA’25]), material science([Advanced 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],[ALT’22]) and its application to natural language models([EMNLP’24 Oral,c],[EACL’24]).

Openings

My lab is seeking several highly motivated PhD students/Postdocs/RAs/Visiting PhD students. PhD positions begin in Fall 2026. Postdocs/RAs/Visiting PhD students can start anytime. If you are interested in working with me, please email your CV, academic transcript, and a brief outline of your research plan. We enthusiastically welcome Ph.D. students committed to long-term, in-depth research. Prior publications are not required.

🎖 Honors and Awards

• AISTATS 2023 Top Reviewer.
• CEMSE Dean’s List Award, KAUST, 2022, 2024, 2025.
• Invited to The ACM Transactions on Database Systems special issue on Best of PODS 2022.

🔥 News

• 2026.02:  🎉 One paper has been accepted at Advanced Science!
• 2026.01:  🎉 Six papers have been accepted at ICLR 2026! Congratulations to Jiahao, Wenjie, Huanyi, and Chenyang!
• 2026.01:  🎉 One paper has been accepted at WWW 2026! Congratulations to Manjiang and Hongji!
• 2025.12:  🎉 I’m happy to serve as Area Chair of ACL!
• 2025.11:  🎉 I’m happy to serve as Area Chair of ICML!
• 2025.10:  🎉 I’m happy to serve as Area Chair of EACL!
• 2025.10:  🎉 I’m happy to serve as Action Editor of ARR (ACL Rolling Review)!
• 2025.09:  🎉 Our paper “EAP-GP: Mitigating Saturation Effect in Gradient-based Automated Circuit Identification” has been accepted at NeurIPS 2025!
• 2025.08:  🎉 I’m happy to serve as Area Chair of ICLR 2026!
• 2025.08:  🎉 I’m happy to serve as Area Chair of ACML 2025!
• 2025.08:  🎉 Two papers have been accepted at Empirical Methods in Natural Language Processing (EMNLP 2025)!
• 2025.08:  🎉 Beginning my new role as a Tenure-Track Assistant Professor of Machine Learning at Mohamed bin Zayed University of Artificial Intelligence (MBZUAI)!