Lijie Hu
Assistant Professor of Machine Learning
Research Interests
Professor Hu's research focuses on responsible AI, particularly in explainable AI (XAI) and privacy-preserving machine learning. Her recent research emphasizes making XAI more accessible and practical. Her work centers on developing Usable XAI-as-a-Service systems (Usable XAI) and Useful Explainable AI toolkits (Useful XAI), bridging the gap between theoretical innovation and real-world application.
Prior to joining MBZUAI, Professor Hu completed her Ph.D. in Computer Science at King Abdullah University of Science and Technology (KAUST). Her research focuses on responsible AI, with particular emphasis on explainable AI (XAI) and privacy-preserving machine learning.
Her recent work aims to make XAI more accessible and applicable in practice. She has introduced concepts such as Usable XAI-as-a-Service systems and Useful Explainable AI toolkits, bridging the gap between theoretical advances and real-world implementation.
Professor Hu’s research was recognized as a "Best of PODS 2022" selection. She has also received several honors, including the KAUST Dean’s List Award and recognition as a Top Reviewer at AISTATS 2023. In addition to her research, she contributes to the broader academic community as a member of the AAAI Student Committee.
- Ph.D. in Computer Science from King Abdullah University of Science and Technology (KAUST)
- M.S. in Mathematics from Renmin University of China
- B.S. in Mathematics from Minzu University of China
- Best of PODS 2022
- King Abdullah University of Science and Technology (KAUST) Dean’s List Award in 2022 and 2024
- Top Reviewer AISTATS 2023.