Scholar
Dongxiao Zhu
Google Scholar ID: L0CbApYAAAAJ
Professor of Computer Science, Wayne State University
Citations & Impact
Citations
2,268
H-index
26
i10-index
56
Publications
20
Co-authors
28
list available
Publications
Resume (English only)
Academic Achievements
- Published 100+ peer-reviewed publications. Recent research projects include 'VisionWay: Accessibility-aware Path Selection for Wayfinding' (funded by NIH) and 'Collaborative Research: III: Medium: Advancing Large Language Model Unlearning: Foundations and Applications' (funded by NSF). Multiple papers accepted at ECAI-25, CSCW 2025, and Medical Physics.
Research Experience
- Served on program committees of flagship AI conferences (such as NuerIPS, ICML, ICLR, CVPR, AAAI, IJCAI, ACL, EMNLP, AMIA, MICCAI) and of premier scientific journals (such as Bioinformatics, Nucleic Acids Research, Journal of Medical Internet Research, Medical Physics, Transportation Research, Small, BMC Genomics). His research has been supported by NSF, NIH, and private agencies.
Education
- Ph.D. from the University of Michigan, Ann Arbor.
Background
- Currently a Professor at the Department of Computer Science, Wayne State University. His recent research interests are in Trustworthy AI and Applications in health, urban, and social computing with emphasis on adversarial robustness, explainability, and fairness. He is the Founding Director of the Wayne AI Research Initiative and the Director of the Trustworthy AI Lab at Wayne State University. His teaching interest lies in programming language, data structures and algorithms, machine learning, and data science.
Miscellany
- In addition to foundational AI research, he also pursues use-inspired AI research in life, physical, and social science domains. He is passionate about leveraging AI for science and social good, working on reducing spatiotemporal mismatch between housing and employment, future of work, and reducing health disparities. He is deeply engaged in AI education, as the Founder and Inaugural Director of Wayne State’s M.S. in AI (Algorithm & Software track), regularly teaches foundational AI courses, and actively leads initiatives to increase AI literacy among faculty and students.
