Ren Wang

Ren Wang is an Assistant Professor in the Department of Electrical and Computer Engineering at Illinois Institute of Technology. He joined the university in 2022 after a postdoctoral fellowship and lecturing role at the University of Michigan. His research focuses on trustworthy machine learning, adversarial robustness, and applications in power systems and healthcare. He holds a Ph.D. from Rensselaer Polytechnic Institute and degrees from Tsinghua University.

Education:

• Ph.D. in Electrical, Computer, and Systems Engineering (ECSE), Rensselaer Polytechnic Institute, 2020
• M.S. in Electrical Engineering (EE), Tsinghua University, 2016
• B.S. in Electrical Engineering (EE), Tsinghua University, 2013

Research Interests: His work emphasizes enhancing machine learning trustworthiness through robustness, privacy, and interpretability. Key projects include immune-inspired adversarial defense systems, quantum-resistant machine learning, and applications in smart grids and bioinformatics. Current trends in his publications address backdoor detection, continual learning, and federated learning security.

Grants & Awards:

• NSF FMitF Award (2023): Verified Robustness in Power System-Informed Neural Networks
• ORAU Ralph E. Powe Junior Faculty Enhancement Award (2023)
• NSF CRII Award (2023): Immune-Inspired Learning Foundations
• DOE Midwest Center for Microgrid Cybersecurity (2025)

Advising & Labs: Leads the Trustworthy and Intelligent Machine Learning (TIML) Lab, mentoring over 20 graduate students and visiting researchers. Current projects span adversarial ML, graph learning, and healthcare model purification. The lab collaborates with institutions like Northwestern University and Oak Ridge National Lab.

Recent Activities: Organized workshops on Generative AI interpretability (2024), Midwest Machine Learning Symposium (2025), and served on editorial boards for IEEE Transactions on Signal Processing and Electronics.