معرفی
Bo Li is a Research Associate Professor in the Computer Science Department and Data Science Institute at the University of Chicago, specializing in trustworthy machine learning with emphasis on robustness, privacy, and generalization for real-world systems like autonomous vehicles and federated learning.
Her academic journey includes:
- Ph.D. in Computer Science, Vanderbilt University, 2016
- Postdoctoral Researcher, UC Berkeley (2017-2018) under Prof. Dawn Song
- Faculty position at UIUC (2018) prior to current role
Her research bridges theoretical foundations and practical deployments in adversarial robustness, privacy-preserving techniques, and distributed learning frameworks, directly addressing reliability challenges in safety-critical AI applications. This work has established her as a leading voice in trustworthy AI development.
Major recognitions include:
- Sloan Fellowship and MIT Technology Review TR-35 Innovator
- IJCAI Computers and Thought Award and NSF CAREER Award
- Intel Rising Star Faculty Award and Symantec Research Labs Fellowship
- Research funding from Amazon, Facebook, and Google
- Multiple best paper awards at premier ML/security conferences
Her contributions extend beyond academia through media features in Nature, Wired, and New York Times, with research exhibited at London's Science Museum, demonstrating significant societal impact of her work on real-world AI safety.
