I am interested in machine learning, security, privacy, game theory, blockchain and related topics. I have designed several robust learning algorithms, a scalable framework for achieving robustness for a range of learning methods, and a privacy preserving data publishing system. I am currently working on anomaly detection systems against causative poisoning attacks and malware detection with real world collected big data. I'm also working on adversarial deep learning for training generative adversarial networks (GAN) and designing robust deep neural networks against adversarial examples. I utilize game theoretic analyses to model the interactions between an intelligent adversary and a machine learning system as, allowing us to design robust learning strategies that explicitly account for an adversary’s optimal response. Another focus of my current research is to develop scalable robust algorithms that can process massive amounts of data available for Internet-scale problems regarding specific cloud computing infrastructure to achieve large-scale secure learning for big data.

Previously I have worked on Information security, Network security, MRI analysis, and other Healthcare related research, and I'm still interested in these topics. If you have any common interests, feel free to contact me and discuss.

Department of Computer Science

University of Illinois at Urbana-Champaign

4108 Siebel Center 201 N. Goodwin Ave.

Urbana, IL 61801, USA

Bo Li

Email:    lxbosky at gmail dot com

Or            bli89 at illinois dot edu

​Office:    4310 Siebel

Assistant Professor

Research Interests