Zhu Qi

Professor Zhu Qi is a faculty member in the Department of Electrical and Computer Engineering at Northwestern University's McCormick School of Engineering, with courtesy appointment in Computer Science. He leads the IDEAS Lab (Design Automation of Intelligent Systems Lab) where his research focuses on design automation for intelligent cyber-physical systems and Internet-of-Things applications.

His research interests include safe and robust machine learning for embodied AI systems, cyber-physical security, energy-efficient CPS, and system-on-chip design. Professor Zhu's work particularly addresses safety, robustness, security, adaptability, resiliency, and energy challenges in the design and operation of embodied AI systems. His applications span connected and autonomous vehicles, robotics, advanced manufacturing, wearable computing, smart buildings and infrastructures, and IoT.

Professor Zhu's recent publications reveal a strong focus on safety verification of neural network controlled systems, robust reinforcement learning methods, and applications of large language models in autonomous systems. His work often combines formal verification techniques with machine learning approaches to provide safety guarantees for AI-enabled cyber-physical systems.

• DATE 2022 Best Paper Award
• AutoSec 2021 Best Short Paper Award
• ACM TODAES 2016 Best Paper Award
• IEEE TCCPS Early-Career Award (2017)
• Humboldt Research Fellowship for Experienced Researchers (2017)
• NAE US Frontiers of Engineering participant (2020)

Professor Zhu has secured multiple research grants from NSF (including FM, DESC, and Fuse grants), DOE, ONR, and industry partners including GM and Toyota. His advising includes PhD students Shuyue Lan and Hengyi Liang, and postdoc Chao Huang who became a Lecturer at University of Liverpool. He leads the IDEAS Lab which focuses on cross-layer design, verification, and adaptation of learning-enabled cyber-physical systems.