Kunal Garg

Kunal Garg is an Assistant Professor in the Mechanical and Aerospace Engineering program at Arizona State University's School of Engineering for Matter, Transport and Energy. He holds a PhD and Master of Engineering in Aerospace Engineering from the University of Michigan (2021, 2019). Prior to joining ASU, he was a Postdoctoral Associate at MIT's Laboratory for Information & Decision Systems (LIDS) and Department of Aeronautics and Astronautics.

His research focuses on integrating control theory with machine learning for autonomous systems, with emphasis on:

• Robust control synthesis for multi-agent coordination
• Finite/fixed-time control under spatiotemporal constraints
• Deadlock resolution in robotics using foundation models (LLMs/VLMs)
• Safety-critical control via barrier functions

Recent publications demonstrate strong focus on neural control barrier functions, deadlock resolution for multi-robot systems, and failure prediction methods. His work frequently appears in top robotics and control conferences including ICRA, CDC, and TRO.

Awards & Honors:

• 2022 DAAD AInet Fellow (AI and Robotics domain)
• Pierre T. Kabamba Award for Excellence in Control Systems (2021)
• Richard and Eleanor Towner Prize for Distinguished Academic Achievement (2021)

He advises MS students through programs like ASU's MORE fellowship and teaches MAE 494/598: Design and Analysis of Nonlinear Controls. His research group develops open-source tools like the NeuralFaultDetector framework for model-free fault detection.