I am an Assistant Professor in the Departments of Electrical & Computer Engineering (ECE) and Mathematics and the Khoury College of Computer Sciences (by courtesy) at Northeastern University, where I direct the Robust Autonomy Lab.

I am broadly interested in the mathematical and algorithmic foundations of trustworthy autonomy. My research applies analytical and computational tools from nonlinear optimization, differential geometry and topology, abstract algebra, and probability and statistics to design principled, computationally efficient, and provably robust algorithms for machine learning, perception, and control.

A major focus of my research is the design of practical estimation and control algorithms for nonlinear systems that provide explicit performance guarantees in real-world operation. To that end, much of my recent work has explored the use of convex relaxation as a general strategy for recovering provably-good approximate solutions to hard computational problems in artificial intelligence. Check out our recent survey article if you’d like to know more!

My research group has multiple openings for fully-funded PhD positions! Please see our announcement of opportunity for more information.


  • Robotics
  • Computer vision
  • Machine learning
  • Optimization
  • Geometry and topology
  • Probability and statistics


  • ScD Computer Science, 2016

    Massachusetts Institute of Technology

  • MA Mathematics, 2010

    University of Texas at Austin

  • BS Mathematics, 2008

    California Institute of Technology

Recent News

[21-Dec-2022] Starting Jan 2023 I will be an Associate Editor for the International Journal of Robotics Research (IJRR) in the area of “Localization and Mapping”. I look forward to reviewing some of the very best work being done in robotics :-)!

[13-Dec-2022] My research group has a new website! Check it out for all the latest and greatest news on trustworthy autonomy :-).

[7-Dec-2022] My research group has been awarded a new grant from Toyota Research Institute to develop novel perception and learning methods for high-agility autonomous driving!

[18-Oct-2022] Our paper on fast verification for certifiable estimation has been accepted to the IEEE Robotics and Automation Letters!

[8-Oct-2022] I delivered a keynote on our group’s work on certifiable machine perception in the workshop on “Safe and Certifiable Navigation and Control for Intelligent Vehicles in Complex Urban Scenarios” at this year’s IEEE International Conference on Intelligent Transportation Systems (ITSC). I very much enjoyed the lively discussion, as well as the opportunity to hear all about the great work being done in this area. Thanks to the organizers for assembling a fantastic series of talks (and also mine ;-P), and in particular to Dr. Weisong Wen for the invitation to speak.

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