I am an Assistant Professor of Electrical Engineering in the School of Engineering and Applied Sciences (SEAS) at Harvard University. I obtained my Ph.D. in Robotics from the Massachusetts Institute of Technology, where I was fortunate to work with Luca Carlone in the Laboratory for Information and Decision Systems.
I direct the Computational Robotics Lab at Harvard University. My group studies the algorithmic foundations of robot perception, action, and learning. We are broadly interested in estimation and decision-making with performance gurantees.
Current Interests: I am currently interested in three challenges.
- Trustworthy robot perception with learned modules
- Perception-based planning and control with performance guarantees
- Convex optimization for estimation, decision-making, and learning
Prospective Students: For PhD opportunities, please apply to the PhD program at Harvard SEAS (e.g., in EE/CS/AM/ME) and list me as a potential advisor. I am also open to taking (undergraduate or graduate) research interns.
This year I am particularly looking for a strong candidate in statistics and machine learning.
I am interested in working with self-motivated candidates with (a) a strong theoretical and computational background (e.g., applied math, optimization and control, statistics, machine learning, and scientific computing), and/or (b) rich experiences in real robotic platforms (e.g., drones, manipulators, ground vehicles).
Due to the large volume of inquiries, I may not be able to reply to all emails, and I apologize for this.
|Feb 6, 2024
|Preprint on discounted adaptive online prediction, as a downstream application, we give a better algorithm for performing online adaptive conformal prediction!
|Jan 31, 2024
|Preprint on sparse polynomial optimization with unbounded sets, as an application, we solve optimal control of the Van der Pol oscillator to certifiable global optimality. Congrats to Shucheng!
|Jan 8, 2024
|Preprint on understanding and computing the true optimal value function of infinite-horizon pendulum swing-up
|Dec 11, 2023
|Talk at Department of Mathematics, National University of Singapore, thank you Kim-Chuan Toh!
|Nov 30, 2023
|Preprint with Yukai Tang and Jean-Bernard Lasserre: revisiting the minimum enclosing ellipsoids of set-membership estimation in control and perception, using convex optimization; my presentation at Autonomy Talks can be found here
|Sep 30, 2023
|Preprint with Xihang Yu: SIM-Sync, certifiably optimal 3D scene reconstruction with learned depth
|Jul 30, 2023
|Congratulations to Shucheng Kang on getting his paper “Verification and Synthesis of Robust Control Barrier Functions” accepted to IEEE Conference on Decision and Control!
|Apr 7, 2023
|Object Pose Estimation with Statistical Guarantees accepted to CVPR 2023 as a highlight paper
|Mar 22, 2023
|New preprint on verification and synthesis of robust control barrier functions: you do not need iterative sum of squares
|Feb 23, 2023
|Talk at Yau Mathematical Sciences Center, Tsinghua University
Awards & Recognitions
|MIT LIDS/ALL Magazine: Honing Robot Perception
|MIT News Spotlight: Making self-driving cars safer through keener robot perception
|Best Paper Award Finalist at Robotics: Science and Systems (RSS)
|Robotics: Science and Systems (RSS) Pioneer
|Graduated Non-Convexity (GNC) algorithm included in Matlab Navigation Toolbox and appeared in MathWorks News and Stories
|Best Paper Award Honorable Mention from IEEE Robotics and Automation Letters (RAL)
|Best Paper Award in Robot Vision at International Conference on Robotics and Automation (ICRA)
|MIT News Spotlight: Spotting objects amid clutter
|Tsinghua Principal Scholarship (Tsinghua News Spotlight)