I am an Assistant Professor at the Department of Operations Research and Financial Engineering at Princeton University. I am an associate faculty with Department of Electrical and Computer Engineering, the Center for Statistics and Machine Learning, and the Robotics at Princeton initiative. I am also a fellow at Princeton Whitman college.
My research lies at the interface of mathematical optimization, machine learning, and optimal control. It focuses on data-driven computational tools to make decisions in highly dynamic and uncertain environments.
I gave a talk on Learning for Optimization under Uncertainty at the Mixed-Integer Programming Workshop at the University of Southern California. I really enjoyed it! Thanks to the brilliant organizers for the invitation!
I gave a talk on Learning for Optimization under Uncertainty at the Conference on Information Sciences and Systems at Johns Hopkins University. Thanks to Enrique Mallada and Mahyar Fazlyab for the invitation!
Thrilled to receive the NSF CAREER Award for the project entitled Learning for Real-Time Embedded Optimization!
New preprint Learning Rationality in Potential Games with my student Stefan Clarke, postdoc Gabriele Dragotto, and in collaboration with Jaime Fernandez Fisac.
I gave a talk on Learning for Optimization under Uncertainty at the IPAM Workshop on Artificial Intelligence and Discrete Optimization. Video is available here. Thanks to the organizers, Xavier Bresson, Bistra Dilkina, Andrea Lodi, and Pascal Van Hentenryck for the invitation!
New preprint The Benefit of Uncertainty Coupling in Robust and Adaptive Robust Optimization in collaboration with Liangyuan Na and Dimitris Bertsimas.
New preprint On the (linear) convergence of Generalized Newton Inexact ADMM. Great collaboration with Zach Frangella, Shipu Zhao, Theo Diamandis, and Madeleine Udell.
New preprint Equitable Data-Driven Resource Allocation to Fight the Opioid Epidemic: A Mixed-Integer Optimization Approach, in collaboration with my senior thesis student Joyce Luo (now at MIT ORC).
New preprint End-to-End Learning to Warm-Start for Real-Time Quadratic Optimization, joint with collaborators Georgina Hall, Brandon Amos, and my student Rajiv Sambharya.
I gave a talk on Learning for Fast and Robust Real-Time Optimization at UC Berkeley Mechanical Engineering Seminar. Thanks Francesco Borrelli for the invitation!
I gave a talk on Real-Time Decision-Making for Clean and Resilient Energy Systems at the ISSNAF Franco Strazzabosco Award Symposium. Video here.
I gave a talk on Mean Robust Optimization at the Future of Analytics and Operations Research workshop at the INFORMS Annual Meeting.
I have organized one invited session at the INFORMS Annual Meeting where Irina Wang, Rajiv Sambharya, and Vinit Ranjan gave a talk.
Irina Wang won the INFORMS Computing Society Student Paper Award for our paper Mean Robust Optimization!
Gabriele Dragotto joined our group at ORFE and Jaime Fernandez Fisac group at ECE as a postdoc to work on multi-agent networks.
Stefan Clarke (PhD) and Cole Becker (MSE) joined our group as graduate students.
I have organized two invited sessions at ICCOPT where Irina Wang, Cole Becker, Rajiv Sambharya, and Vinit Ranjan gave a talk.
New preprint Mean Robust Optimization in collaboration with Bart Van Parys and my students Irina Wang and Cole Becker.
Vineet Bansal was featured on the CSML news for his brilliant work on OSQP!
I gave a talk on Real-time decision-making via data-driven optimization at Politecnico di Milano at the DEIB Department Seminar. First time I was there after 10 years! Thanks Maria Prandini for the invitation!
Our proposal for an ORFE Research Software Engineer was selected for funding!
Rajiv Sambharya won the Excellence in Teaching Award from the Princeton Graduate School for his work on ORF307!
Cole Becker won the Princeton SEAS Mueller Prize and the John Ogden Bigelow Jr. Prize in Electrical Engineering.
Joyce Luo won the Sigma Xi Book Award (video at this link).
I gave a talk on Real-time decision-making via data-driven optimization at the Cornell ORIE Seminar. Thanks Andrea Lodi for the invitation!
I gave a talk on Real-time decision-making via data-driven optimization at the NASA JPL Multi-Agent Tech Talks. Thanks Federico Rossi for the invitation!
Our paper Embedded Code Generation with CVXPY was accepted for publication in IEEE Control Systems Letters. It will be presented at IEEE CDC 2022.
I received the Princeton SEAS Innovation Award for the proposal "Learning Task-specific Optimizers for Real-time Autonomous Systems”!
Jaime and I won the Metropolis Project research award for the proposal “Towards Resilient Urban Networks with Differentiable Agent Decision Models”!
Our paper Online mixed-integer optimization in milliseconds was accepted for publication in INFORMS Journal on Computing.
I served in the program committee of the 4th L4DC conference.
Our paper CoCo: Online Mixed-Integer Control via Supervised Learning was accepted for publication in Robotics and Automation Letters!
I gave a talk on Accelerating quadratic optimization with reinforcement learning at the INFORMS Annual Meeting.
Irina Wang and Vinit Ranjan joined our group as graduate students.
I received internal funding from Princeton CSML to support Vineet Bansal, a Research Software Engineer, to work on OSQP.
I received the 250th Anniversary Fund for Innovation for Undergraduate Education for redesigning ORF307.
I gave a talk on Real-time decision-making via data-driven optimization at the Joint Princeton Robotics and Optimization Seminar (video).
Our paper Machine Learning for Real-Time Heart Disease Prediction was accepted for publication in IEEE Journal of Biomedical and Health Informatics.
I started teaching the undergraduate optimization class ORF307.
Rajiv Sambharya joined our group as a graduate student.
Our paper on the OSQP solver won the Best Paper Award for the journal Mathematical Programming Computation!
I served in the program committee of the 3rd L4DC conference.
I gave a talk on Real-time decision-making via data-driven optimization at the Raytheon Technologies Research Center. Thanks Alessandro Pinto for the invitation.
I received the Pierskalla Best Paper Award from the INFORMS Health Applications Society together with the amazing folks of the COVIDAnalytics project!
I started teaching the graduate optimization class ORF522.
I started organizing the Princeton Optimization Seminar.
I joined the ORFE Department at Princeton University!