Research

Lossless Compression of Deep Neural Networks

CPAIOR 2020
With Abhinav Kumas and Srikumar Ramalingam
[Preprint]

Empirical Bounds on Linear Regions of Deep Rectifier Networks

AAAI 2020
With Srikumar Ramalingam
[Poster at MIFODS 2019][Preprint]

Bounding and Counting Linear Regions of Deep Neural Networks

ICML 2018
With Christian Tjandraatmadja and Srikumar Ramalingam
Princeton Day of Optimization 2018 Best Poster Award
[Poster at MIP 2018][Talk at INFORMS 2018][Preprint]

How Could Polyhedral Theory Harness Deep Learning?

SciML 2018 workshop, US Department of Energy (position paper)
With Christian Tjandraatmadja and Srikumar Ramalingam
[Preprint]

Template-based Minor Embedding for Adiabatic Quantum Optimization

Under review
With Teng Huang, Arvind Raghunathan, and David Bergman
[Preprint]

Seamless Multimodal Transportation Scheduling

Under review
With Arvind Raghunathan, David Bergman, John Hooker, and Shingo Kobori
[Preprint]

Last-Mile Scheduling Under Uncertainty

CPAIOR 2019
With Arvind Raghunathan, David Bergman, John Hooker, and Shingo Kobori
[Proceedings]

The Integrated Last-Mile Transportation Problem (ILMTP)

ICAPS 2018
With Arvind Raghunathan, David Bergman, John Hooker, and Shingo Kobori
[Proceedings]

The Offshore Resources Scheduling Problem: Detailing a Constraint Programming Approach

CP 2012
With Gilberto Nishioka and Fernando Marcellino
[Preprint]

When Lift-and-Project Cuts are Different

INFORMS Journal on Computing (to appear)
With Egon Balas
[Preprint]

Reformulating the Disjunctive Cut Generating Linear Program

Under review
(Single author)
Winner of the INFORMS 2016 Poster Competition
[Poster at MIP 2016] [Talk at Northeastern University]

Compact Representation of Near-Optimal Integer Programming Solutions

Mathematical Programming (to appear)
With John Hooker
[Talk at MOPTA 2016][Preprint]

Enumerative Branching With Less Repetition

CPAIOR 2020
(Single author)
[Poster at MIP 2017]