Updates

Summer 2021

I will be one of the speakers of the next MIP Workshop.

Spring 2021

I will return to the UCLA Institute for Pure and Applied Mathematics for the Deep Learning and Combinatorial Optimization workshop.

Fall 2020

I am organizing a session on “Machine Learning and Discrete Optimization” at INFORMS 2020.

I gave a tutorial with Thibaut Vidal on combinatorial optimization and machine learning at the 2020 Brazilian Symposium on Operations Research (SBPO in Portuguese). The slides for my part of the tutorial are here.

Summer 2020

I am chairing the INFORMS Undergraduate Operations Research Prize.

My paper with Abhinav Kumar and Srikumar Ramalingam on lossless compression of neural networks will be published at CPAIOR 2020. This paper will also be presented at the LXAI Workshop at ICML 2020.

My paper on enumerative branching with less repetition has also been accepted at CPAIOR 2020.

I launched the MIPLIBing project with Ryan J. O’Neil.

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Spring 2020

I am a track chair of the INFORMS Optimization Society Conference 2020 (postponed due to the pandemic).

My paper with Srikumar Ramalingam on empirical bounds on linear regions was published at AAAI-20. This paper was also presented in January at ISAIM 2020. I wrote a motivating blog post about the relationship between neural networks and piecewise linear functions.

I gave a talk at the Google office in New York City.

Fall 2019

I joined Bucknell University as assistant professor of business analytics.

I am serving in the program committee of AAAI-20 and LION 14 (Automatic Solver Configuration session).

My paper with Egon Balas on irregular lift-and-project cuts has been accepted at the INFORMS Journal on Computing.

I organized a session on “Machine Learning and Discrete Optimization” at INFORMS 2019. I was also a speaker of the Academic Job Market Search Panel. John Angelis wrote a post about the panel for the official conference blog.

Summer 2019

In August, I was one of the featured speakers of the 2019 YinzOR Student Conference at Carnegie Mellon University. There is a follow-up piece at CMU Tepper’s website.

I visited Brazil in July, and I gave a talk at my alma matter Unicamp.

Spring 2019

A preprint of my current work with Abhinav Kumar and Srikumar Ramalingam on exact and approximate transformations of neural networks is now on arxiv.

My paper with John Hooker on decision diagrams of near-optimal solutions was accepted at Mathematical Programming.

A paper with collaborators at MERL on scheduling uncertain passengers on shared last-mile transportation has been accepted at CPAIOR 2019.

I was one of the invited speakers for the Deep Geometric Learning of Big Data and Applications workshop at the UCLA Institute for Pure and Applied Mathematics. You can find video and slides online.

I coauthored a piece on student volunteering at the April issue of ORMS Today.

I attended the 2019 NSF CISE CAREER workshop in DC.

I gave a talk at Brown University.

I gave a talk at the University of Massachusetts Amherst and and interview to their INFORMS student chapter:

I presented a poster on approximating the number of linear regions of neural networks at the deep learning workshop of the MIT Institute for Foundations of Data Science

Fall 2018

A preprint of new work with Srikumar Ramalingam on approximating the number of linear regions of neural networks is on arxiv.

In December, I gave talks at Bucknell and RPI.

I organized a session on “Machine Learning and Discrete Optimization” at INFORMS 2018, where I talked about linear regions of neural networks. Zulqarnain Haider wrote a neat summary about it for the official blog of the conference.

The INFORMS Student Chapter at Carnegie Mellon won the 2018 Student Chapter Award at the Magna Cum Laude level.

In October, I gave talks at Colby College and The University of Utah.

I won the Best Poster Award at the Princeton Day of Optimization.

A preprint of my work with Egon Balas on irregular lift-and-project cuts is now available on arxiv.

Summer 2018

The bounding and counting paper has been accepted at ICML 2018.

I presented a poster on the bounding and counting paper at the MIP 2018 workshop and at the IFDS Fundamentals of Data Analysis summer school in Madison.

I am back to Mitsubishi Electric Research Labs as a visiting research scientist.

A preprint of work with MERL collaborators on using decision diagrams and branch-and-price for scheduling last-mile passenger transportation is now on arxiv.

I joined the committee of the INFORMS Undergraduate Operations Research Prize.

Spring 2018

My PhD thesis won The Gerald L. Thompson Doctoral Dissertation Award in Management Science at CMU’s 2018 commencement – MERL also ran a story about it

Updates on the bounding and counting paper:

• The paper has been used as a reference in deep learning courses at Waterloo, Texas A&M, and National Taiwan University this semester.
• I gave talks about it at the Brookhaven National Laboratory and at the Process Systems Engineering group at Carnegie Mellon.

A paper with collaborators at MERL on warm start for scheduling last-mile passenger transportation has been accepted at ICAPS 2018.

Participated in the DoE Scientific Machine Learning workshop with a position paper on deep learning and polyhedral theory.

I organized the session “New Paradigms for Cut Generation” at the INFORMS Optimization Society Conference, where I gave a talk on irregular lift-and-project cuts.

Fall 2017

The bounding and counting paper, my first collaboration with Christian Tjandraatmadja and Srikumar Ramalingam on deep learning theory, is now on arxiv.

The INFORMS Student Chapter at Carnegie Mellon won the 2017 Student Chapter Award at the Magna Cum Laude level.

I organized the session “Decision Diagrams for Optimization” at INFORMS 2017, where I gave a talk on postoptimality with decision diagrams.

A preprint of my work with John Hooker on decision diagrams of near-optimal solutions is now available at Optimization Online.

I was nominated to attend the INFORMS 2017 Teaching Effectiveness Colloquium.

Summer 2017

I gave a talk at Northeastern University.

I am back in Boston to work at Mitsubishi Electric Research Labs with Arvind Raghunathan.

I presented a poster on branching with decision diagrams at NemFest and MIP 2017.

Spring 2017

I attended the first INFORMS Student Leadership Conference.

I organized the session “New Paradigms for Cut Generation” at the INFORMS Computing Society Conference, where I gave a talk on regularity of lift-and-project cuts.

Fall 2016

I won the Poster Competition at the 2016 INFORMS Annual Meeting for my work on reverse polar lift-and-project cuts.

I won the INFORMS Judith Liebman Award for outstanding student chapter service.

The INFORMS Student Chapter at Carnegie Mellon won the 2016 Student Chapter Award at the Summa Cum Laude level.

I gave a talk on branching with decision diagrams at INFORMS 2016.

I was featured in October’s “What’s Your StORy” of ORMS Today magazine.

I was nominated to attend the INFORMS 2016 Teaching Effectiveness Colloquium

Summer 2016

I interned at Mitsubishi Electric Research Labs with Arvind Raghunathan.

I gave a talk on decision diagrams of near-optimal solutions at MOPTA 2016.

I presented a poster on reverse polar lift-and-project cuts at MIP 2016.

Spring 2016

I organized the session “New Paradigms for Cut Generation” at the INFORMS Optimization Society Conference, where I gave a talk on reverse polar lift-and-project cuts.

Fall 2015

I was listed among the top Twitter mentions at INFORMS 2015 according to ORMS Today.

I gave a talk on decision diagrams of near-optimal solutions at INFORMS 2015

I was nominated to attend the INFORMS 2015 Doctoral Student Colloquium.

I attended the Purdue CIBER Doctoral Consortium.

Summer 2015

I curated the official Twitter account for ISMP 2015.

Fall 2014

I am Deeply honored to be in the acknowledgements of the new Integer Programming book.

I was mentioned in the IFORS newsletter story about INFORMS 2014.

I was mentioned in a story at America.gov about studying in the US.