I’m currently a Research Fellow at the Simons Institute for the Theory of Computing, until May 2018. I am delighted to be a part of two semester-long programs: Bridging Continuous and Discrete Optimization and Real-Time Decision Making. Prior to this, I obtained a doctoral degree in Operations Research from MIT, and was lucky to have Michel Goemans and Patrick Jaillet as my thesis advisors. For my bachelors (and a joint masters), I majored in Computer Science and Engineering (CSE) at IIT Delhi. My research interests are broadly in
- combinatorial, convex and robust optimization with applications in online learning and data-driven decision-making under partial information (here’s a LIDS article about some of this work),
- optimization with applications in pricing and revenue management, inventory routing and machine learning (here’s a Huffington Post article about some of our work on pricing),
- strategic behavior, fairness and “unintended” bias in decisions (a growing list of problems identified in current learning and optimization methods and the data they use)
I can be contacted via email: swatig at alum dot mit dot edu.
List of collaborators: Michel Goemans, Patrick Jaillet, Dimitris Bertsimas, Georgia Perakis, Naveen Garg, Amitabha Tripathi, Martin Demaine, Kristen LeFevre, Atul Prakash, Maxime Cohen, John Silberholz, Iain Dunning, Joel Tay, Jeremy Kalas, Nishita Agarwal, Thulasi J Rangan.
I will join as an assistant professor in the Industrial & Systems Engineering department of Georgia Institute of Technology, starting Fall 2018. I am happy to talk with enthusiastic prospective graduate students interested in Operations Research, Algorithms Combinatorics and Optimization or the Machine Learning PhD programs at Georgia Tech. I can be contacted via email (swatig at alum dot mit dot edu).
11/2017: I am giving a talk about “Learning What Works Best When” at Visa Research, Palo Alto.
11/2017: I am co-organizing an Optimization and Fairness Mini-symposium at the Simons Institute, along with David Williamson! Looking forward to a half-day of exciting talks!
11/2017: How can one explain their research to an average educated person? To meet this challenge, I will give a talk on “Alexa, What Should I Read Next?”, during the Fireside Chats competition at the Simons Institute.
10/2017: I am invited to give a talk at the Workshop on Algorithms and Optimization (January 2018), International Centre for Theoretical Sciences (ICTS), Bangalore.
09/2017: Our paper on “What Works Best When? A Systematic Evaluation of Heuristics for Max-Cut and QUBO” got accepted for publication in the INFORMS Journal on Computing!
08/2017: I will teach a module on the “Growth and Decay of Functions” at the Berkeley Math Circle (a weekly program for around 500 San Francisco area elementary, middle and high school students) in January, based off a BLOSSOMS video we shot earlier at MIT.
07/2017: I have been selected as the Microsoft Research Fellow, for the Real-Time Decision Making program at the Simons Institute!
05/2017: I have successfully defended my thesis titled, Combinatorial Structures in Online and Convex Optimization! I extend a heartfelt thanks to my advisors, committee members, friends and family for their encouragement and support.
01/2017: Our paper on “Newton’s Method for Parametric Submodular Function Minimization” got accepted for IPCO 2017!
12/2016: I am looking forward to attending a short winter course at the Harvard Law School on Internet & Society: The Technologies and Politics of Control, taught by Jonathan Zittrain and Joi Ito!
10/2016: What works best when? A Framework for Systematic Heuristic Evaluation (with John Silberholz, Iain Dunning) received a special recognition by INFORMS Computing Society in 2016 as a part of the student paper competition!
10/2016: An Efficient Algorithm for Dynamic Pricing using a Graphical Representation (with Maxime Cohen, Jeremy Kalas, Georgia Perakis) is a Finalist in the INFORMS Service Science Section student paper award 2016!