Divya Singhvi

Ph.D. Candidate
Operations Research Center
Massachusetts Institute of Technology
1 Amherst St, Cambridge, MA 02142
dsinghvi "at" mit "dot" edu
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I am a fourth-year doctoral candidate at the Operations Research Center at MIT, advised by Professor Georgia Perakis. My research lies at the intersection of machine learning and operations management. Particularly, I have worked on problems related to optimal demand learning, pricing, recommendations and logistics in online and offline retail operations.

During my PhD, I spent a summer as an intern at the Business Analytics and Mathematical Sciences division of the IBM T. J. Watson Research Center . Prior to joining MIT, I finished my undergraduate studies at Cornell University majoring in Operations Research and Engineering and minoring in Applied Mathematics.

My CV can be found here

  • Predicting Bike Usage for New York City's Bike Sharing System (with S Singhvi, P I Frazier, S G Henderson, E O'Mahony, D B Shmoys and D B Woodard), AAAI Workshop: Computational Sustainability. 2015. Final article.
  • Leveraging Comparables for New Product Sales Forecasting (with L Baardman, I Levin and G Perakis), 2018, major revision in Operations Research. preprint.
  • First Delivery Gaps: A Supply Chain Lever to Reduce Product Returns in Online Retail (with M Chaurasia, S Pandey, H S Rathore, G Perakis and Y Spantidakis), 2018, major revision in Manufacturing & Service Operations Management.
  • Sequential Learning of Product Recommendations with Customer Disengagement (with H Bastani, P Harsha and G Perakis), 2018, submitted. preprint.
  • Non Parametric Dynamic Pricing with Limited Price Experimentation (with G Perakis), 2018, soon to be submitted.
Honors and Awards
  • 2018 - First place in POMS Applied Research Challenge
  • 2018 - First place in POMS College of Supply Chain Management Best Student Paper Award
  • 2018 - Finalist in INFORMS Service Science Section Best Student Paper Award
  • 2018 - Honorable mention in MIT Operations Research Center Best Student Paper Competition
  • 2011-2015 - TATA Scholarship for Students from India, Cornell University
  • Less Can be More In Price Experimentation, presented at INFORMS 2016, MSOM 2017, INFORMS 2017, INFORMS 2018, MIT Sloan OM Seminar Series 2018
  • Leveraging Comparables for New Product Sales Forecasting, presented at MSOM 2017. INFORMS 2017, ISB-POMS Workshop 2017, RMP 2018, MSOM Supply Chain Management SIG 2018, INFORMS Data Mining and Decision Analytics Workshop 2018.
  • Sequential Learning of Product Recommendations, presented at INFORMS 2018.
  • Dynamic Pricing with Unknown Latent Class Models, presented at MSOM 2018, INFORMS 2018.