Ashwin Venkataraman
Assistant Professor of Operations Management
- Ashwin[dot]Venkataraman[AT]UTDallas[dot]edu
- (972) 883-5944
- JSOM 3.221
About Me
I am an Assistant Professor of Operations Management at the Naveen Jindal School of Management at University of Texas, Dallas. Previously, I was a Postdoctoral Fellow at the Institute for Quantitative Social Science (IQSS) at Harvard University. I graduated from the Courant Institute of Mathematical Sciences at New York University with a Ph.D. in Computer Science, where I was co-advised by Prof. Srikanth Jagabathula and Prof. Lakshminarayanan Subramanian.
Working Papers
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Estimating Large-scale Tree Logit Models
(with Srikanth Jagabathula, Paat Rusmevichientong, and Xinyi Zhao)Major Revision at Operations Research, Aug 2022.
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Nonparametric Demand Estimation in the Presence of Unobserved Factors
(with Sandeep Chitla and Srikanth Jagabathula)Under Review.
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The Generalized Stochastic Preference Choice Model
(with Gerardo Berbeglia) -
Price Optimization under the Featurized Rank-based Model
(with Mohammad Amin Farzaneh and Sajad Modaresi) -
Natural calamities, strikes, festivals, elections, or policies: What events drive food price fluctuations in India?
(with Sunandan Chakraborty, Srikanth Jagabathula, and Lakshminarayan Subramanian) -
An MM Algorithm for Estimating the MNL Model with Product Features
(with Srikanth Jagabathula)
Journal and Conference Papers
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CollectiveTeach: A System To Generate And Sequence Web-Annotated Lesson Plans
(with Rishabh Ranawat and Lakshminarayanan Subramanian)In ACM SIGCAS Conference on Computing and Sustainable Societies (COMPASS '21), pp. 1-13, 2021.
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A Conditional Gradient Approach for Nonparametric Estimation of Mixing Distributions
(with Srikanth Jagabathula and Lakshminarayanan Subramanian)Management Science, 66(8):3635-3656, 2020.
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A Model-based Embedding Technique for Segmenting Customers
(with Srikanth Jagabathula and Lakshminarayanan Subramanian)Operations Research, 66(5):1247-1267, 2018.
Identifying Unreliable and Adversarial Workers in Crowdsourced Labeling Tasks
(with Srikanth Jagabathula and Lakshminarayanan Subramanian)Journal of Machine Learning Research (JMLR), 18(93):1-67, 2017.
Predicting Socio-economic Indicators using News Events
(with Sunandan Chakraborty, Srikanth Jagabathula, and Lakshminarayan Subramanian)Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD '16), pp. 1455-1464, 2016.
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Reputation-based Worker Filtering in Crowdsourcing
(with Srikanth Jagabathula and Lakshminarayanan Subramanian)Advances in Neural Information Processing Systems 27 (NIPS '14), pp. 2492-2500, 2014.
Other Publications
Nonparametric Estimation of Choice Models
(with Srikanth Jagabathula)In X. Chen, S. Jasin, C. Shi (eds) The Elements of Joint Learning and Optimization in Operations Management. Springer Series in Supply Chain Management, vol 18. Springer, Cham., 2022.
Rethinking Customer Segmentation and Demand Learning in the Presence of Sparse, Diverse, and Large-scale Data
Ph.D. Dissertation, Sept 2018.
Data-Driven Probabilistic Framework for Student Learning
(with Rishabh Ranawat, Shiva Iyer, Srikanth Jagabathula, and Lakshminarayan Subramanian)ICML/IJCAI/AAMAS Workshop on AI and Computational Psychology: Theories, Algorithms and Applications (CompPsy), July 2018.
CollectiveTeach: Crowdsourcing Lesson Plans
(with Rishabh Ranawat, Sepehr Vakil, Jay Chen, Srikanth Jagabathula, and Lakshminarayan Subramanian)KDD Workshop on Advancing Education with Data, Aug 2017.
Awards and Honors
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Honorable Mention, INFORMS George B. Dantzig Dissertation Award (2019)Awarded to the best dissertation in any area of OR/MS
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NYU GSAS Dean's Dissertation Fellowship (2017-18)1-year fellowship awarded to 30 Ph.D. students across NYU's Graduate School of Arts and Science (GSAS)
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Jacob T. Schwartz Ph.D. Fellowship (2015)For outstanding performance in the Ph.D. program (1 of 2 students awarded in the computer science department)
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Henry M. MacCracken Fellowship (2012-17)For pursuing graduate studies at NYU