2023 (In-person)
"From Offline Greedy Algorithms to Online Learning: Theory and Applications", MIT, LIDS Student Conference (plenary talk), Feb 2023
"When Matching Meets Batching: Optimal Multi-stage Algorithms and Applications”, Stanford Management Science and Engineering, Feb 2023.
"When Matching Meets Batching: Optimal Multi-stage Algorithms and Applications”, Northwestern Kellogg School of Management (Operations),Feb 2023.
TBD, Lyft (Rideshare seminar), forthcoming.
2022 (Remote & In-person)
"When Matching Meets Batching: Optimal Multi-stage Algorithms and Applications”, Columbia Graduate School of Business - Decision, Risk, and Operations (DRO), April 2022.
"Optimal Algorithms for Continuous Non-monotone Submodular Maximization",Toyota Technological Institute at Chicago - Machine Learning Seminar, April 2022.
"Bayesian Blackbox Reductions in Mechanism Design", Northwestern-University of Chicago Economic Theory Conference, May 2022.
"A Few Prices More: Revenue Approximation and Batched Prophet Inequality", Workshop on Algorithms and Economics (WALE), June 2022.
"From Offline Greedy Algorithms to Online Learning: Theory and Applications", University of Illinois at Urbana-Champaign, C3.ai DTI Workshop on Data, Learning, and Markets, Oct 2022
"When Matching Meets Batching: Optimal Multi-stage Algorithms and Applications”, Simons Institute at UC Berkeley, Workshop on Structure of Constraints in Sequential Decision Making, Oct 2022
"When Matching Meets Batching: Optimal Multi-stage Algorithms and Applications”, UC Irvine, Computer Science, Nov 2022
2021 (Remote & In-person)
"When Matching Meets Batching: Optimal Multi-stage Algorithms and Applications”, Stanford Graduate School of Business - Operations and Information Technology (OIT), Jan 2021.
"When Matching Meets Batching: Optimal Multi-stage Algorithms and Applications”, University of Hong Kong - Computer Science, Jan 2021.
"Bayesian Blackbox Reductions in Mechanism Design", Guest lecturer in the course "Simplicity and Complexity in Economic Theory", Instructors: Paul Milgrom and Mohammad Akbarpour, Stanford Graduate School of Business - Economics, May 2021.
"Bayesian Blackbox Reductions in Mechanism Design", Workshop in Information and Learning in Decisions and Operations, July 2021.
"Near-Optimal Experimental Design for Networks: Independent Block Randomization", Google Research NYC, Sept 2021.
"Near-Optimal Experimental Design for Networks: Independent Block Randomization", Facebook’s Operations Research Workshop, Sept 2021.
"Fair Dynamic Rationing", prize session for INFORMS AMD Michael H. Rothkopf Junior Researcher Paper Prize, Oct 2021.
"Optimal Algorithms for Continuous Non-monotone Submodular Maximization", Cornell University - Computer Science, Nov 2021.
"When Matching Meets Batching: Optimal Multi-stage Algorithms and Applications", Core Data Science (CDS) seminar at Facebook Research, Nov 2021.
"When Matching Meets Batching: Optimal Multi-stage Algorithms and Applications", London Business School — Management Science & Operations, Nov 2021.
"From Offline Greedy Algorithms to Online Learning: Theory and Applications", Purdue Krannert School of Business — Supply Chain & Operations Management, Nov 2021.
2020 (Remote)
"When Matching Meets Batching: Optimal Multi-stage Algorithms and Applications”, University of Illinois at Urbana-Champaign ISE, Oct 2020.
"When Matching Meets Batching: Optimal Multi-stage Algorithms and Applications”, Duke Fuqua School of Business - Decision Sciences, Oct 2020.
"Bayesian Blackbox Reductions in Mechanism Design”, ACM EC 2020 - Highlights Beyond EC Plenary Session, July 2020.
“Multi-scale Online Learning: Theory and Applications”, MIT Sloan School of Management, May 2020.
“Optimal Algorithms for Continuous Submodular Maximization”, Rutgers University CS, April 2020.
2019
“Optimal Algorithms for Continuous Submodular Maximization”, University of Washington CS, Oct 2019.
“Hierarchical Clustering with Structural Constraints”, Toyota Technological Institute at Chicago (TTIC), Sept 2019.
“Optimal Algorithms for Continuous Submodular Maximization”, Google Research NYC, March 2019.
Markets with Data: Challenges and Solutions", University of California Irvine CS, February 2019.
Markets with Data: Challenges and Solutions", Purdue CS, February 2019.
Markets with Data: Challenges and Solutions", Purdue ECE and IE, February 2019.
“Data, Markets, and Structured Online Learning”, University of Chicago Booth School of Business, February 2019.
“Data, Markets, and Structured Online Learning”, Purdue Krannert School of Management, February 2019.
“Markets with Data: Challenges and Solutions”, Northwestern CS, February 2019.
“Algorithms vs. Mechanisms: Bayesian Blackbox Reductions in Mechanism Design”, Northwestern Kellogg School of Business (MEDS), January 2019.
“Data, Markets, and Structured Online Learning”, NYU Stern School of Business, January 2019.
“Data, Markets, and Structured Online Learning”, University of Minnesota ISyE, January 2019.
“Data, Markets, and Structured Online Learning”, University of Michigan's Ross School of Business, January 2019.
“Data, Markets, and Structured Online Learning”, University of Illinois at Chicago IDS, January 2019.
2018
“Optimal Algorithms for Continuous Submodular Maximization”, Georgia Tech ISyE DOS seminar, November 2018.
“Optimal Algorithms for Continuous Submodular Maximization”, MIT EECS ML seminar, November 2018.
“Optimal Algorithms for Continuous Submodular Maximization”, USC CS theory seminar, November 2018.
“Optimal Algorithms for Continuous Submodular Maximization”, Northwestern EECS, 2018 Junior Theorists Workshop, November 2018.
“Optimal Algorithms for Continuous Submodular and DR-Submodular Maximization”, Yale YINS theory seminar, October 2018.
“Multi-scale Online Learning and its Applications to Online Auctions”, Stanford TOCA-SV, January 2018.
2017
“Bayesian Blackbox Reductions and Combinatorial Bernoulli Factories”, Stanford Theory Seminar, September 2017.
“Bernoulli Factories and Blackbox Reductions in Mechanism Design”, Google Research Labs (NYC), July 2017.
“Mechanism Design For Complex Environments: Online Auctions and Learning”, B-exam talk, Cornell University, June 2017.
“Algorithms vs. Mechanisms : Mechanism Design For Complex Environments”, University at Buffalo, March 2017.
“Bernoulli Factories and Mechanism Design”, Theory Seminar at Cornell University, Feb 2017.
2016
“Online Leaning in Auctions”, Microsoft Research (Redmond), Aug 2016.
“Secretary Problems with Non-Uniform Arrival Order”, University of Washington, July 2016.
“Robustness and Approximation Theory in Online Algorithm Design”, INFORMS International 2016, June 2016.
“Bernoulli Factories and Mechanism Design”, Microsoft Research (Redmond), May 2016.“
“Optimal Auctions vs. Anonymous Pricing” , NYCE 2016: New York Computer Science and Economics Day, January 2016.
2015
“Robustness of Online Algorithms”, Google Research Labs (Mountain-view), Nov 2015.
“Posted Pricing vs Optimal Auction in Single Item Environment”, Microsoft Research (New England), May 2015.