"Going Beyond Black Box Models by Leveraging Behavioral Insights: an Intent-Based Recommendation Framework."
Boston University Questrom School of Business. May 2025 (scheduled).
CMU Tepper School of Business. Apr 2025 (scheduled).
19th Annual Bass FORMS Conference. Mar 2025 (scheduled).
Stanford GSB Quant Marketing WIP Seminar. Feb 2025 (scheduled).
Macau International Conference on Business Intelligence and Analytics. Dec 2024.
2024 Yale AIML Conference. Dec 2024.
UC Davis Graduate School of Management. Dec 2024.
Stanford GSB Faculty AI Research Flash Talk. Nov 2024.
Summer Workshop on AI for Business (SWAIB), Shanghai, China. July 2024.
ISMS Marketing Science Conference 2024, Sydney, Australia. June 2024.
“Recommending for a Multi-Sided Marketplace: A Multi-Objective Hierarchical Approach.”
UCLA Anderson School of Management (Marketing Camp). May 2024.
Columbia Business School. Mar 2024.
UC Berkeley Haas School of Business. Mar 2024.
University of Arizona Wieland Speaker Series. Feb 2024.
Warrington College of Business, University of Florida. Jan 2024.
Peking University Guanghua School of Management. Dec 2023.
UChicago Booth Marketing Seminar. Nov 2023.
USC Marshall Statistics Seminar. Nov 2023.
AIBA Workshop, Temple University (virtual). Oct 2023.
Reading Group Sequence on Interference & Marketplace, Stanford GSB. Sept 2023.
KDD 2023 “AI for Open Society” Day Invited Talk. Aug 2023.
SICS, Haas School of Business, UC Berkeley. June 2023.
School of Business, University of California, Riverside. Feb 2023.
Coupang, Inc. May 2023.
Stern School of Business, New York University. Nov 2022.
The Wharton School, University of Pennsylvania. Nov 2022.
Stanford Graduate School of Business. Nov 2022.
Kellogg School of Management, Northwestern University. Oct 2022.
2022 INFORMS Annual Meeting. October 2022.
Conference on Information Systems and Technology (CIST) 2022 (Best Paper Award).
SC Johnson College of Business, Cornell University (virtual). Oct 2022.
Naveen Jindal School of Management, UT Dallas. Oct 2022.
16th ACM Conference on Recommender Systems (Recsys 2022). Sept 2022.
HKUST Business school (virtual), Sept 2022.
CUHK Business school (virtual), Sept 2022.
ISMS Marketing Science Conference 2022 (virtual). June 2022.
“Surrogate for Long-Term User Experience in Recommender Systems.”
Netflix Research Seminar Talk. Oct 2023.
DataFun Summit 2023 (virtual). August 2023.
Bay Area Machine Learning Symposium (BayLearn) 2022. October 2022.
Google Search Tech Talk. September 2022.
28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. August 2022.
Google Research Brain Dump. February 2022.
Google Research Conference 2021. October 2021.
Google Research Reinforcement Learning Workshop. July 2021.
“Can Small Heads Help? Understanding and Improving Multi-Task Generalization.”
Snap Inc Tech Talks. November 2022.
ACM The Web Conference 2022. April 2022.
“User Intent Modeling in Recommender Systems.”
CONSEQUENCES+REVEAL '22: Causality, Counterfactuals, Sequential Decision-Making & Reinforcement Learning,16th ACM Conference on Recommender Systems (Recsys 2022 Workshop). September 2022 (Invited Speaker and Panelist).
“Understanding and Improving Fairness-Accuracy Trade-offs in Multi-Task Learning.”
Mays Business School, Texas A&M University. July 2022.
ISMS Marketing Science Conference 2022 (virtual). June 2022.
Bay Area Machine Learning Symposium (BayLearn) 2021. October 2021.
27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. August 2021.
Faire Wholesale, Inc. July 2021.
“Food Discovery with Uber Eats: Recommending for the Marketplace.”
SigOpt. August 2019.
Facebook Research. June 2019.
Airbnb. June 2019.
“Uber Eats Restaurant Ranking and Recommendation.”
Moving the World with Data Meetup. San Francisco, CA, October 2018.
AI Applications @ Uber Eats Meetup. San Francisco, CA, October 2017.
“Robust Approximate Lasso for High-Dimensional Regression.”
IBM Thomas J. Watson Research Center. February 2016.
Yale University. September 2015.
2015 Joint Statistical Meetings (JSM), August 2015.
NSF Workshop for Empr Process and Mod Stat Decision Theory. May 2015.
“Bayesian time series for online query frequency prediction.”
Internet Services & Research Center, Microsoft Research, August 2015.