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  1. Directory
  2. Faculty
  3. Yash Kanoria

Yash Kanoria

Merrill Lynch Professor of Workforce Transformation
Decision, Risk, and Operations Division
Kanoria, Yash
Contact
Office: 981 Kravis
Phone: (650) 3530476
E-mail: [email protected]
Links
Personal Website
Curriculum Vitae

Yash Kanoria is the Merrill Lynch Professor of Workforce Transformation in the Decision, Risk and Operations division at Columbia Business School. He specializes in the design and optimization of marketplaces including matching markets and online platforms. In the MBA program, he teaches an elective on Digital Marketplaces, and the Business Analytics core class. 

Yash obtained a BTech from IIT Bombay in 2007, a PhD in Electrical Engineering from Stanford in 2012, and spent a year at Microsoft Research New England during 2012-13. He has won several research and practice awards including the MSOM Young Scholar Prize, the Lanchester Prize, the Sigecom Test of Time award, an Amazon best Operations Research paper award, and the NSF Career Award. 

Education
BTech in Electrical Engineering, IIT Bombay, 2007; MS in Electrical Engineering, Stanford, 2009; PhD in Electrical Engineering, Stanford, 2012
Joined CBS
2013

All Activities

  • Research
  • Teaching
  • Achievements
  • Press
  • Authored Works
  • CaseWorks
  • Journal articles
  • Working papers
  • Articles
  • Books
  • Chapters
Journal Article
Kanoria, Yash, Seungki Min, and Pengyu Qian. “The Competition for Partners in Matching Markets.” (June 01, 2025).
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Journal Article
Besbes, Omar, Yash Kanoria, and Akshit Kumar. “Dynamic Resource Allocation: Algorithmic Design Principles and Spectrum of Achievable Performances.” (November 18, 2024).
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Journal Article
Kanoria, Yash, Ilan Lobel, and Jiaqi Lu. “Managing Customer Churn Via Service Mode Control.” (July 28, 2023).
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Journal Article
Kanoria, Yash. “Dynamic Spatial Matching.” (January 01, 2022).
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Journal Article
Kanoria, Yash and Daniela Saban. “Facilitating the Search for Partners on Matching Platforms: Restricting Agent Actions.” (May 19, 2021).
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Journal Article
Arnosti, Nicholas, Ramesh Johari, and Yash Kanoria. “Managing Congestion in Matching Markets.” (January 19, 2021).
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Journal Article
Johari, Ramesh, Vijay Kamble, and Yash Kanoria. “Matching while Learning.” (January 07, 2021).
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Journal Article
Kanoria, Yash and Pengyu Qian. “Blind Dynamic Resource Allocation in Closed Networks via Mirror Backpressure.” (July 13, 2020).
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Journal Article
Feigenbaum, Itai, Yash Kanoria, Irene Lo, and Jay Sethuraman. “Dynamic Matching in School Choice: Efficient Seat Reallocation After Late Cancellations.” (May 08, 2020).
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Journal Article
Kanoria, Yash and Hamid Nazerzadeh. “Incentive-Compatible Learning of Reserve Prices for Repeated Auctions.” (February 24, 2020).
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Journal Article
Ashlagi, Itai , Mark Braverman, Yash Kanoria, and Peng Shi. “Clearing matching markets efficiently: informative signals and match recommendations.” (January 01, 2020).
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Journal Article
Baswana, Surender , Partha Pratim Chakrabarti, Sharat Chandran, Yash Kanoria, and Utkarsh Patange. “Centralized Admissions for Engineering Colleges in India.” (November 12, 2019).
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Journal Article
Kanoria, Yash, Daniela Saban, and Jay Sethuraman. “Convergence of the Core in Assignment Markets.” (June 06, 2018).
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Journal Article
Anderson, Ross , Itai Ashlagi, David Gamarnik, and Yash Kanoria. “Efficient Dynamic Barter Exchange.” (September 14, 2017).
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Journal Article
Ashlagi, Itai, Yash Kanoria, and Jacob D. Leschno. “Unbalanced Random Matching Markets.” (February 01, 2017).
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Journal Article
Ibrahimi, Morteza , Yash Kanoria, Matt Kraning, and Andrea Montanari. “The Set of Solutions of Random XORSAT Formulae.” (October 15, 2015).
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Journal Article
Bayati, Mohsen , Christian Borgs, Jennifer Chayes , Yash Kanoria, and Andrea Montanari. “Bargaining dynamics in exchange networks.” (March 02, 2015).
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Journal Article
Kanoria, Yash and Hamid Nazerzadeh. “Dynamic Reserve Prices for Repeated Auctions: Learning from Bids.” (January 01, 2014).
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Journal Article
Kanoria, Yash and Andrea Montanari. “Optimal Coding for the Binary Deletion Channel With Small Deletion Probability.” (October 01, 2013).
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Journal Article
Kanoria, Yash and Omer Tamuz. “Tractable Bayesian Social Learning on Trees.” (April 01, 2013).
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Journal Article
Kanoria, Yash and Andrea Montanari. “Majority dynamics on trees and the dynamic cavity method.” (October 25, 2011).
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Journal Article
Kanoria, Yash, Andrea Montanari, David Tse, and Baosen Zhang. “Distributed Storage for Intermittent Energy Sources: Control Design and Performance Limits.” (January 01, 2011).
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Journal Article
Ibrahim, Morteza , Adel Javanmard, Yash Kanoria, and Andrea Montanari. “Robust Max-Product Belief Propagation.” (January 01, 2011).
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Journal Article
Kanoria, Yash and Andrea Montanari. “Subexponential convergence for information aggregation on regular trees.” (January 01, 2011).
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Journal Article
Kanoria, Yash. “An FPTAS for Bargaining Networks with Unequal Bargaining Powers.” (January 01, 2010).
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Journal Article
Kanoria, Yash, Subhasish Mitra, and Andrea Montanari. “Statistical Static Timing Analysis using Markov Chain Monte Carlo.” (January 01, 2010).
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Journal Article
Dutta, Chinmoy , Yash Kanoria, D. Manjunath, and Jaikumar Radhakrishnan. “A Tight Lower Bound for Parity in Noisy Communication Networks.” (January 01, 2008).
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Journal Article
Kanoria, Yash and D. Manjunath. “On Distributed Computation in Noisy Random Planar Networks.” (January 01, 2007).
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Working Paper
Besbes, Omar, Yash Kanoria, and Akshit Kumar. Impact of Rankings and Personalized Recommendations in Marketplaces. Forthcoming.
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Working Paper
Allouah, Amine, Omar Besbes, Josue D. Figueroa, Yash Kanoria, and Akshit Kumar. What Is Your AI Agent Buying? Evaluation, Implications and Emerging Questions for Agentic E-Commerce. January 01, 2025.
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Working Paper
Allen Sirolly, , Hongyao Ma, Yash Kanoria, and Rajiv Sethi. Network-Based Detection of Wash Trading. January 01, 2025.
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Working Paper
Alvo, Matias, Yash Kanoria, and Daniel Russo. Neural Inventory Control in Networks via Hindsight Differentiable Policy Optimization. January 01, 2025.
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Working Paper
Kanoria, Yash, Hongyao Ma, and Allen Sirolly. The Impact of Race-Blind and Test-Optional Admissions on Racial Diversity and Merit. January 01, 2024.
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Working Paper
Besbes, Omar, Yash Kanoria, and Akshit Kumar. The Fault in Our Recommendations. January 01, 2024.
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Working Paper
Chen, Yilun , Yash Kanoria, and Akshit Kumar. Feature-Based Dynamic Matching. January 01, 2023.
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Working Paper
Immorlica, Nicole, Yash Kanoria, and Jiaqi Lu. When does competition and costly information acquisition lead to a deadlock? January 01, 2022.
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Working Paper
Lin, Yiheng , Judy Gan, Guannan Qu, Yash Kanoria, and Adam Wierman. Decentralized Online Convex Optimization in Networked Systems. January 01, 2022.
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Working Paper
Banerjee, Siddhartha , Yash Kanoria, and Pengyu Qian. Dynamic Assignment Control of a Closed Queueing Network under Complete Resource Pooling. January 01, 2018.
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  • Courses
  • Case Studies
Course
B8148: The Analytics Advantage
View Course on The Analytics Advantage
Course
B6101: Business Analytics
View Course on Business Analytics
Course
B8159: Digital Marketplaces
View Course on Digital Marketplaces
Course
B5101: Business Analytics
View Course on Business Analytics
  • Awards
  • Grants
  • In the Media
  • Articles
In the Media

New Prediction Market With Crypto Roots Is Making Waves in Asia

Bloomberg News
In the Media

A Step-by-Step Guide to Getting Ready for AI Agents

Business of Fashion
In the Media

A $400,000 Profit on Maduro's Capture Raises Insider Trading Questions on Polymarket

NPR
In the Media

How Prediction Markets Raise Insider Trading and Credit Risks

Cointelegraph
In the Media

Google Will Integrate Kalshi and Polymarket Predictions into Its Finance AI Tools

NBC News
In the Media

Polymarket Volume Inflated by ‘Artificial’ Activity, Study Finds

Bloomberg
In the Media

AI and Agentic Commerce

Forbes
Article

What Happens When AI Does Your Shopping?

Read More about What Happens When AI Does Your Shopping?
  • Articles
  • CaseWorks
Case ID
260202

“Designed to be Deleted”: Hinge as a Digital Dating Marketplace

How should an online dating like Hinge platform design its product, algorithm, and strategy to effectively facilitate meaningful, high-quality connections in a competitive and complex digital market place?

View Case on “Designed to be Deleted”: Hinge as a Digital Dating Marketplace
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