Sophie H. Yu

Sophie H. Yu

Assistant Professor

Operations, Information and Decisions

The Wharton School

I study hidden structure in networks and how to make better decisions in matching markets.

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ABOUT

About myself

I am an assistant professor of Operations, Information and Decisions at the Wharton School of Business. I was a Postdoctoral Scholar under Prof. Itai Ashlagi and Prof. Amin Saberi, at Management Science and Engineering, Stanford University. I received my PhD in Decision Sciences from the Fuqua School of Business at Duke University, under Prof. Jiaming Xu and Prof. Yehua Wei.

My research interests focus on data analysis, algorithm design, and performance evaluation in large-scale networks and stochastic systems. My works draw inspiration from real-world business, engineering, and natural sciences problems that can be modeled into large and complex networks. I have explored a range of topics from the fundamental limits and efficient algorithms on graph matching to online platform policy design with bounded regret and data confidentiality protection.

RESEARCH COLLABORATIONS

Students

Students I’ve worked closely with:

LATEST & NOTEWORTHY

News

Earlier news

THE COMPLETE COLLECTION

Preprint and Publications

CONVERSATIONS & IDEAS

Selected Talks

  • INFORMS Annual Meeting, Nov, 2026

  • Carnegie Mellon University, Operations Seminar, Sep, 2026

  • Allerton Conference, UIUC, Sep, 2026

  • Renmin University of China: Information (Aug); Business and Gaoling AI (June), 2026

  • Tsinghua University, School of Economics and Management, Operations Seminar, June, 2026

  • Mostly OM, Tsinghua University, May, 2026

  • Hong Kong University of Science and Technology, IEDA Seminar, May, 2026

  • The Chinese University of Hong Kong, Operations Management Seminar, May, 2026

  • The University of Hong Kong (HKU), Operations Management Seminar, May, 2026

  • OM in the Wild Workshop, May, 2026

  • Stanford University, Guest lecture, Nov, 2025

  • INFORMS Annual Meeting, Oct, 2025

  • University of Pennsylvania, Theory of Computer Science Seminar, Oct, 2025

  • Allerton Conference, UIUC, Sep, 2025

  • INFORMS Applied Probability Society Conference, Jul, 2025

  • INFORMS Revenue Management and Pricing, Jul, 2025

  • The 57th ACM Symposium on Theory of Computing (STOC), June, 2025

  • Marketplace Innovations Workshop, May, 2025

  • OM in the Wild Workshop, May, 2025

  • University of UT Austin, IEOR Seminar, Jan, 2025

  • University of Toronto, Rotman Young Scholar Seminar, Dec, 2024

  • University of Pennsylvania, Operations Seminar, Dec, 2024

  • INFORMS Annual Meeting, Oct, 2024

  • Institut de Mathématiques de Toulouse (IMT), Online Stochastic Matching, Sep, 2024

  • Stanford University, Rain Seminar, Apr, 2024

  • London School of Business, Operations Management Seminar, Feb, 2024

  • Shanghai Jiao Tong University, Antai College of Economics, Jan, 2024

  • INFORMS Annual Meeting, Oct, 2023

  • INFORMS Applied Probability Society Conference, June, 2023

  • ACM SIGMETRICS, June, 2023

  • The 55th ACM Symposium on Theory of Computing (STOC), June, 2023

  • MIT FODSI Computational Complexity of Statistical Problems Workshop, June, 2023.

  • University of California, Davis, Probability Seminar, May, 2023.

  • Marketplace Innovations Workshop, May, 2023

  • Stanford University, GSB, OIT Seminar, Feb, 2023

  • Columbia University, IEOR Seminar, Feb, 2023

  • Duke University, Department of Computer Science, CS Theory Seminar, Jan, 2023

  • University of Southern California, Marshall, Operations Seminar, Jan, 2023

  • University of Southern California, Marshall, Statistics Seminar, Jan, 2023

  • Northwestern University, Statistics Seminar, Jan, 2023

  • University of Chicago, Booth, Operations Management Seminar, Jan, 2023

  • Northwestern University, Kellogg, Operations Seminar, Dec, 2022

  • Cornell University, Ithaca, ORIE Seminar, Dec, 2022

  • Cornell Tech, ORIE Seminar, Dec, 2022

  • Emory University, Goizueta, ISOM Seminar, Dec, 2022

  • Georgia Institute of Technology, ISyE Seminar, Dec, 2022

  • University of Pennsylvania, Wharton, OID Seminar, Dec, 2022

  • University of Southern California, Viterbi School of Engineering, ISE Seminar, Nov, 2022

  • University of California, Davis, GSM, Business Analytics Seminar, Nov, 2022

  • INFORMS Annual Meeting, Session TB41, Oct, 2022

  • INFORMS Annual Meeting, George Nicholson Student Paper Competition, Oct, 2022

  • Cornell University, ORIE Young Researchers Workshop, Oct, 2022

  • Duke University, Fuqua School of Business, Interdisciplinary Seminar, Jan, 2022

  • University of California, Berkeley, Simons Institute, CCSI Student Seminar, Nov, 2021

  • INFORMS Annual Meetings, Session WC08, Oct, 2021

  • IEEE International Symposium on Information Theory Conference, Jul, 2021

IN THE CLASSROOM

Teaching

  • Instructor, EGRMGMT-580 Decision Modeling (Graduate) at Pratt school of engineering, Duke University, Spring 2022

    (Instructor Rating: 4.82/5.00, Response rate: 18/21, Department mean: 4.38/5.00)

  • Teaching Assistant, PhD BA 915/ STA 715/ MATH 742: Stochastic Models, Duke University, Fall 2022

  • Teaching Assistant, Weekend MBA Decision 611: Decision Models, Duke University, Fall 2022

  • Teaching Assistant, PhD BA 990/ ECE 590: Statistical Inference on Graphs, Duke University, Spring 2022

  • Teaching Assistant, PhD BA 910/Statistics 502: Bayesian Inference, Duke University, Spring 2021

  • Teaching Assistant, MBA Decision 516: Quantitative Business Analysis, Duke University, Fall 2020

  • Teaching Assistant, MBA Decision 521Q: Quantitative Business Analysis, Duke University, Fall 2020

  • Teaching Assistant, MQM Decision 518Q: Applied Probability and Statistics, Duke University, Fall 2019

  • Teaching Assistant, MQM Decision 521Q: Decision Analytics and Modeling, Duke University, Spring 2019

  • Teaching Assistant, Economics 618: Advanced Econometrics, Duke University, Fall 2016

Research illustration

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