Lin An

PhD Candidate in Algorithms, Combinatorics, and Optimization (ACO)
Tepper School of Business
Carnegie Mellon University
linan@andrew.cmu.edu

Biography

I am currently a fourth year PhD candidate in the interdisciplinary Algorithms, Combinatorics, and Optimization (ACO) doctoral program at the Tepper School of Business, Carnegie Mellon University. I am fortunate to be advised by Prof. Andrew A. Li and Prof. Benjamin Moseley.

My research focuses on leveraging AI to enhance decision-making processes, particularly through the integration of optimization and machine learning techniques. I explore a range of models, including stochastic, online, and prediction-based frameworks, aimed at addressing key challenges in operations management. My primary areas of application include resource allocation, recommendation systems, and inventory management, where I seek to develop innovative solutions that improve efficiency and performance in dynamic, data-driven environments.

Before coming to CMU, I earned my Masters's degree in Operations Research from Columbia IEOR in 2021, where I worked with Prof. Yuri Faenza. I obtained my Bachelor's degree in Math with a minor in Economics from Boston College in 2020.

Awards and Honors

Conference Proceedings

  1. Timeliness Through Telephones: Approximating Information Freshness in Vector Clock Models.
        Da Qi Chen, Lin An, Aidin Niaparast, R. Ravi, and Oleksandr Rudenko. 2022.
       ACM-SIAM Symposium on Discrete Algorithms (SODA 2023).

Journal Articles

  1. The Nonstationary Newsvendor with (and without) Predictions.
       Lin An, Andrew A. Li, Benjamin Moseley, and R. Ravi. 2023.
       Minor revision, Manufacturing & Service Operations Management (M&SOM).

Preprints under Review/Works in Preparation

  1. Generating Recommendations Optimally.
        Lin An, Andrew A. Li, and Gabriel Visotsky. 2024.
       In Preparation.

  2. Best of Many in Both Worlds: Online Resource Allocation with Predictions under Unknown Arrival Model.
        Lin An, Andrew A. Li, Benjamin Moseley, and Gabriel Visotsky. 2024.
       Submitted.
        A preliminary version appeared in the refereed venue of the 2024 Informs Optimization Society Conference (IOS 2024).

Teaching

  • Mathematical Models for Consulting (Undergraduate). Instructor, 2024 Fall, Carnegie Mellon University.
  • Operations Strategy (MBA). Teaching Assistant, 2023 Fall, Carnegie Mellon University.
  • Optimization (Undergraduate). Teaching Assistant, 2023 Fall, Carnegie Mellon University.
  • Advanced Graph Theory (PhD). Teaching Assistant, 2022 Fall, Carnegie Mellon University.

Invited Talks

  • Online Resource Allocation with Predictions
    INFORMS Annual Meeting, October 2024.
    NYU Stern MOILS Seminar, September 2024.
    INFORMS Revenue Management and Pricing Section (RM&P) Coference, July 2024.
    M&SOM Coference, July 2024.
    INFORMS Optimization Society (IOS) Coference, April 2024.
    INFORMS Annual Meeting, October 2023.

  • The Nonstationary Newsvendor with (and without) Predictions
    INFORMS Annual Meeting, October 2022.

Service

Personal

  • I like playing poker (all kinds, mainly Texas hold 'em). Here and here are my WSOP Player Profiles. Here is my Hendon Mob Profile. Here are some photos of me playing poker at WSOP and at CMU (where I eliminate Xuan Liu to get this nice photo). It would be nice to win a bracelet someday!

    Update: I won a WSOP Circuit Ring on August 02, 2024.

  • I am a big fan of Tottenham Hotspur, a soccer team in the English Premier League. We have a Pittsburgh Spurs Supporters' Club, where we go to a bar and watch games together on matchdays (if we win, we take a photo). If you would like to join, contact me!
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