Yi-Chun Akchen (formerly Yi-Chun Chen)

I am an Assistant Professor at the UCL School of Management, University College London, since August 2023. My research aims to understand customer choice from a data-driven perspective and provides operational insights using machine learning and optimization techniques.

I received my PhD from the UCLA Anderson School of Management, where I was fortunate to be advised by Professor Velibor Mišić. I received my master’s degree from Stanford University and bachelor’s degree from National Taiwan University.

CV: PDF | Email: yi-chun.akchen@ucl.ac.uk

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Publications

— Journal Papers —

• On Size Substitution and Its Role in Assortment and Inventory Planning
  with Felipe Caro
  Minor revision in M&SOM
  
  • Blog post in UCLA Anderson Review

• Assortment Optimization under the Decision Forest Model
  with Velibor Mišić
  Minor revision in M&SOM
  

• Consider or Choose? The Role and Power of Consideration Sets
  with Dmitry Mitrofanov
  Forthcoming in Management Science
  
  • Finalist, Service Science Best Cluster Paper Competition, INFORMS, 2024.

• Column-Randomized Linear Programs: Performance Guarantees and Applications
  with Velibor Mišić
  Operations Research (2025)
  

• Decision Forest: A Nonparametric Approach to Modeling Irrational Choice
  with Velibor Mišić
  Management Science (2022) [Code]
  • Blog post in Management Science Review
  • Honorable Mention, George Nicholson Student Paper Prize, INFORMS, 2020.
  • 1st Place, Decision Analysis Student Paper Award, INFORMS, 2019.
  • 2nd Place, Jeff McGill Revenue Management and Pricing Student Paper Award, INFORMS, 2019.
  • Finalist, Service Science Best Paper Award, INFORMS, 2019.
  • Spotlight Presentation, 2019 INFORMS Revenue Management and Pricing Conference.

• Deep Reinforcement Learning for Event-Driven Multi-Agent Decision Processes
  with Kunal Menda, Justin Grana, James Bono, Brendan Tracey, Mykel Kochenderfer, David Wolpert
  IEEE Transactions on Intelligent Transportation Systems (2019)

• Learning Discrete Bayesian Networks from Continuous Data
  with Tim Wheeler, Mykel Kochenderfer
  Journal of Artificial Intelligence Research (2017)

— Conference Papers —

• Improving Offline Value-Function Approximations for POMDPs by Reducing Discount Factors
  with Mykel Kochenderfer, Matthijs Spaan
  IEEE/RSJ International Conference on Intelligent Robots and Systems (2018)

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