Yuting Yuan

I am a Visiting Assistant Professor of Mathematics and Data Science at the College of William & Mary.

Curriculum VitaeEmail

My research is focused on service operations and interpretable decision-making. I am particularly interested in integrating mathematical modeling with data science to derive practical decision support tools with solid theoretical foundations.  

I received a Ph.D. in Operations Management at Simon Business School, University of Rochester, under the supervision of Professor Yaron Shaposhnik

Selected Research (Reverse chronological order)

Interpretable Routing in Disaster Response Management

(Previously, "The Impact of the Zero-COVID Policy and its Implication on Scheduling Supply Delivery")

Colin Tang, Yuting Yuan; In Progress, Data

Staff Sharing Under Uncertainty 

Yuting Yuan; Major revision, M&SOM, Draft

I propose a capacity-sharing strategy for service systems with worker shortages, which leads to significant cost-savings compared with a benchmark rule that staffs each unit independently. 

 Waiting-Time Prediction with Invisible Customers

Yoav Kerner, Ricky Roet-Green, Arik Senderovich, Yaron Shaposhnik, Yuting Yuan; Minor revision, M&SOM, Draft

We derive accurate predictions for patients' waiting times in a queue when the system predictor only observes partial queue length. 

Interpretable Prediction Rules for Congestion Risk in Intensive Care Units

Fernanda Bravo, Cynthia Rudin, Yaron Shaposhnik, Yuting Yuan; Stochastic Systems, forthcoming
We apply queueing theory and machine learning (ML) to derive interpretable prediction rules for ICU capacity issues in the short term.

Information Visibility in Omnichannel Queues

Ricky Roet-Green, Yuting Yuan; Draft available at SSRN

We study the impact of the invisible queue in an omnichannel system on throughput and social welfare, where customers strategically decide to join or balk.

Conference Talks

Seminar Talks

Research Yuting Yuan.mp4

A 5-minute video tour of my research (produced in 2021).