Research Narrative

I am currently working on "Operations in Distributed Queueing Systems."

Real-world service systems—from airport security to cloud computing—feature time-varying dynamics and distributed queues that are either physically separated (airport terminals, hospital departments) or logically distinct (priority classes, virtual server pools). 

My research develops optimization methods for these complex stochastic systems across three key dimensions: 

1. Server-Side Optimization

   • Constrained Staff Scheduling [5] (IEEE T-ASE 2022):
     We develop physician scheduling models for emergency department (ED) fever clinics that balance COVID-19 safety requirements (social distancing, disinfection) with operational efficiency, where physicians cannot freely switch between COVID and regular units.

   • Server Routing-Scheduling [3] (Transportation Science, 2023):
     Classical policies like the cμ-rule fail when servers must travel between distributed queues (e.g., airport terminals). We propose rollout-based policies that account for stochastic travel times and achieve near-optimal performance. 

2. Customer-Side Optimization

   • Handoff Minimization [6] (Major revision at Management Science):
     Patient handoffs are "the number one contributor to quality and safety problems" in EDs (feedback from a physician). From a system-of-systems perspective, we design implementable patient assignment policies that minimize handoffs while maintaining system throughput.

3. Revenue Optimization

   • Dynamic Pricing [1] (Accepted by Operations Research):
     For multi-class, multi-pool systems, we develop dual-based dynamic pricing policies that are both tractable and asymptotically optimal at scale.

   • Assortment Optimization [7] (Major revision at Operations Research):
     We develop a blind policy in an explicit form to tackle assortment optimization for multi-class reusable resource systems, in which the policy automatically achieves competitive performance bounds.