Dr. Chaoyue Zhao

Associate Professor

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Biography

Chaoyue Zhao joined the Industrial & Systems Engineering (ISE) department in fall 2019 as an associate professor. Prior to this appointment, he was the Jim & Lynn Williams Assistant Professor at Oklahoma State University. He obtained his Ph.D. in Industrial Systems Engineering from the University of Florida in 2014 and his B.S. in Information Computing Sciences from Fudan University in 2010. Dr. Zhao's research focuses on data-driven optimization methodologies for strategic operational planning and power systems management. He has developed innovative approaches for effective decision-making under uncertainty, particularly in power system scheduling and optimal power flow. His analytical models advance scalable solution methods that improve the cost-effectiveness of daily power operations and help mitigate risks associated with system disruptions. Dr. Zhao has received multiple grants from prominent federal agencies including the National Science Foundation and the Department of Transportation, and has been recognized with several awards for his contributions to the field, including the Pritsker Doctoral Dissertation Award and the IISE Outstanding Young Investigator Award.

Research Interests

Data-Driven Optimization Stochastic Optimization Robust Optimization Deep Reinforcement Learning Power System Planning Scheduling Resilience Renewable Energy Integration Risk Assessment

Experience

Associate Professor

2019-09-01 — Present

University of Washington • Seattle, WA

Joined the Industrial & Systems Engineering department.

Assistant Professor

— Present

Oklahoma State University • Stillwater, OK

Appointed as Jim & Lynn Williams Assistant Professor.

Awards

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Collaborative Research: Power System Flexibility: Metric, Assessment, Algorithm

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Re-engineering Adaptable Lives of Businesses

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Collaborative Research: Designing Market-based Optimization Tool for Future Work

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Collaborative Research: Enhancing Power System Resilience through Data-Driven Optimization

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Collaborative Research: Data-Driven Risk-Averse Models and Algorithms for Power Generation Scheduling

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Transportation Consortium South-Central States (Tran-SET): Study of the Impacts of Freight Consolidation and Truck Sharing on Freight Mobility

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Data-Driven Optimization for Power Grid Investment and Operation Resilience

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Feasibility Study: Hazardous Material Movement Model for HazMat Transportation in Oklahoma

Courses

IND E 412 Integer Dynamic Programming IND E 512 Introduction to Optimization Models IND E 599 Integer Programming

Requirements for University of Washington

Master Program
Requirements
GPA Requirement
Required:3
TOEFL
Total
Required:80
IELTS
Overall
Required:6.5
Duolingo
Overall Score
Required:105
Overall
Required:105
Prerequisites
Bachelor's degree from a regionally accredited college or university
Application Checklist
  • Online application
  • Transcripts
  • Statement of Purpose
  • Letters of Recommendation
  • Resume/CV
  • English proficiency scores (for international students)
Specialization Notes

Standard Graduate School requirements for University of Washington apply to most departments listed unless specified otherwise by the program.