About Me

Geunyeong Byeon is an Assistant Professor in the School of Computing and Augmented Intelligence at Arizona State University. Previously, she worked as a postdoctoral appointee in the Mathematics and Computer Science Division at Argonne National Laboratory for six months and spent a summer as a graduate research assistant at the Center for Nonlinear Studies at Los Alamos National Laboratory.

Research: Geunyeong Byeon's research interests are in optimization for supporting decision-making in large, interdependent systems. Her studies explore methodologies and computational aspects of large-scale optimization and apply them to challenging applications in energy systems. 

Of Recent Interest

• Two-Stage distributionally robust optimization over wasserstein balls

• Distribution system modeling

• Benders decomposition

• Federated algorithms

Teaching: Geunyeong Byeon has been involved in teaching many undergraduate and graduate classes in operations research, including linear and nonlinear optimization, continuous optimization methods, convex programming, queuing systems, and introductory operations research 

Of Recent Interest

• Optimization I (Fall 2022/23/24)

• Computing for Data-Driven Optimization (Fall 2021; Fall 2023; Spring and Fall 2024; Spring 2025)

• Probability and Statistics for Engineering Problem Solving (Spring 2021)

Service: Geunyeong Byeon was a reviewer of INFORMS Journal on Computing, Management Science, Annals of Operations Research, Journal of Global Optimization, IEEE Transactions on Power Systems, IEEE Transactions on Smart Grids, IEEE Transactions on Automation Science and Engineering, Power Systems Computation Conference, IEEE International Conference on Automation Science and Engineering