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Assist Prof Dr. Minseok Ryu, Power Systems Computation, Best Researcher Award

Assistant Professor at Arizona State University, United States


Dr. Minseok Ryu is an Assistant Professor at the School of Computing and Augmented Intelligence at Arizona State University. He completed his Ph.D. in Industrial and Operations Engineering from the University of Michigan and holds a master’s and bachelor’s degree in Aerospace Engineering from KAIST. His postdoctoral research at Argonne National Laboratory has been recognized by the Department of Energy for its contributions to advanced scientific computing. Dr. Ryu’s research interests lie in developing scalable and privacy-preserving algorithms for complex systems, with a strong emphasis on interdisciplinary collaboration. He has received numerous accolades, including the Alliance Fellowship from Mayo Clinic and ASU and highlighted research recognitions from the DOE-ASCR.

Professional Profile:


Ph.D. in Industrial and Operations Engineering, University of Michigan, Ann Arbor, MI; May 2020

M.S. in Aerospace Engineering, KAIST, Daejeon, Korea; February 2014

B.S. in Aerospace Engineering, KAIST, Daejeon, Korea; February 2012

🏢 Professional Experience:

  • Assistant Professor, School of Computing and Augmented Intelligence, Arizona State University, Tempe, AZ; August 2023 – Present
    • Responsibilities: Leading research initiatives, teaching, and mentoring students. Participating in committee roles and overseeing various academic and administrative duties.
  • Postdoctoral Appointee, Mathematics and Computer Science Division, Argonne National Laboratory, Lemont, IL; August 2020 – July 2023
    • Responsibilities: Conducting advanced research in applied mathematics, computer science, and developing scalable algorithms for various applications.
  • Research Assistant, Applied Mathematics and Plasma Physics Group, Los Alamos National Laboratory, Los Alamos, NM; May 2019 – August 2019
    • Responsibilities: Engaged in research projects focusing on applied mathematics and plasma physics.
  • Post Baccalaureate Research Fellow, Kellogg School of Management, Northwestern University, Evanston, IL; November 2014 – April 2015
    • Responsibilities: Conducted research in operations management and contributed to academic publications.

Honors & Award:

2024 Alliance Fellow, Mayo Clinic and ASU Alliance for Health Care

Highlighted Research, Department of Energy, Advanced Scientific Computing Research (DOE-ASCR) in 2022 and 2023

Rackham Graduate Student Research Grant, University of Michigan, 2016

MICDE Fellowship, University of Michigan, 2015

National Science Foundation Student Award, INFORMS Computing Society, 2015

National Scholarship, Government of Korea, 2010-2013

Department Honor, KAIST, 2010

Best Technical Poster Award, KAIST, 2010

Research Interests:

Dr. Minseok Ryu’s research focuses on the development of scalable algorithms and machine learning models for applications in industrial engineering, operations research, and augmented intelligence. His work encompasses privacy-preserving federated learning, optimization of power systems, and computational methods for enhancing system resilience against extreme threats. He is particularly interested in interdisciplinary collaborations that integrate advanced computational techniques with practical applications in engineering and healthcare.

Top Noted Publication:

Data-Driven Distributionally Robust Appointment Scheduling over Wasserstein Balls

  • Authors: R. Jiang, M. Ryu, G. Xu
  • Published in: arXiv preprint arXiv:1907.03219, 2019
  • Citations: 28

APPFL: Open-Source Software Framework for Privacy-Preserving Federated Learning

  • Authors: M. Ryu, Y. Kim, K. Kim, R. K. Madduri
  • Published in: IEEE International Parallel and Distributed Processing Symposium Workshops, 2022
  • Citations: 19

A Privacy-Preserving Distributed Control of Optimal Power Flow

  • Authors: M. Ryu, K. Kim
  • Published in: IEEE Transactions on Power Systems, 2022, 37(3), 2042-2051
  • Citations: 18

An Extended Formulation of the Convex Recoloring Problem on a Tree

  • Authors: S. Chopra, B. Filipecki, K. Lee, M. Ryu, S. Shim, M. Van Vyve
  • Published in: Mathematical Programming, 2017, 165, 529-548
  • Citations: 18

Nurse Staffing under Absenteeism: A Distributionally Robust Optimization Approach

  • Authors: M. Ryu, R. Jiang
  • Published in: arXiv preprint arXiv:1909.09875, 2019
  • Citations: 14


Minseok Ryu | Power Systems Computation | Best Researcher Award

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