Minseok Ryu | Energy and Sustainability | Best Researcher Award

Assist Prof Dr Minseok Ryu, Arizona State University, United States

Dr. Minseok Ryu is an Assistant Professor at Arizona State University’s School of Computing and Augmented Intelligence since August 2023 👨‍🏫. He earned his Ph.D. in Industrial and Operations Engineering from the University of Michigan in 2020 🎓. His research focuses on optimization and machine learning applications in power systems and privacy-preserving federated learning 🔍⚡. Dr. Ryu has held positions at Argonne National Laboratory and Los Alamos National Laboratory 🏢. He has received numerous awards, including the 2024 Alliance Fellowship at Mayo Clinic and ASU and multiple research highlights from the DOE-ASCR 🌟.

Publication profile

google scholar

Education

Minseok Ryu holds a Ph.D. in Industrial and Operations Engineering from the University of Michigan, Ann Arbor, which he completed in May 2020 🎓. Before that, he earned an M.S. in Aerospace Engineering from KAIST, Daejeon, Korea, in February 2014 🚀. His academic journey began with a B.S. in Aerospace Engineering from KAIST, which he obtained in February 2012 ✈️.

Employment

Minseok Ryu is currently an Assistant Professor at the School of Computing and Augmented Intelligence at Arizona State University in Tempe, AZ (Aug 2023–present) 📚. Previously, he was a Postdoctoral Appointee at the Mathematics and Computer Science Division, Argonne National Laboratory, Lemont, IL (Aug 2020–Jul 2023) 🔬. He also worked as a Research Assistant with the Applied Mathematics and Plasma Physics Group, Los Alamos National Laboratory, Los Alamos, NM (May 2019–Aug 2019) 🧪. Additionally, he served as a Post Baccalaureate Research Fellow at the Kellogg School of Management, Northwestern University, Evanston, IL (Nov 2014–Apr 2015) 🎓.

Honors & Awards

Minseok Ryu has achieved numerous accolades throughout his career. In 2024, he was honored as an Alliance Fellow by the Mayo Clinic and ASU Alliance for Health Care and participated in the Faculty Summer Residency program. His research was highlighted by the Department of Energy’s Advanced Scientific Computing Research (DOE-ASCR) in both 2023 and 2022. Ryu received the Rackham Graduate Student Research Grant in 2016 and multiple fellowships from the University of Michigan in 2015. Additionally, he earned the National Science Foundation Student Award from INFORMS Computing Society. Earlier, he received the National Scholarship from the Korean government (2010-2013) and accolades from KAIST, including the Department Honor and Best Technical Poster Award in 2010. 🎓🔬📊

Presentations

Minseok Ryu has made significant contributions to various fields, presenting his research at numerous esteemed conferences. His work includes heuristic algorithms for geomagnetically induced current blocking devices (Paris, June 2024) 🌍⚡, generating columns (Phoenix, Oct 2023) 📝, and differentially private algorithms for constrained federated learning (Seattle and Amsterdam, 2023) 🔒🤖. He has also focused on privacy-preserving federated learning frameworks (Arlington, Aug 2022; Virtual, June 2022) 🛡️📡. Additionally, he has explored optimal power flow control, transmission expansion planning, and robust optimization in healthcare staffing across various platforms including INFORMS, SIAM, and international symposiums 🌐🧑‍⚕️

Research focus

Minseok Ryu’s research primarily focuses on data-driven optimization and privacy-preserving techniques, particularly in federated learning and power systems. His work spans several areas, including robust optimization under uncertainty, privacy-preserving distributed control, and federated learning frameworks. Key applications include improving nurse staffing models, optimizing electric grids against geomagnetic disturbances, and developing secure frameworks for federated learning in biomedical research. Ryu’s contributions are significant in ensuring privacy and robustness in distributed systems and optimization problems. 🧠🔒💡🔋👩‍⚕️