Minseok Ryu | Power Systems Computation | Best Researcher Award

Posted on by ScienceFather

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

PHD at the University of Michigan, United States

Minseok Ryu is an Assistant Professor at Arizona State University’s School of Computing and Augmented Intelligence. He earned his Ph.D. in Industrial and Operations Engineering from the University of Michigan in 2020. Prior to his current role, he held a postdoctoral position at Argonne National Laboratory and conducted research at Los Alamos National Laboratory. Ryu’s expertise spans privacy-preserving federated learning, optimization, and power system resilience. He has secured significant funding, including from DOE-ASCR and NSF, and developed the open-source APPFL package for federated learning. Ryu is actively involved in professional societies like INFORMS and IEEE, contributing to conferences and serving as a panelist for NSF reviews.

Professional Profiles

Education

Ph.D. Industrial and Operations Engineering, University of Michigan, Ann Arbor, MI; May 2020 M.S. Aerospace Engineering, KAIST, Daejeon, Korea; Feb 2014 B.S. Aerospace Engineering, KAIST, Daejeon, Korea; Feb 2012

Work Experience

Assistant Professor, School of Computing and Augmented Intelligence, Arizona State University, Tempe, AZ Aug 2023–present Postdoctoral Appointee, Mathematics and Computer Science Division, Argonne National Laboratory, Lemont, IL Aug 2020–Jul 2023 Research Assistant, Applied Mathematics and Plasma Physics Group, Los Alamos National Laboratory, Los Alamos, NM May 2019–Aug 2019 Post Baccalaureate Research Fellow, Kellog School of Management, Northwestern University, Evanston, IL Nov 2014–Apr 201

Honors & Awards

2024 Alliance Fellow, Mayo Clinic and ASU Alliance for Health Care 2023 Highlighted Research, Department of Energy, Advanced Scientific Computing Research (DOE-ASCR) 2022 Highlighted Research, DOE-ASCR

Professional Activities

Membership in Professional Societies: INFORMS, IEEE, IISE, SIAM Proposal Review: Panelist for National Science Foundation (NSF) Journal/Conference Review: Numerous journals and conferences including IEEE Transactions on Power Systems, Management Science, and others.

Research Focus

Minseok Ryu’s research primarily focuses on advanced optimization techniques and privacy-preserving federated learning systems. His work spans several key areas including privacy-preserving distributed control in power systems, data-driven distributionally robust optimization for scheduling, and mitigating uncertain disturbances in electric grids. Ryu has also contributed significantly to the development of algorithms for differentially private federated learning, enhancing security and robustness in biomedical research and heterogeneous computing environments. His expertise extends to heuristic algorithms for geomagnetically induced current blocking devices, showcasing a deep commitment to advancing resilient infrastructure and secure data handling in complex operational environments.

Publications

  1. A GPU-based Distributed Algorithm for Linearized Optimal Power Flow in Distribution Systems, Publication date: 2023.
  2. Enabling End-to-End Secure Federated Learning in Biomedical Research on Heterogeneous Computing Environments with APPFLx (preprint), Publication date: 2023.
  3. Efficient Heuristic Approaches to Binary Optimization: a Sensor Placement Application, Publication date: 2023.
  4. APPFLX: Providing privacy-preserving cross-silo federated learning as a service, Publication date: 2023.
  5. Heuristic Algorithms for Placing Geomagnetically Induced Current Blocking Devices, Publication date: 2023.
  6. Enabling End-to-End Secure Federated Learning in Biomedical Research on Heterogeneous Computing Environments with APPFLx, Publication date: 2022.
  7. APPFL: Open-Source Software Framework for Privacy-Preserving Federated Learning, Publication date: 2022.
  8. A Privacy-Preserving Distributed Control of Optimal Power Flow, Publication date: 2022.
  9. Differentially private federated learning via inexact ADMM with multiple local updates, Publication date: 2022.
  10. Mitigating the Impacts of Uncertain Geomagnetic Disturbances on Electric Grids: A Distributionally Robust Optimization Approach,  Publication date: 2022.
.

Sajjad Ali | Computational Methods | Best Researcher Award

Posted on by ScienceFather

Dr. Sajjad Ali | Computational Methods | Best Researcher Award

PHD at Abdul Wali Khan University Mardan, Pakistan

Dr. Sajjad Ali is a Lecturer in Mathematics at Shaheed Benazir Bhutto University Sheringal, Dir (Upper), Pakistan. He received his Ph.D. in Mathematics from Abdul Wali Khan University Mardan in 2019. With over a decade of teaching experience, Dr. Ali specializes in Bio-Mathematics, Fractional Differential Equations, and Advanced Homotopy Methods. He supervises M.Phil and Ph.D. students and is involved in departmental administration. His research interests include mathematical modeling and computational methods. Dr. Ali is proficient in MATLAB, MS Office, Excel, and LaTeX, and he is fluent in Urdu, English, Pashto, and Khohar.

Professional Profiles

Education

Ph.D. in Mathematics (2015 – 2019) Abdul Wali Khan University Mardan, Khyber Pakhtunkhwa, Pakistan M.Phil in Mathematics (2009 – 2012) Abdul Wali Khan University Mardan, Khyber Pakhtunkhwa, Pakistan Bachelor of Education (B.Ed) (2007 – 2008) Allama Iqbal Open University, Islamabad, Pakistan Master of Science in Mathematics (2005 – 2007) University of Malakand Chakdara, Khyber Pakhtunkhwa, Pakistan Bachelor of Science in Mathematics (2002 – 2004) Government Degree College Tangi, Charsadda, Khyber Pakhtunkhwa, Pakistan F.Sc. Pre-Engineering (2000 – 2002) Government Degree College Tangi, Charsadda, Khyber Pakhtunkhwa, Pakistan Metric in Science (1999 – 2000) Government School No.2 Tangi, Charsadda, Khyber Pakhtunkhwa, Pakistan.

Skills

Research in Mathematics Teaching and Administrative Skills Software MATLAB MS Office Excel LaTeX

Work History

Shaheed Benazir Bhutto University Sheringal, Dir (Upper), Pakistan Lecturer in Mathematics (2011 – Present) Teaching Ph.D./M.Phil courses in Bio-Mathematics, Fractional Differential Equations, and Advanced Homotopy Methods Teaching BS courses in Partial Differential Equations and Ordinary Differential Equations Supervising M.Phil and Ph.D. research students M.Phil/Ph.D. Coordinator in the Department of Mathematics Member of the Departmental Admission Committee Warden of Ihsan Boys Hostel Tameer e Seerat Degree College, Mardan Campus, Pakistan Lecturer in Mathematics (2010 – 2011) Taught graduate-level Mathematics Hostel Warden Farabi Degree College, Peshawar, Pakistan Lecturer in Mathematics (2009 – 2010) Taught graduate-level Mathematics Government Degree College, Tangi, Charsadda, Pakistan Lecturer in Mathematics (2007 – 2009) Taught graduate-level Mathematics

Interests

Mathematical modeling, Computational methods

Awards

Top Position Holder in Master of Mathematics at University of Malakand (2007) Awardee as Lecturer in Mathematics through the Higher Education Commission Pakistan (2008)

Research Focuse

Dr. Sajjad Ali’s research focuses on the numerical treatment and computational solutions of fractional order differential equations, with applications in reaction-diffusion systems, biological population models, and ion-acoustic waves. His work includes developing iterative and stable methods for solving boundary value problems of nonlinear fractional differential equations. Dr. Ali has collaborated extensively with international researchers, contributing to journals such as Chaos, Solitons & Fractals and the Journal of Advanced Research. His studies also explore the stability analysis and exact solutions of complex mathematical models, emphasizing fractional calculus and its applications in various scientific and engineering problems.

Publications

  1. Nonlinear coupling of upper-hybrid waves with lower-hybrid waves in a degenerate dense plasma, Publication date: 2021.
  2. Unstable mode of ion-acoustic waves with two temperature q-nonextensive distributed electrons, Publication date: 2021.
  3. Computation of solution to fractional order partial reaction diffusion equations, Publication date: 2020.
  4. On stable iterative solutions for a class of boundary value problem of nonlinear fractional order differential equations, Publication date: 2019.
  5. Computation of iterative solutions along with stability analysis to a coupled system of fractional order differential equations, Publication date: 2019.
  6. Approximate solutions to nonlinear fractional order partial differential equations arising in ion-acoustic waves, Publication date: 2019.
  7. Stable monotone iterative solutions to a class of bound-ary value problems of nonlinear fractional order differential equations, Publication date: 2019.
  8. Monotone iterative technique and Ulam-Hyers stability analysis for nonlinear fractional order differential equations with integral boundary value conditions, Publication date: 2019.
  9. Optimum solutions of space fractional order diffusion equation, Publication date: 2018.
  10. On Approximate solutions of fractional Order partial differential equations, Publication date: 2018.
.