Sungho Shin
Engineering · Purdue University West Lafayette
Publications
95
Citations
412
Est. group size
~4
Recurring co-author estimate
Active years
22
Publishing since 2005
Sungho Shin works on optimization methods and software for large-scale engineering systems, with a particular focus on power grids, energy infrastructure, and control. Much of the work involves developing GPU-accelerated numerical solvers (such as MadNLP, a nonlinear programming solver) and applying them to problems like optimal power flow, battery storage management, carbon capture process design, and hydrogen supply chains. The research combines mathematical optimization theory with practical software tools intended to speed up computation for complex energy and infrastructure networks.
Publication output grew substantially from a handful of papers in 2017-2019 to a sustained higher rate of roughly 13-17 per year from 2020 onward, though 2025 shows a temporary dip followed by a rebound in 2026.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Design of Carbon Capture Processes Under Part-load Operating Conditions
arXiv (Cornell University) · 2026
- Design of Carbon Capture Processes Under Part-load Operating Conditions
arXiv (Cornell University) · 2026
- GPU-Accelerated Nonlinear Multi-Period AC Optimal Power Flow for Large-Scale Power–Hydrogen Systems
Systems and Control Transactions · 2026
- A MIBLP model for a Northern European negative-emission hydrogen supply chain with CCS in the North Sea
Systems and Control Transactions · 2026
- MadNLP/MadNLP.jl: v0.10.1
Zenodo (CERN European Organization for Nuclear Research) · 2026
- Approximate Dynamic Programming for Degradation-aware Market Participation of Battery Energy Storage Systems: Bridging Market and Degradation Timescales
arXiv (Cornell University) · 2026
- CD-FKD: Cross-Domain Feature Knowledge Distillation for Robust Single-Domain Generalization in Object Detection
arXiv (Cornell University) · 2026
- CD-FKD: Cross-Domain Feature Knowledge Distillation for Robust Single-Domain Generalization in Object Detection
arXiv (Cornell University) · 2026
- MadNLP/MadNLP.jl: v0.9.1
Zenodo (CERN European Organization for Nuclear Research) · 2026
- ExaModelsPower.jl: A GPU-compatible modeling library for nonlinear power system optimization
Electric Power Systems Research · 2026
- An augmented Lagrangian method on GPU for security-constrained AC optimal power flow
Electric Power Systems Research · 2026
- Near-Optimal Performance of Stochastic Model Predictive Control
Mathematics of Operations Research · 2026
- MadNLP/MadNLP.jl: v0.9.0
Zenodo (CERN European Organization for Nuclear Research) · 2026
- Alternative Learning with Semi-Supervised Relaxation for AC Optimal Power Flow
SSRN Electronic Journal · 2026
- Alternative Learning with Semi-Supervised Relaxation for AC Optimal Power Flow
SSRN Electronic Journal · 2026
- arXiv (Cornell University)×43
- Electric Power Systems Research×4
- IFAC-PapersOnLine×3
- SSRN Electronic Journal×3
- Zenodo (CERN European Organization for Nuclear Research)×3
- J. Pearson
Engineering · Purdue University West Lafayette
- Kevin M. Passino
Engineering · The Ohio State University
- Akshay Kudva
Engineering · The Ohio State University
- Joel A. Paulson
Engineering · The Ohio State University
- Linas Mockus
Engineering · Purdue University West Lafayette
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 20, 2026.
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