Scholar
Gonzalo E. Constante Flores
Google Scholar ID: KFCcT3MAAAAJ
Postdoctoral Scholar, Purdue University
Citations & Impact
Citations
465
H-index
10
i10-index
10
Publications
20
Co-authors
0
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- Publications:
- - A Quadratically-Constrained Convex Approximation for the AC Optimal Power Flow, 2025.
- - Physics-informed neural networks with hard linear equality constraints, 2024, Computers & Chemical Engineering.
- - Diagnosing infeasible optimization problems using large language models, 2024, INFOR: Information Systems and Operational Research.
- - Daily scheduling of generating units with natural-gas market constraints, 2024, European Journal of Operational Research.
- - An effective hybrid decomposition approach to solve the network-constrained stochastic unit commitment problem in large-scale power systems, 2024, EURO Journal on Computational Optimization.
- Awards: Finalist for the 2024 IEEE PES PEEC Outstanding Doctoral Dissertation Award.
Research Experience
- Currently a Postdoctoral Researcher at Purdue University, advised by Prof. Can Li. Formerly a PhD student at The Ohio State University.
Education
- PhD in Electrical Engineering from The Ohio State University, 2022, Advisor: Prof. Antonio Conejo; MSc in Electrical Engineering from The Ohio State University; BSc in Electrical Engineering from Escuela Politécnica Nacional.
Background
- Interests: Optimization, Machine Learning, Power Systems. Field: Developing theory, algorithms, and models for large-scale optimization and machine learning with applications in power and energy systems.
Co-authors