Gonzalo E. Constante‐Flores
Engineering · The Ohio State University
Publications
46
Citations
424
Est. group size
~1
Recurring co-author estimate
Active years
12
Publishing since 2015
This researcher works on optimization and machine learning methods applied to electric power systems, including power flow calculations, microgrid energy management, and fault detection in industrial processes. Recent work focuses on combining physics-based constraints with deep learning and large language models to make optimization and diagnostic tools more reliable and interpretable. The research bridges electrical power engineering, chemical process systems, and data-driven modeling techniques.
Publication output has grown substantially over the last decade, rising from about 1 paper per year in 2017 to a peak of 14 in 2025, with a notably higher average pace (6.2 papers/year) in the most recent five years.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Self-Supervised Learning of Parametric Approximation for Security-Constrained DC-OPF
arXiv (Cornell University) · 2026
- Self-Supervised Learning of Parametric Approximation for Security-Constrained DC-OPF
arXiv (Cornell University) · 2026
- Reinforcement Learning for Airport Thermo-Electrical Microgrid Energy Management with Constraint Enforcement
2026
- FaultExplainer: Leveraging large language models for interpretable fault detection and diagnosis
Computers & Chemical Engineering · 2025
- Conformalized Prediction of Post-Fault Voltage Trajectories Using Pre-Trained and Finetuned Attention-Driven Neural Operators
SSRN Electronic Journal · 2025
- A Quadratically-Constrained Convex Approximation for the AC Optimal Power Flow
arXiv (Cornell University) · 2025
- Conformalized prediction of post-fault voltage trajectories using pre-trained and finetuned attention-driven neural operators
Neural Networks · 2025
- A Quadratically-Constrained Convex Approximation for the AC Optimal Power Flow
Research Square · 2025
- Enforcing Hard Linear Constraints in Deep Learning Models with Decision Rules
arXiv (Cornell University) · 2025
- Physics-informed neural networks with hard linear equality constraints
Computers & Chemical Engineering · 2024
- Diagnosing infeasible optimization problems using large language models
INFOR Information Systems and Operational Research · 2024
- Conformalized Prediction of Post-Fault Voltage Trajectories Using Pre-trained and Finetuned Attention-Driven Neural Operators
arXiv (Cornell University) · 2024
- FaultExplainer: Leveraging Large Language Models for Interpretable Fault Detection and Diagnosis
arXiv (Cornell University) · 2024
- Distributed manufacturing for electrified chemical processes in a microgrid
AIChE Journal · 2023
- Diagnosing Infeasible Optimization Problems Using Large Language Models
arXiv (Cornell University) · 2023
- arXiv (Cornell University)×9
- International series in management science/operations research/International series in operations research & management science×8
- Computers & Chemical Engineering×2
- European Journal of Operational Research×2
- International Journal of Electrical Power & Energy Systems×2
- Vassilis Kekatos
Engineering · Purdue University West Lafayette
- Yufei He
Engineering · The Ohio State University
- Sajjad Abedi
Engineering · Purdue University West Lafayette
- Douglas R. Hale
Engineering · Indiana University
- Nan Gu
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 19, 2026.
Claim or correct this profile