Artificial Intelligence for Sustainable Energy Systems

Building trustworthy artificial intelligence and digital twins for fault diagnosis, prognostics and health management of next-generation energy systems.

Artificial Intelligence Explainable AI Fault Diagnosis Anomaly Detection Predictive Maintenance PHM Photovoltaics Battery Systems Digital Twins

Edgar Hernando Sepúlveda-Oviedo

Université de Perpignan Via Domitia · University Institute of Technology (IUT) · PROMES-CNRS (UPR 8521)

40+ Scientific outputs
7+ h-index
35+ Peer-review records
3 CNU qualifications
Edgar Hernando Sepúlveda-Oviedo

Associate Professor
Maître de Conférences

Affiliations
UPVD · IUT GIM
PROMES-CNRS (UPR 8521)
CSPG Research Team

Research Areas
Artificial Intelligence
Fault Diagnosis & Prognostics
Renewable Energy Systems
Biomedical Modeling

I am an Associate Professor (Maître de Conférences) in Industrial Engineering and Maintenance at the Université de Perpignan Via Domitia (UPVD) and a researcher at PROMES-CNRS (UPR 8521) within the CSPG research team (Centrales Solaires de Prochaines Générations).

My research focuses on the development of model-based and data-driven approaches for fault diagnosis, prognostics, predictive maintenance, and artificial intelligence applied to complex engineering systems. My work aims to improve the performance, reliability, resilience, and interpretability of industrial and energy systems operating under real-world conditions.

My primary research interests lie in renewable energy systems, including photovoltaic power plants, battery energy storage systems, smart grids, microgrids, digital twins, and intelligent monitoring platforms. In parallel, I have conducted research in biomedical systems modeling, particularly in neonatal and fetal physiology, computational medicine, hybrid systems, and simulation-based medical education.

Academic Path

2010-2015 Mechatronics Engineering, Universidad Nacional de Colombia
2016-2019 Master in Industrial Automation, Universidad Nacional de Colombia
2020–2023 CIFRE PhD, LAAS-CNRS and Feedgy
2023–2024 ATER, INSA Toulouse
2024–2025 Postdoctoral Researcher, LAAS-CNRS
2025–present Associate Professor, UPVD · IUT GIM · PROMES-CNRS

I obtained my PhD from Université Toulouse III – Paul Sabatier and LAAS-CNRS in Toulouse, France. My doctoral work was recognized with the Prix de Thèse 2024 awarded by the École Doctorale GEETS, as well as the Best Oral Presentation Award at the GEETS Doctoral School Conference in 2022.

I am qualified by the French National Council of Universities (CNU) in three disciplinary sections:

Section Field Status
Section 61 Computer Engineering, Automation and Signal Processing Qualified for Maître de Conférences
Section 27 Computer Science Qualified for Maître de Conférences
Section 63 Electrical Engineering, Electronics, Photonics and Systems Qualified for Maître de Conférences

Research Interests

  • Artificial Intelligence and Machine Learning
  • Explainable Artificial Intelligence (XAI)
  • Fault Detection, Isolation and Diagnosis (FDI)
  • Prognostics and Predictive Maintenance
  • Renewable Energy Systems
  • Photovoltaic Power Plants
  • Battery Energy Storage Systems
  • Smart Grids and Microgrids
  • Digital Twins
  • Industrial Automation
  • Biomedical Systems Modeling
  • Neonatal and Fetal Physiological Modeling
  • Instrumentation and Monitoring Systems
  • Embedded Systems
  • Data Analytics and Data Mining
  • Industry 4.0 and Cyber-Physical Systems