Scholar
Pedro P. Vergara
Google Scholar ID: r-a55GMAAAAJ
Associate Professor - Delft University of Technology
Distribution Networks
Optimal Power Flow
Mathematical Programming
Machine Learning
Reinforcement
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Citations & Impact
All-time
Citations
1,320
H-index
22
i10-index
38
Publications
20
Co-authors
13
list available
Publications
12 items
SAVGO: Learning State-Action Value Geometry with Cosine Similarity for Continuous Control
2026
Cited
0
Learning to Route Electric Trucks Under Operational Uncertainty
2026
Cited
0
Topology-Aware Graph Reinforcement Learning for Energy Storage Systems Optimal Dispatch in Distribution Networks
2026
Cited
0
SmartMeterFM: Unifying Smart Meter Data Generative Tasks Using Flow Matching Models
2026
Cited
0
Quantum-Enhanced Reinforcement Learning for Accelerating Newton-Raphson Convergence with Ising Machines: A Case Study for Power Flow Analysis
2025
Cited
0
Data driven approach towards more efficient Newton-Raphson power flow calculation for distribution grids
2025
Cited
0
Solving Power System Problems using Adiabatic Quantum Computing
2025
Cited
0
Optimizing Electric Vehicles Charging using Large Language Models and Graph Neural Networks
2025
Cited
0
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Co-authors
7 total
Peter Palensky
TU Delft
Phuong H. Nguyen
Eindhoven University of Technology
Bo Nørregaard Jørgensen
Professor, PhD., Head of Center for Energy Informatics, University of Southern Denmark
Matthias Möller
Associate Professor of Numerical Analysis, Delft University of Technology
Tarek Alskaif
Associate Professor of Energy Informatics, Wageningen University & Research, The Netherlands
Valentin Robu
Senior Researcher, CWI Amsterdam and Full Professor, TU Eindhoven
Damien Ernst
Professor of Electrical Engineering and Computer Science, ULiège
