Research Scientist @ Gridmatic
Optimization and power systems

I'm currently a research scientist at Gridmatic. Previously, I obtained my PhD at Stanford University, where I studied optimization and market design for the electricity grid. My thesis focused on developing computational tools for long-term grid planning problems and was supported by the DOE Computational Science Graduate Fellowship. You can see a selection of my published work below.

Publications

• Gradient methods for bilevel electricity grid expansion planning
  Degleris, El Gamal, and Rajagopal
  Applied Energy (2026)

• GPU Accelerated Security Constrained Optimal Power Flow
  Degleris, El Gamal, and Rajagopal
  Optimization and Engineering (2026)

• Fast grid emissions sensitivities using parallel decentralized implicit differentiation
  Degleris, Fuentes Valenzuela, El Gamal, and Rajagopal
  IEEE SmartGridComm (2024)

• Equitable dynamic electricity pricing via implicitly constrained dual and subgradient methods
  Balogun, Martin, Degleris, and Rajagopal
  IEEE SmartGridComm (2023)

• Dynamic locational marginal emissions via implicit differentiation
  Fuentes Valenzuela, Degleris, El Gamal, Pavone, and Rajagopal
  IEEE Transactions on Power Systems (2023)

• Spatiotemporal clustering with Neyman-Scott processes via connections to Bayesian nonparametric mixture models
  Wang, Degleris, Williams, and Linderman
  Journal of the American Statistical Association (2023)

• Emissions-aware electricity network expansion planning via implicit differentiation
  Degleris, Fuentes Valenzuela, El Gamal, and Rajagopal
  Climate Change Workshop at NeurIPS (2021) (Spotlight Talk)

• Point process models for sequence detection in high-dimensional neural spike trains
  Williams, Degleris, Wang, and Linderman
  NeurIPS (2020) (Oral Presentation)

• A provably correct and robust algorithm for convolutive nonnegative matrix factorization
  Degleris and Gillis
  IEEE Transactions on Signal Processing (2020)

Teaching

• From 2017 to 2020, I TA'd ENGR 108 (Applied Matrix Methods) under Professors Stephen Boyd, David Tse, and Brad Osgood.

• In 2022, I redesigned the lecture notes for CEE 272R (Engineering Future Electricity Systems) in collaboration with Professor Ram Rajagopal.