David Pérez Piñeiro

I am a research scientist at Gridmatic, where I build optimization models and algorithms for quantitative energy trading.

I am interested in convex optimization and its applications to control, energy, and finance. I am completing my PhD at NTNU, advised by Sigurd Skogestad, and have been a visiting researcher with Richard Braatz at MIT and Stephen Boyd at Stanford. Before that, I earned a BS in Energy Engineering from the University of Vigo and an MS in Sustainable Energy from NTNU, supported by a "la Caixa" Foundation postgraduate fellowship.

Papers

An operator splitting method for large-scale CVaR-constrained quadratic programs (code)

E. Luxenberg, D. Pérez-Piñeiro, S. Diamond, S. Boyd. Optimization and Engineering, 2026.

Can language models speed up general-purpose numerical programs? (code, website)

O. Press, B. Amos, H. Zhao, Y. Wu, S. Ainsworth, D. Krupke, P. Kidger, T. Sajed, B. Stellato, J. Park, N. Bosch, E. Meril, A. Steppi, A. Zharmagambetov, F. Zhang, D. Pérez-Piñeiro, A. Mercurio, N. Zhan, T. Abramovich, K. Lieret, H. Zhang, S. Huang, M. Bethge, O. Press. NeurIPS, 2025.

Home battery dispatch under a tiered peak power tariff (code)

D. Pérez-Piñeiro, S. Skogestad, S. Boyd. Preprint, 2023.

Supervisory control design for balancing supply and demand in a district heating system with thermal energy storage

C. Zotică, D. Pérez-Piñeiro, S. Skogestad. Computers & Chemical Engineering, 2021.

Optimal operation and control of a thermal energy storage system: classical advanced control versus model predictive control

C. Zotică, D. Pérez-Piñeiro, S. Skogestad. ESCAPE, 2020.

Self-optimizing control of a continuous-flow pharmaceutical manufacturing plant

D. Pérez-Piñeiro, A. Nikolakopoulou, J. Jäschke, R. D. Braatz. IFAC World Congress, 2020.