Joaquim Dias Garcia

Joaquim Dias Garcia joined PSR in 2015. He has been working with: (i) research and development of advanced methodologies in stochastic optimization, equilibrium / bilevel models and reinforcement learning techniques for large applications in energy markets; (ii) development of new computer systems for detailed operational planning, such as New Genesys, for the Pacific Northwest of the United States; (iii) new developments for PSR models such as SDDP (stochastic optimization of power systems operation); CORAL (generation-transmission reliability analysis); OptGen (expansion planning for electrical systems) and OptFlow (optimal non-linear power flow); (iv) instructor on PSR tools (USA, Mexico, Peru and Brazil); and (v) contributions to the JuMP ecosystem of optimization for the Julia programming language and other open source activities. Before joining PSR he worked with Signal Processing at the Optoelectronics Laboratory and with Statistics and Optimization in R&D projects at LAMPS, both at PUC-Rio.

Joaquim is the author and co-author of more than 15 articles in specialized publications; presented papers and chaired sessions at several power systems and operational research conferences (INFORMS Annual Meeting, ISMP, ICSP, IEEE PES GM, PSCC, EURO); is a reviewer of journals and conferences in these areas (IEEE Transactions on Power Systems - Outstanding Reviewer in 2019 and 2020, IEEE Transactions on Sustainable Energy, Electric Power Systems Research, INFORMS Journal on Computing, Computational Management Science Journal, Power Systems Computations Conference, PowerTech Conference , Brazilian Conference on Operations Research).

He has a degree in electrical engineering and mathematics from PUC-Rio, Brazil. He also attended a year at UC Santa Barbara, where he joined a working group on dynamic systems and control. He is currently finishing his doctoral thesis in electrical engineering with an emphasis on operational research, also at PUC-Rio.

Enthusiast of Cycling, Volleyball, Progressive Rock, Heavy Metal, Beer and Wine.