Two parallel research fronts, one common thread.
My doctorate studies stochastic optimization in the context of the Brazilian power system: cut selection, the NEWAVE–DECOMP coupling, different SDDP formulations and other general techniques. My master's traces modern generative models through the lens of Optimal Transport, from normalizing flows to flow matching, and the connecting idea of moving mass from where it is to where it should be!
Stochastic Optimization
SDDP, decomposition methods, optimal control. Applications in hydrothermal dispatch and energy planning, and everywhere else i can find.
PhD · FGV/EMApGenerative Models
Normalizing flows, continuous NFs, score & diffusion models, flow matching.
MSc · COPPE/UFRJAI-Agent Engineering
Multi-agent SDLC pipelines, guardrails, RAG, type-aware AST mapping over large codebases, context engineering! I love making agents think!
Pluma FinanceScientific Computing
Numerical methods for ODEs/PDEs, CFD, diffusion-based super-resolution of reduced-order models.
NACAD/UFRJBuilding systems where mathematics matters.
Data engineer and general consultant at LabMA/UFRJ, helping generate and optimize the brazilian biometric tables. Earlier: Early engineer at Pluma Finance, quant trading systems and scientific ML.
Technical writeups, roughly every good writing day ;)
First posts landing soon. still cooking!
Tábuas: optimizing a 1TB Oracle pipeline
The techniques that took an analytical pipeline from naïve to fast. Optimized bitmasks, plan analysis, and everything else.
coming soonMinions: an affordable multi-agent SDLC
Lessons on making a multi-agent software pipeline both cheap and functional. Real failure modes, and everything i learned about agents!
coming soonFour small tools, shipped and public.
Open-source, outside the day job — db_orchestrator, citation-xray, sparring, llm-chunking. Mostly Python, mostly born from an actual itch.