RefineML
A requirements-focused approach for the continuous and agile refinement of ML-enabled systems.
Applied Scientist at Dell Technologies
PhD candidate in Computer Science at PUC-Rio
I am an Applied Scientist at Dell Technologies, where I work on multimodal AI inference and serving. My work focuses on performance modeling, capacity planning, and the scalability of generative AI systems.
I am also a PhD candidate in Computer Science at PUC-Rio. My research investigates agile management and requirements engineering for ML-enabled systems, including RefineML, developed through industry–academia collaboration.
Previously, I worked as a Data Scientist at ExACTa PUC-Rio and CERN. I hold an M.Sc. in Physics from PUC-Rio and a B.Sc. in Physics from UFF. I received the Best Industrial Experience Paper Award at Software Quality Days 2025.
A requirements-focused approach for the continuous and agile refinement of ML-enabled systems.
An open-source application for multilingual audio transcription using Whisper.