I am a fourth-year PhD Candidate at ÉTS Montreal, working in the Distech Controls Industrial Research Chair project with a MITACS scholarship. I am advised by Professors Marco Pedersoli and Eric Granger. My primary research focus is computer vision and machine learning, especially in object detection and domain adaptation. I am also a member of the International Laboratory on Learning Systems (ILLS). In winter 2025, I was a Machine Learning intern at RBC Borealis, working on test-time adaptation (TTA) for forecasting.

I completed my Master's at CIn-UFPE, advised by Hansenclever Bassani. In parallel, I was a researcher at LINCS/CETENE with Edna Barros and Antonyus Pyetro in object detection and face recognition. By the end of my Master's, I worked as a junior data engineer at Neurotech for eight months, focusing on ETL, data ingestion, and deep learning solutions.

For my undergraduate studies, I earned a bachelor's in computer engineering at CIn-UFPE, where I worked in robotics with Edna Barros and Hansenclever Bassani, and in computer vision with Carlos Alexandre. During my bachelor's, I interned as a software engineer at Motorola/CIn, developing a parser for 4G wireless communication, and co-founded RoboCIn, the top robot competition team in Latin America. Throughout my academic career, I have received several scholarships and won hackathons and robotics competitions.

I am a reviewer for CVPR, ICLR, WACV, and LXAI, and currently serve as co-chair for the LXAI NeurIPS 2024 workshop. In my free time, I enjoy Kaggle competitions, playing guitar, watching anime, and drinking a good cappuccino.

I am currently seeking internship positions for 2025. After my PhD, I am open to postdoctoral or industry opportunities. Please feel free to contact me if you have any opportunities.

My main interests include object detection, generative models, domain adaptation, diffusion models, parameter-efficient fine-tuning, and visual prompt tuning.