Profile

About

I am a dual-degree PhD student at Carnegie Mellon University and Instituto Superior Técnico. My PhD is supervised by Fernando De la Torre at Carnegie Mellon University and by Carlos Santiago and Catarina Barata at Instituto Superior Técnico. My research interests lie in computer vision, particularly generative models, representation learning, and self-supervised learning. I am interested in how visual models can learn structured and transferable representations from unlabeled data, and how those representations can support more controllable and semantically meaningful generation.

My background spans probabilistic state estimation, prototype-based learning, and applied machine learning. Before starting my PhD, I was a Visiting Scholar at Carnegie Mellon University’s Physical Perception Lab. My recent work includes vMFProto, a distributional prototype-learning approach for interpretable image classification, as well as production AI systems developed at Pairwire and GLS.

Research interests

Broadly, I want to understand how visual models organize information in their latent spaces, how useful representations can be learned with limited supervision, and how those representations can be used for generation.

Representation Learning

Visual embedding spaces that capture semantic structure, variability, and transferable information.

Self-Supervised Learning

Meaningful and robust visual representations learned from unlabeled data.

Generative Models

Structured, controllable, and semantically meaningful visual generation.

Recent updates

  1. Started a dual-degree PhD at Carnegie Mellon University and Instituto Superior Técnico

    Beginning doctoral research in computer vision through the CMU Portugal Program.

  2. Released the vMFProto preprint

    Distributional part prototypes for interpretable image classification.

  3. Joined the Physical Perception Lab at CMU as a Visiting Scholar

    Worked with Prof. Shubham Tulsiani on visual representation learning.