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I've completed my Ph.D. at the University of California San Diego under the supervision of Prof. Nuno Vasconcelos. The title of my dissertation was "Learning to see and hear without human supervision". After graduation, I will be doing a postdoc at CMU working with Prof. Abhinav Gupta and, in the Fall of 2022, I will join the ECE department at the University of Wisconsin Madison as an Assistant Professor. Before UC San Diego, I earned both B.Sc. and M.Sc. degrees from Instituto Superior Técnico, Universidade de Lisboa, Portugal in 2010 and 2012, respectively, where I worked with I worked with Prof. Margarida Silveira.
For up-to-date information about my work, please visit my new webpage.
I am interested in computer vision and machine learning. Specifically, my research focuses on developing learning and deployment frameworks that enable deep learning to operate with restricted labeled data and restricted computing power. As such, I maintain an active interest in areas such as zero-shot, low-shot learning and other transfer learning problems, self-supervised learning, multimodal supervision, and efficient training and deployment procedures.
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Learning to see and hear without human supervision |
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Robust Audio-Visual Instance Discrimination |
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Audio-Visual Instance Discrimination with Cross-Modal Agreement |
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Deep Hashing with Hash-Consistent Large Margin Proxy Embeddings |
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Learning Representations from Audio-Visual Spatial Alignment |
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Solving Long-tailed Recognition with Deep Realistic Taxonomic Classifier |
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NetTailor: Tuning the Architecture, Not Just the Weights |
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PIEs: Pose Invariant Embeddings |
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Self-Supervised Generation of Spatial Audio for 360° Video |
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Semantically Consistent Regularization for Zero-Shot Recognition |
Minimal neighborhood redundancy maximal relevance:
Application to the diagnosis of Alzheimer's disease |
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Predicting conversion from MCI to AD with FDG-PET brain images at different prodromal stages |
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Diagnosis of Alzheimer's disease using 3D Local Binary Patterns |
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Texton-based diagnosis of Alzheimer's disease |
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Efficient selection of non-redundant features for the diagnosis of Alzheimer's disease |
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Extending Local Binary Patterns to 3D for the diagnosis of Alzheimer's disease |
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Automated Diagnosis of Alzheimer's Disease using PET Images: A study of alternative procedures for feature extraction and selection |
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University of California, San Diego |
San Diego, CA |
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Facebook AI Research |
New York, NY |
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Adobe Research |
Seattle, WA |
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Institute for Systems and Robotics |
Lisbon |
Fundacao para a Ciencia e Tecnologia |
2015-2019 |
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University of California, San Diego |
2014 |
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SVCL