Ph.D. student & Senior Data Scientist
Montreal, QC, Canada
I’m a Ph.D. student in Telecommunications at INRS under the supervision of Prof. Tiago Falk. My research interest lies in efficient deep learning (e.g., Model compression and Efficient architectures), representation learning, and self-supervised learning for speech and language processing (SLP). In addition, I aim to build efficient speech representation learning algorithms robust to distribution shifts and malicious users.
Previously, I worked as a senior data scientist at Itaú-Unibanco, where I was responsible for developing a wide range of ML solutions to handle tabular data, speech, and NLP, from conception to large-scale deployment, impacting more than 20 million users. In the past, I also had some internship experiences with investment funds and in the O&G fields. On the academic side, I have received my M.Sc. degree in Electrical Engineering at USP, a Specialization in Data Science at ITA, and my B.S. in Computer and Information Engineering from UFRJ.
For more details, please take a look at my CV (last update: 2023/10/18).
Apart from my professional interests, I like to practice Wushu (lineage: Wu Ji Tang Lang Men), and I enjoy the Beat Generation literary movement, mainly the works of Kerouac, Ginsberg, and Cassady.
|Nov 8, 2023||Our paper “Adapting Self-Supervised Features for Background Speech Detection in Beehive Audio Recordings” received the Best Paper Presented by a Young Researcher Award at IEEE MetroAgriFor|
|Nov 3, 2023||Received the IEEE Signal Processing Society (SPS) Scholarship!|
|Sep 4, 2023||We got two papers accepted at IEEE MetroAgriFor on Beehive Acoustics Monitoring|
|Jul 15, 2023||Received the CIFAR Inclusive AI Scholarship to attend the CIFAR DLRL Summer School!|
|Jun 2, 2023||We got one paper accepted at the AI and (cyber)security workshop @ IEEE SMC 2023|
- ConferenceRobustDistiller: Compressing Universal Speech Representations for Enhanced Environment RobustnessIn 2023 International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2023
- ConferenceImproving the Robustness of DistilHuBERT to Unseen Noisy Conditions via Data Augmentation, Curriculum Learning, and Multi-Task EnhancementIn NeurIPS 2022 Efficient Natural Language and Speech Processing Workshop, 2022
- ConferenceA Perceptual Loss Based Complex Neural Beamforming for Ambix 3D Speech EnhancementIn Proc. L3DAS22: Machine Learning for 3D Audio Signal Processing, 2022
- JournalMonaural speech enhancement through deep wave-U-netExpert Systems with Applications, 2020