CV

PDF version here

Education

• 2016 – 2019: PhD in Signal Processing and Machine Learning, Inria Rennes, France.
  • Main themes: Sparsity-constrained optimization, Dictionary learning, Tensor methods.
  • Supervisor: Dr. Rémi Gribonval.
• 2014 – 2016: MSc Electrical Engineering, UNICAMP, Brazil. GPA: 4/4.
  • Master thesis title: Learning Structured Dictionaries.
  • Supervisor: Dr. Renato R. Lopes.
• 2010 – 2012: Engineering Cycle ÉCOLE POLYTECHNIQUE, Palaiseau, France.
  • Emphasis in Electrical Engineering.
• 2008 – 2014: BSc Electrical Engineering, UNICAMP, Brazil.
  • GPA : 0,94/1. Class rank: 1st /84.

Experience

• Permanent Researcher, INRAE, UMR TETIS, Montpellier, France (from Oct 2022)
  • Team ATTOS (Acquisition, Remote Sensing, Earth Observation data processing).
  • Inria project-team EVERGREEN.
  • Topics: Machine and deep learning for Earth observation data analysis; Satellite image time series; Explainable AI; Multi-modal data.
• Postdoctoral Researcher, IMAG, Montpelliern France (Jan 2022 - Aug 2022)
  • ANR project CAMELOT (CooperAtive MachinE Learning and OpTimization).
  • EPS (probability and statistics) team.
  • Supervisor: Prof. Joseph Salmon.
• Postdoctoral Researcher, CNRS, Institut de Recherche en Informatique de Toulouse (Jan 2020- Dec 2021)
  • FACTORY ERC project - New paradigms for latent factor estimation.
  • Supervisor: Dr. Cédric Févotte.
• Teaching Assistant, University of Rennes 1 (Sep 2018 – Dec 2018)
  • Object-oriented programming. Responsible for laboratory sessions in Java, 20h.
• Digital Communications Research Engineer, Idea! Electronic Systems (Jan 2014 – Nov 2015)
  • Research, Development and Modeling of physical layer algorithms (equalization / synchronization / coding) for digital communication systems. Digital TV Demodulator (ISDB-Tb standard).
• Design Engineer, LIP6 (Paris 6 Informatics Laboratory) (Feb 2013 - Jul 2013)
  • VHDL implementation of a multi-channel Ethernet Medium Access Controller (MAC), following the IEEE 802.3 standard.
• Research Internship, LIP6 - System on Chip department (Apr 2012 - Aug 2012)
  • Multi-core computer architecture, cache coherence protocols. Modeling in SystemC .
  • Supervisor: Dr. Alain Greiner.
• Undergraduate Internship, Schneider Toshiba Inverter Europe (Jul 2011 - Aug 2011)
  • Development of a cost estimation tool for Excel (using VBA routines) on a starting project of variable speed drives.
• Teaching Assistant, UNICAMP (Mar 2009 – Aug 2009) / (Aug 2009 – Dec 2009) / (Aug 2013 – Dec 2013)
  • Office hours (8h/week) on: Digital circuits and systems / General Physics / Operations Research.

Recent publications

See my full list of publications here.

Safe screening for sparse regression with the Kullback-Leibler divergence

Cassio Dantas, Emmanuel Soubies, Cédric Févotte, "Safe screening for sparse regression with the Kullback-Leibler divergence." In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021.

Expanding boundaries of Gap Safe screening

Cassio Dantas, Emmanuel Soubies, Cédric Févotte, "Expanding boundaries of Gap Safe screening." In Journal of Machine Learning Research, 2021.

Accelerating sparse inverse problems using structured approximations

Cassio Dantas, "Accelerating sparse inverse problems using structured approximations." At Université Rennes 1, 2019.

Learning Tensor-structured Dictionaries with Application to Hyperspectral Image Denoising

Cassio Dantas, Jérémy Cohen, Rémi Gribonval, "Learning Tensor-structured Dictionaries with Application to Hyperspectral Image Denoising." In European Signal Processing Conference (EUSIPCO), 2019.

Hyperspectral Image Denoising using Dictionary Learning

Cassio Dantas, Jérémy Cohen, Rémi Gribonval, "Hyperspectral Image Denoising using Dictionary Learning." In Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2019.

Other scientific activities

Workshops

• SPARS : The Signal Processing with Adaptive Sparse Structured Representations workshop, July 2019, Toulouse, Portugal. Poster presentation.
• GdR ISIS Seminar : “Nouvelles méthodes tensorielles et applications”, June 2019, Paris, France. Oral presentation.
• SPARS : The Signal Processing with Adaptive Sparse Structured Representations workshop, June 2017, Lisbon, Portugal. Oral presentation.
• GdR MIA Seminar : “Parcimonie et applications”, May 2018, Bordeaux, France. Oral presentation.

Summer schools

• Peyresq Summer School in Signal and Image processing : “Signaux, images et science des données”, July 2018, Peyresq, France. 21h courses.
• Structured Regularization for High-Dimensional Data Analysis, June 2017, Institut Henri Poincaré, Paris, France. 28h courses.
• SpaRTan/MacSeNet SPARS Summer School, June 2017, Lisbon, Portugal. 18h courses.
• SP Coding School, January 2015, Unicamp, Campinas, Brasil. 50h courses.

Event Organization

• Journée Science et Musique (JSM), Oct 2017 / Oct 2018. Science vulgarization thematic day at Rennes university for the local community. Planned and managed the events costs and contracts.

Peer Reviewing

• Journal : IEEE Transactions on signal processing;
• Conferences : ICASSP; CAMSAP; SBrT.

Online Courses

• Machine Learning (Stanford).
• Introduction to Artificial Intelligence (Stanford).
• Artificial Intelligence Planning (University of Edinburgh).
• Fundamentals for Big Data (Mines-Télécom).
• Control of Mobile Robots (Georgia Tech).
• Internet History Technology ans Security (University of Michigan).
• VLSI CAD Logic to Layout (University of Illinois).
• Circuits and Electronics (MIT).

Other Skills

Software

• Languages: Matlab, Python, Java, C, SystemC, VHDL, VBA (for Excel).
• Tools: Git/SVN, LaTeX, Linux, Windows, Office.

Languages

• English (advanced, 103/120 at TOEFL iBT),
• French (fluent),
• Portuguese (native).