Hi there! This is Marcos.
Here, I will be sharing technical notes and insights as I explore AI, Computer Vision, Sensor Fusion, and algorithm development in Python, C++, Rust, and Swift.
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About Marcos Borges
Marcos Borges is a Research Engineer specialising in AI, Vision, and Sensor Fusion. His experience includes the development of proofs of concept for autonomous navigation, remote sensing, and target tracking. He has also worked in collaboration with international teams and researchers across diverse fields such as biotechnology, medical diagnostics, aerospace, defence, and security.
Professional Experience
Senior Research Engineer
ENGIE Lab CRIGEN, Paris area, France — Jun 2018 - Feb 2024
Led R&D for Computer Vision and Embedded Systems, contributing to AI strategy and execution. Delivered Machine Learning prototypes for Robotic Perception, Object Tracking, Neuromorphic Computing, and Physics Informed Neural Networks.
Doctoral Researcher
Safran Electronics & Defense, Massy, France — Aug 2014 - Nov 2017
R&D in Bayesian estimation, Kalman filtering, Random Finite Sets, sensor management, and data fusion for remote sensing and target tracking.
Research Engineer
INPE, São Paulo, Brazil — Feb 2012 - Jul 2014
R&D in multi-objective optimisation and machine learning, aimed at the design and improvement of industrial robots and satellite navigation sensors.
Research Engineer Trainee
Lucaph, São Paulo, Brazil — Feb 2008 - Dec 2010
Designed and prototyped a micro-plate washer to automate ELISA blood sample processing, integrating custom circuit boards developed using Altium Designer, and embedded C software for PIC and ARM7 microcontrollers.
Education
École Centrale de Lille, France — Sept 2014 - Dec 2018
Doctor of Philosophy (PhD) in Signal and Image Processing
Relevant Coursework
Signal and Image Processing
Target Tracking Algorithms (Kalman filters, JPDA, MHT, PHD, CPHD, and GLMB)
Foundations and Applications of Sensor Management
Partially Observable Markov Decision Process (POMDP)
Random Finite Sets (RFS)
Multi-Sensor Data Fusion
INPE - National Institute for Space Research, Brazil — Feb 2011 - Dec 2013
Master of Engineering (MEng) in Computational and Applied Mathematics
Honour & award
Genetic Algorithm for design optimisation of an LED-based Spectrally Tunable Light Source recognised as one of the top three papers presented during the XII Workshop on Applied Computing at INPE, 2012.
Relevant Coursework
Artificial Neural Networks
Data Structures using C++
Digital Image Processing
Multi-Objective Optimisation
Machine Learning and Pattern Recognition
São Francisco University, Brazil — Feb 2006 - Dec 2010
Bachelor of Engineering (BEng) in Computer Engineering
Publications
Real-Time Sensor Management Strategies for Multi-Object Tracking.
Centrale Lille, France, Dec 19, 2018.A Risk-Based Sensor Management using Random Finite Sets and POMDP.
IEEE FUSION, China, Jul 10, 2017.Sensor Management using Expected Risk Reduction approach.
IEEE FUSION, Germany, Jul 5, 2016.Spectrally tunable LED-based light source for star sensor calibration, with application of the evolutionary computing paradigm.
INPE, Brazil, Dec 19, 2013.Generalized Extremal Optimization Algorithm to design a LED-based spectrally tunable light source for Star Simulation.
PACIS, Brazil, Nov 19, 2013.
