Last page update: 15/04/2021
Ph.D. on Computer Vision and Machine Learning.
Senior AI Architect at ActiveEon, Paris - France.
Experienced C++ and Python Developer.
15+ years of professional experience with software engineering, software architecture, and software design. I have been working since Nov 2000 with low-level and high-level software development at several IT companies (for more info, please see my CV).
Currently, I'm working as a Senior AI Architect at ActiveEon and I'm leading the Artificial Intelligence (AI) team.
I work on the intersection of scientific research and software engineering, by bringing cutting-edge AI technologies to the core platform of ActiveEon. My main focus is on AI at Scale, HPC+IA, and MLOps.
In short, my activities are:
- Lead a team of PhDs on AI & Machine Learning;
- Development of end-to-end AI workflows;
- Development of parallel & distributed AI workflows;
- Development of multi-node & multi-GPU AI workflows;
- Development of a large-scale distributed AutoML workflow for hyperparameter optimization & neural architecture search;
Summary of my AI research experience:
Since 2010, my AI research activities include intelligent video analysis for object detection, segmentation, and tracking, to perform event/action recognition and behavior classification/prediction.
I also developed and deployed computer vision and machine learning models at the edge on system-on-a-chip (SoC) devices such as Raspberry PI, PandaBoard, and NVIDIA Jetson boards (Nano, Xavier NX, TX2, and AGX Xavier).
My Ph.D. was focused on the application of advanced matrix and tensor methods for robust low-rank/sparse representation and subspace learning/clustering of multidimensional and streaming data, such as moving object detection and background-foreground separation in multi-spectral and multi-featured video sequences.
In the past, between my B.Sc. and my M.Sc, I worked on several embedded systems and robotic projects using microcontrollers and SoC boards to read sensors, I/O devices, performing data acquisition, signal processing, image/video processing, wireless communication, and motor control. For more information, please see the Projects page at the top of this page.
Main research interests: Computer Vision, Machine / Deep Learning, Pattern Recognition, Applied Mathematics, Matrix / Tensor Decomposition, Optimization, Big Data.
Journal reviewer: I peer-reviewed for more than 10 high-quality journals, such as Elsevier (CVIU, IVC, PRL, NC, IF), Springer (NCA, CC, FITEE, JIVP), IEEE (TIP, TNNLS, TCSVT), MDPI (Sensors), JEI, JOSA-A, PLOS ONE. For more information, please see my Publons profile for an updated version.
My open source libraries and source code:
BGSLibrary - A Background Subtraction Library.
VDTC - Vehicle Detection, Tracking, and Counting.
LRSLibrary - Low-Rank and Sparse tools for Background Modeling and Subtraction in Videos.
MTT - Matlab Tensor Tools for Computer Vision.
IMTSL - Incremental and Multi-feature Tensor Subspace Learning.
OSTD - Online Stochastic Tensor Decomposition.
For more details, please visit my GitHub profile: https://github.com/andrewssobral