Who am I?

Passionate about mathematics and computer science, I work on making both worlds meet and get the best out of each other. I have had and still am having a dual academic and engineering career in which I let industrial questions drive my research interest and let my engineering problems benefit from current research. In parallel to research and industrial problem solving, I mentor students in their learning journeys.

A Brief History of me

Here are the key highlights from my career.

• Currently Advanced Researcher
  Part of the ECUADOR team at INRIA Sophia Antipolis. Working on the tapenade software and researching on automated differentiation.
  
• Currently freelance Mentor/Teacher
  Contributed to London School of Economics online programs. Teaching mathematics and calculus.
  Mentoring students via Open classrooms in their data/AI projects.
• Expert engineer
  Artelys France, Paris.
  Industrial software development for power systems and optimization.
  Working with RTE on the open source projecs dynawo and powsybl.
  Development of a robust and combinatorial optimization using HPC and knitro.
  Contributions to the optimization engine of the suite crystal of software.
  (Some) Technologies used: C++, Python, Pandas, Docker, Airflow, Sun grid engine, AWS.
• Algorithm engineer
  Continental UK, Burgess Hill.
  Development of camera/radar sensor fusion algorithms.
  Development of calibration algorithms for multicamera systems in autonomous vehicles.
  (Some) Technologies used: C++, Matlab, Numerical optimisation.
• Assistant professor of mathematics
  School of mathematics and statistics.
  Beijinjg Institute of Technology.
  Teaching applied mathematics (optimization, regression, matrix analysis, computational science engineering).
  Researching signal processing (compressed sensing, stochastic PDEs).
• Postdoc
  Within the Chair for mathematics C (Analysis) at RWTH Aachen.
  Within the Department of Mathematics of Drexel University.
  Doing undergraduate teaching (calculus/algebra/numerical analysis) and graduate teaching (Mathematical and computational genomics / Mathematical foundations of machine learning)
  Researching compressed sensing and its applications. (to PDEs, MRImages, Metagenomic data survey)

On my free time, I tend to fiddle around with computer vision an Raspberry Pi's and similar nerdy things. Or I am out playing music or running marathons or hiking or... Should you be so curious, you may have a look at a more extended academic resume, or check my Linkedin profile. Why would one want to inflict this upon themselves beats me.

Some key points

I am a fervent believer in Open science and reproducible research. As such most of my work and all of my recent works can be found online on various platforms: my research page; my list of publications; my software on GitHub; some recent papers on arXiv. You may also drop me an email, should you need more references. I have also contributed to some open source projects, such as

• dynawo: a suite of simulation tools for power systems. In particular I work on automatically controling voltage on a (very) large high voltage network.
• powsybl: PoWerSystemBlocks. In particular I have implemented a few functions regarding remedial actions and passed on some features to the python API: PyPowSyBl.
• CSPDE: Compressed Sensing for PDEs. This is pretty much all in-house and is a tool to compute numerical solutions to parametric PDEs through generalized polynomial chaos.

I am very greatful to have had the opportunity to teach and talk in various places around the world, including:

• Southeast Asian Mathematical Society School on Modern Trends in Signal and Data Processing which took place in December 2022 in Manila.
• High performance AI in the industry within the Teratec forum in June 2022. I talked about robust and stochastic combinatorial optimization on an HPCa>.
• Gene Golub SIAM Summer School on the Theory and Practice of Deep Learning which took place (virtually online) in South Africa in July 2021.
• Summer program on Mathematical Signal Processing and Data Analysis within the Academia Sinica in Taipei in Summer 2019.

As a researcher, I am generally interested in applications of sparse approximation and signal processing to general mathematical and engineering problems. I am now tackling new challenges in algorithmic differentiation and contribute on theoretical aspects as well as implementations within the source to source differentiation software TAPENADE. I have contributed to many very diverse areas including (in non logical order) Optimal Coherence Tomography; Numerical solutions to parametric PDEs; Numerical recovery of sparse signals; Metagenomics; ...

This page is an ongoing work and contains only a subset of what it is hoped it will contain soon