I'm a data journalist with Les Décodeurs at leading French newspaper, Le Monde.

Resume

Job & Research Experience

November 2021 - now: Data journalist at Le Monde, France
As part of Les décodeurs, I wrote some data-journalism articles, a few fact-checks. I also write Python scripts for the newsroom and clean large databases for investigation purposes.
June 2020 - August 2021: PhD candidate at SIERRA - INRIA/CNRS, France
Structure learning of causal networks using optimization techniques. Advised by Alexandre d'Aspremont.
2019 - 2020: Teaching assistant at Stanford University, USA
Mining Massive Data Sets (Graduate), Linear Algebra with Application to Engineering Computations (Graduate), Partial Differential Equations for Engineers & Vector Calculus for Engineers (Undergraduate)
Class of more than 150 students. 20h/week: grading, holding office hours, designing assignments and exams, lecturing.
June 2019 - August 2019: Machine Learning intern at Therapanacea, France
I designed a new segmentation network for organs and tumors in CT Scans. Combined low resolutions 3D and high resolution 2D networks to alleviate the issue of patch training.
April 2018 - July 2018: Research intern at Institute for InfoComm Research, Singapore
I implemented several state-of-the-art papers to compare them to our model and conducted extensive experiments on several models and datasets. I also worked with the Medical Imaging team to apply our techniques to detecting pathologies.
June 2017 - August 2017: Deep Learning intern at Pzartech, Tel-Aviv, Israël
I participated in the design of an RGB-D recognition neural network. Also developed a 2D recognition system inspired by GoogLeNet Inception, and practiced my Computer Vision skills to design a whole learning pipeline.
September 2015 - April 2016: Educator intern at Apprentis d'Auteuil, France
Organized and leading educational activities and charity events; developed a Computer Science Introduction Course using Scratch; worked in teams with caseworkers, parents and children.

Education

MSc. at Stanford University (2018 - 2020)
Computational and Mathematical Engineering - GPA: 3.95/4
Bayesian & Classical Statistics, Deep Generative Models, Big data, Numerical Linear Algebra, PDEs, ... Projects: Fake News Detection, Topic analysis on cable-news TV, ...
BSc. & MSc. at Ecole Polytechnique (2015 - 2018)
Computer Vision and Machine Learning - GPA: 3.88/4
Relevant courses: Mathematics & Computer Science - Optimization, Random Modeling, Differential Calculus, Computer Vision, Computer Graphics, Algorithmic, Quantum and Statistical Physics, Cellular Biology & Genetics}
Lycée Saint Louis (2013 - 2015)
MP option Info - Intensive undergraduate program in Mathematics, Physics and Computer Science. - GPA: 4.0 Program leading to the nationwide competitive entrance to the French Grandes Écoles for scientific studies.

Research papers

A Bregman Method for Structure Learning on Sparse Directed Acyclic Graphs M. Romain, A. d'Aspremont
Adversarially learned anomaly detection H. Zenati, M. Romain, CS. Foo, B. Lecouat, V. Chandrasekhar accepted at the 2018 IEEE International conference on data mining (ICDM)

Check out my Google Scholar.

More about me

I speak French, English and a rusty Spanish because I was raised on the French-Spanish border.

I started climbing in Stanford and basically didn't stop 🧗‍♀. I also volunteer as an EMS at Protection Civile and participate in many humanitarian actions with them. I also love to play volleyball, paraglide, and ski.

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