Summary
I have a PhD in Computer Science, and I am also an Engineer and an Inventor.
My main areas of expertise are Machine Learning and Data science, where I am specialized in graph analysis and visualization.
I have 6 years of expertise in Machine Learning.
Skills
(Left=high, Right=low)
Programming: Python, Ocaml, Latex/Pandoc, Javascript/NodeJS, Lua, C, Lisp
Databases: Neo4J, Redis, SQL
Topics of Interest: Algorithms, Machine Learning, Graphs, Security, Time Series, Biometry, Distributed computing, Recommander Systems, Dark data.
Languages: French, English, Spanish, Japanese, Tokipona
Coding Challenges:
Others: Two patents published, one pending.
Tech Hobbies: Laser Cutting, Arduino, Raspberry, MagTag
Non-Tech Hobbies:
- Leatherworks (made bags, belts, keychains, steering wheel cover, …)
- Woodworking (carving in the round, laser cutting)
- Chocolate maker (I may have 10kg of chocolate at home waiting for me !)
- Poï and Staff Juggling (Best way to relax in Fall)
- Swimming (Best way to relax in summer)
- Piano (Best way to relax on a rainy day)
If you want to know more about my hobbies and creation, have a look at my other website
Go to the contact page
My History
Quick links:
(Click on the figure lines to get directly to the corresponding paragraph.)
Professional Path
(from present to past)
Ingenico
(2019 ~ today) Research Engineer (Suresnes).
Topics:
- Automated scientific watch
- Predictive Maintenance
- Malware detection
- Biometry
- Graph analysis and community detection
- Ensemble learning
- Patents
Achievements:
- Scientific watch: developed tools for scientific papers analysis (PhD work)
- Predictive Maintenance: analyzed time series to predict terminal failures and items to be repaired
- Malware detection: Created ML algorithms for explainable malware classification
- Cryptocurrency: Taught how cryptocurrency works, how the network is organized, and how transaction are processed
- Biometry:
- Palm Vein Biometry: Security analysis of a solution
- Voice biometry: studied state of the art algorithms for voice generation and user recognition
- Repport of Behavioral and continuous biometry on smartphone
- IoT 4.0: Summer School on automated programming
Keymetrics
(2017 ~ 2019) Research Engineer, Keymetrics (Paris).
Topics:
- Time series analysis
- Cross-correlation
- Point process
- CUSUM and online error detection algorithm
- NodeJS monitoring
- Machine Learning
- Feature engineering
- Predictive maintenance
Achievements:
- Created process for time series clustering and embedding: Developed outlier-resistant features for time series representation and clustering.
- Created a memory leak detection algorithm.
Wallix
(2017) Research Engineer, Wallix (Paris).
Topics:
- Natural Language Processing (NLP)
- Security x Machine Learning: Intrusion detection systems (IDS)
- Cryptography
Achievements:
- H2020 project initiator: Applying for H2020 projects. Organizing meeting with potential partners, built the application file. Obtained three grants.
- Learned about Homomorphic and functional encryption
- Implemented a Spam filtering module with extended trees and neural networks
- Studied Hidden Markov Models and Conditional Random Fields
CRI
(2016-2017) “Centre de Recherche Interdisciplinaire”. 3 months internship (Paris).
This transition internship was dedicated to learning algorithms in AI and Machine Learning.
Topics:
- Classical AI algorithms (BFS / DFS, greedy algorithms)
- Machine learning algorithms:
- Support Vector Machine
- Conditional Random Field
- Hidden Markov Model
Achievements
- Developed skills in efficient algorithms writing in Ocaml
- Reached level 6 on FranceIoI (French platform for algorithm training)
Sivienn
(2016) M2 Internship (Palaiseau).
Modeling influence of temperature over materials for passive building monitoring.
Use of time series analysis and statistical methods.
Topics:
- Statistics
- Time series analysis
- Cross-correlation analysis
- Gaussian process
Achievements:
- Performed analysis of temperature - dilatation time series using cross correlation analysis, Gaussian process, and de-trending. (scope: non-intruisive building monitoring)
- Made an interactive Web server for computing and displaying results on demand with
bokeh.
Institue for Molecular Science (IMS)
(2015) M1 Internship (Okazaki, Japan)
Modeling Infrared properties of molecule using DFT.
Topics:
- Molecular modeling
- Numerical simmulation
- SAC-CI, DFT
Achievements:
Studied two organics molecules with supposed visible transition spectrum.
Use a large computing cluster.
Education
PhD Thesis
(2018 ~ 2022) PhD student at ENS (École Normale Supérieure de Paris). Financed by Ingenico.
Supervisor: David Naccache.
Link to the thesis: Connecting Graphs to Machine Learning
Link to [my publications(/Research.html)
Topics:
- Machine Learning
- Graphs
- Scientific watch
- Recommander systems
- Data Visualization
Achievements:
Tools for performing scientific watch:
- Automated cluster classification
- Topic analysis
- Trend monitoring and evaluation
SMNO
(2015- 2016) “Science of Nano-Object and Materials”. M2 at UPMC (Universitée Pierre et Marie Curie).
Topics:
- Quantum physics
- Condensed matter physics & chemistry:
- Magnetism
- Semiconductors
- Electronical properties
- Optical properties
- Computational Chemistry
ENSCP
(2013-2016) Chimie ParisTech (Paris).
Top Chemistry engineering school.
Diploma awarded in 2016.
Topics:
- Thermodynamic
- Organic and Inorganic Chemistry
- Mathematics
- Modeling and Simulation
- Quantum chemistry
- Cristallography
- Chemistry and interfaces
- Chemical risks
Prep Classes
(2011-2013) Preparatory classes in Biology (BCPST, Tours).
Topics:
- Biology
- Genetics
- Cell organization
- Biological development
- Photosynthesis and Krebs cycles
- Plants growth and organization
- Geology
- Ecology
- Maths:
- Probabilities
- Algebra
- Calculus
- Differential equations
- Programming
- Physics and Chemistry:
- Thermodynamic
- Electricity
- Optics
- The different state of matter
- Organic chemistry
- Inorganic Chemistry