Raphaël Reynouard

CTO · Machine Learning · Model Checking
KLEIDROBE · Switzerland

I lead an AI startup, combining a strong theoretical foundation with hands-on experience in deploying real-world systems.
I hold a PhD in Machine Learning, with a focus on its application to critical systems via Model Checking techniques.
My recent postdoc at Eawag involved applying deep learning methods to hydrology.
Extensive experience in Python, demonstrated through the development of the Jajapy library.
At Kleidrobe, I'm leading the IT team building a SaaS product involving computer vision.

Skills

Programming Languages & Tools
  • python
  • pytorch
  • numpy
  • scikit
  • r
  • java
  • github
  • node
  • react
  • js
Technical Knowledge
  • AI, Deep Learning, Computer Vision, Statistical Foundations of Machine Learning
  • Data Analysis and Visualization
  • Full-stack development
  • Automata Theory & Markov Models, Model Checking
  • Algorithm Design
  • Numerical Methods
Languages
  • French, native
  • English, full professional profeciency
  • German, basics
  • Icelandic, basics

Experience

Chief Technology Officer

Kleidrobe · Berlin, Germany
  • Deep learning · Computer vision · Fashion
  • Building an AI model for online customer sizing
  • Leading the IT team building a scalable SaaS product
since January 2025

Project Leader

Bains de Saillon · Saillon, Switzerland
  • Algorithmic · Full Stack
  • Developed Janus, a HR management software
  • Automatic generation of employees schedules following legal constraints and personal preferences
  • Python Backend, Flask API, SQL database, Bootstrap frontend
November 2024 - February 2025

Postdoc Researcher

EAWAG · Dübendorf, Switzerland
  • Deep Learning · Generative AI · Hydrology
  • Developed deep learning and generative AI methods for structure learning and parameter estimation of mass-conserving process-based models
January 2024 - August 2024

IT Specialist

Expo Kilim · Brussels, Belgium
  • Database management
  • Maintained internal website and managed CCTV system setup
June 2018 - September 2019

Education

Ph.D. in Computer Science

Reykjavík University · Reykjavík, Iceland
  • Machine Learning · Model Checking
  • Anna Ingólfsdóttir · Giovanni Bacci
  • On learning stochastic models: from theory to practice
  • Developed and implemented unsupervised machine learning methods for parameter estimation of Markov models.
  • Managed my own research agenda and gave talks across Europe (Belgium, Switzerland, Germany, Denmark, Italy)
August 2020 - November 2023

M.S. in Computer Science

Université Libre de Bruxelles · Brussels, Belgium
September 2018 - June 2020

B.S. in Computer Science

Université Libre de Bruxelles · Brussels, Belgium
September 2015 - June 2018

Publications

On learning stochastic models: from theory to practice

R. Reynouard
PhD Thesis

A MM Algorithm to Estimate Parameters in Continuous-time Markov Chains

G. Bacci, A. Ingólfsdóttir, K. G. Larsen, R. Reynouard
QEST'23

Jajapy: a learning library for stochastic models

R. Reynouard, G. Bacci, A. Ingólfsdóttir
QEST'23

Active Learning of Markov Decision Processes using Baum-Welch algorithm

G. Bacci, A. Ingólfsdóttir, K. G. Larsen, R. Reynouard
ICMLA'21

Online Learning of non-Markovian Reward Models

G. Rens, J.-F. Raskin, R. Reynouard, G. Marra
ICAART'21

Tool

Jajapy

A Machine Learning Python library for Markov models
A python library implementing the Baum-Welch algorithm on various kinds of Markov models.
  • Learning HMMs, MCs, MDPs and CTMCs from traces.
  • Parameter estimation for synchronous composition of CTMCs.
  • Parameter estimation for PCTMCs.
  • Compatibility with Prism and Storm.
Since 2022

Research activities

Artifact evaluation committee member

QEST'23

Artifact evaluation committee member

QEST+FORMATS'24

People I’ve had the honor of working with

Side Projects

Playground

Visualization of several algorithms that facinate me

Which is AI

Guess which of the pictures is AI generated