Ayman CHAOUKI

AI Researcher

Massy, Île-de-France, France3 mos experience

Key Highlights

Developed algorithms for optimal Decision Trees in Reinforcement Learning.
Presented research at EWRL 2023 workshop.
Published multiple papers in finance and data science.

Stackforce AI infers this person is a skilled AI researcher specializing in Reinforcement Learning and Decision Tree optimization.

Contact

Skills

Other Skills

PythonDynamic programmingBranch & BoundReinforcement LearningDecision Trees

About

I am a PhD student under the joint supervision of Ecole Polytechnique (France) and the University of Waikato (New Zealand). My research pertains to seeking optimal Decision Trees within a Reinforcement Learning framework. I developed new algorithms for this purpose, from Dynamic Programming and Branch & Bound to Monte Carlo Tree Search methodologies. The induced methods satisfy optimal convergence and finite-time PAC-style optimality guarantees. My aim is to further develop these methods and generalise them to Markov Decision Processes satisfying reasonable assumptions, with the objective of studying their sample complexities and comparing them with the standard Reinforcement Learning algorithms.

Experience

3 mos

Total Experience

3 mos

Average Tenure

Current Experience

Hrflow.ai (ex: riminder.net)

AI Researcher

Sep 2025 – Present · 9 mos · Courbevoie, Île-de-France, France

Lix

Postdoctoral researcher

Jan 2025 – Sep 2025 · 8 mos · Palaiseau, Île-de-France, France

Rule based fraud detection with graph search.

Télécom paris

Engineer in Research and Development

Apr 2020 – Apr 2021 · 1 yr · Palaiseau, Île-de-France, France · Remote

Deep Reinforcement Learning applied to seeking optimal Decision Trees. The work was presented at EWRL 2023 workshop https://openreview.net/pdf?id=sf4RZXGqrC .

Capital fund management (cfm)

2 roles

Research Fellow

Nov 2019 – Dec 2019 · 1 mo · Paris, Île-de-France, France · On-site

I continued work with the Head of Execution Strategies Joachim de Lataillade on a followup project to my internship. The publication can be found at https://arxiv.org/abs/2003.04646 .

Research Intern

May 2019 – Oct 2019 · 5 mos · Paris, Île-de-France, France · On-site

Research on Deep Reinforcement Learning applied to portfolio optimisation, with an accepted publication in the journal of finance and data science https://www.sciencedirect.com/science/article/pii/S2405918820300118 .

Generali france

Data Scientist Intern

Mar 2018 – Aug 2018 · 5 mos · Île-de-France, France · On-site

Improving upon Generalised Linear classifier models with gradient boosting algorithms.
Computer Vision: Information extraction from scanned ID cards with Deep Learning and Tree Search.

Mazars

Data Scientist Intern

Sep 2017 – Feb 2018 · 5 mos · Courbevoie, Île-de-France, France · On-site

Optimisation of a vehicle routing problem using Branch & Bound.

Junior centrale études

Translating Python scripts to Julia

Mar 2017 – Jul 2017 · 4 mos · Remote

Through the intermediary of Junior Centrale Etudes, I worked for professor Gabriel Peyré (CNRS) on translating his numerical tours from Python to Julia. My contribution is cited on professor Peyré's website https://www.numerical-tours.com/2017/08/05/julia-tours/ .