Quant Researcher @QRT

Previously Double Degree Master student at Ensae Paris and MVA (ENS Paris-Saclay). Interested in Machine Learning, Deep Learning, Swarm intelligence.

I open source some of my projects here.

Currently working on :

• Quantools : [Financial Engineering | Visualization | High Performance Python] A tool-box for quants (ML-oriented)
• DDQL : [RL | Optimal Execution | Trading] Implementation of a paper.

Contact : lucas[dot]saban[at]ensae[dot]fr

• 1st place at 2022 Ostrum Asset Management Finance Game. Deep Recurrent Reinforcement Learning for Dynamic Portfolio Optimization.
• 1st place at the 2022 Hi Paris Hackacthon delivered by Capgemini. Segmentation and classification computer vision tasks.
• 1st place at the 2022 ENSAE's Hackathon by Eleven Strategy and Data For Good. We used computer vision, NLP and audio segmentation to evaluate Bechdel scores.
• 2nd place at the 2021 ENSAE's Hackathon by Capgemini

• Leveraging latent representations for efficient textual OOD detection. Paper, Repo (Not published)

• Large scale joint Hyperparameters and feature selection using Multi-objective heuristic optimization Report, Presentation and Repo

• Implementation of Fast Shapelet discoveries for time series classification Orignal Paper, Report and Repo

• Implementation of Double Deep Q-Learning for Optimal Trading Execution Orignal Paper, Report and Repo

• Spatio-temporel spectral clustering algorithm based on HDBSCAN for dynamic event recognition. Source is private but happy to talk about it.

• A full-stack Image Classification project using Tensorflow, Transfer-learning and CNN's. An iOS app, that I coded in swift, is the front-end part of the project. It was realized with Augustin Cramer

• A scikit-learn plugin for binary Classification tasks, delivered as a pypi package. The source is available here.

• An Ant-Search Simulation with GUI using C++ and SFML

• A data Visualization project using Geopandas : Gravity Law Model Applied to inter-cities traffic