Engineering student at CentraleSupélec (Université Paris-Saclay), previously Sorbonne Université. I build machine learning models, quantitative tools and real-time systems that have to work outside the notebook — for uranium mines, financial advisors, and a live-streamed ATM.Engineering student at CentraleSupélec. I build machine learning models, quantitative tools and real-time systems that have to work outside the notebook — for uranium mines, financial advisors, and a live-streamed ATM.
Looking forRole
6-month role in machine learning or quantitative finance, from February 2027: internship, VIE or fixed-term contract.
A physics-informed model for uranium mine operations
Asked to fix a production model planning well cleaning, I traced its errors to interactions between neighbouring wells — then derived a new model from the geology literature.
Transformer with spatio-temporal cross-attention + Neural ODE
Data
10,000+ well time series, up to 20 years each10,000+ well series, up to 20 years
Found
~30% of legacy data silently imputed
Real-time systemsQSTNMRK, 2026
Fig. 1 — The Last Dollar, streaming 24/7.
The Last Dollar
A 24/7 live-streamed sculpture fed by an internet-connected ATM. I built it end to end, including a low-cost streaming stack whose cost stays flat regardless of audience size.
I started programming at 12 and never really stopped. I did a double bachelor's in mathematics and computer science, and I'm now on a gap year before my final engineering year. The mathematics is what I lean on most — usually when an AI model does something I wasn't expecting.
Right now I'm a data science intern at Orano and lead developer at QSTNMRK, on art e-commerce and live-streaming projects. A few years of freelancing before that taught me to pin down what a client really needs, and to stay on the hook when something breaks after delivery.
Next, I want to work close to the people who have the problem — on hard technical problems, across different clients. I'm looking for a 6-month role from February 2027 — internship, VIE or fixed-term contract all work for me — in London.Next, I want to work close to the people who have the problem — on hard technical problems, across different clients.
Global nuclear fuel cycle company, from uranium mining to recycling.orano.group ↗︎
Traced the errors of a production model planning well cleaning across uranium mines to an overlooked factor: interactions between neighbouring wells.
Designed a physics-informed replacement — a Transformer with spatio-temporal cross-attention coupled to a Neural ODE, trained on 10,000+ well time series spanning up to 20 years.
Built the extraction from mine monitoring systems (SQL, REST).
PyTorch
Transformers
Neural ODE
Physics-informed ML
SQL
Jan 2024 — Present
Part-time
Lead Developer · QSTNMRK
Art collective — e-commerce, IoT and live-streamed works.
Built The Last Dollar end to end, featured in designboom: ATM hardware over MQTT, and a streaming stack whose cost stays flat regardless of audience size.
Built with the founders the projection tool (NestJS, React) brokers used in client meetings to present the company's retirement products; also modelled the B2B commission schemes (upfront, trail and linear payouts, clawbacks).
Set up the servers, development environments and monitoring with Traefik, Prometheus and Grafana.
Built with advisors a retirement-plan (PER) simulator projecting capital at retirement and each client's tax saving, including carried-over deduction ceilings.
Designed a web app for digital client files and advisor booking.
Administered the internal Salesforce CRM with an external team at BayBridgeDigital.
A small delivery vehicle on Raspberry Pi and Arduino that detects its track by image processing, computes steering, and drives the motors through turns in an urban-like course.
Computer vision
Raspberry Pi
Arduino
Control
Jun 2025 · Team project, CentraleSupélecJun 2025 · CentraleSupélecPrivate
Graphical Models in Finance
Sparse dependency networks across MSCI World stocks (Graphical Lasso, Ledoit-Wolf) on rolling 250-day windows; networks densify with new cross-sector links in turbulent periods.
Python
Graphical Lasso
Statistics
Finance
May 2024 · with Bouygues TelecomMay 2024 · Bouygues TelecomPrivate
Anomaly Detection on a LoRaWAN IoT Network
A Spark pipeline over large-scale LoRaWAN logs that flags devices and traffic behaving abnormally and points at likely causes — unsupervised, on time-series features.
A recommender built on subtitle text rather than ratings, with TF-IDF, K-Means and a perceptron. Supervised by Nicolas Baskiotis; results turned out to hinge on preprocessing.