MaQI
MaQI is the data and infrastructure programme for the Master "AI for Market and Quantitative Investment" at École Polytechnique. It studies the practical arithmetic of running quantitative-research workloads at university scale — data acquisition, storage, reproducible execution, and the contract surface between teaching, research, and the industry partners that fund both. The horizon is multi-year: data once, infrastructure once, reusable across cohorts.
People
- Charles-Albert Lehalle — scientific advisor. Previously Imperial College London and Capital Fund Management (CFM); the intellectual lineage that anchors the programme.
- Emmanuel Sérié — operator. Carries the data, infrastructure, and partner-facing surfaces.
- Wissal Efdaoui — research engineer. Carries data acquisition, storage, and day-to-day execution.
Three paths in
- For CAL — compute arbitrage verdict. One-page brief: top-2 architectures per use case, three atomic open questions.
- For Wissal — pipeline status & Wasabi buckets. Where each pipeline is, what each bucket holds, what is yours this week.
- For external collaborators — orientation. Programme, people, thesis, and how to plug in.
Research thesis
Quantitative finance is a discipline whose best results emerge when data, compute, and people are co-located in the same operational unit. MaQI is built on that assumption: rather than fragment infrastructure across courses and projects, the programme consolidates a small number of high-quality datasets, a reproducible execution layer, and a steady cadence of student and research output. Industry partners contribute to and benefit from a shared substrate, not a series of one-off engagements.
Contact
For collaboration, partnership, or programme inquiries: contact@serie-research.dev.
The cadence is monthly. We answer within a week.