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For external collaborators — orientation

One page. Programme, people, thesis, and how to plug in.

Programme

MaQI is the data and infrastructure programme for the Master AI for Market and Quantitative Investment at École Polytechnique. The horizon is multi-year: data once, infrastructure once, reusable across cohorts of students and research projects.

Practically: a small set 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.

People

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.

How to plug in

Three useful entry points, in order of commitment:

  1. Read a provider fiche. Each data or compute provider lives as a typed page under docs/providers/ (data) or docs/compute/ (compute) — name, jurisdiction, pricing, sovereignty class, current status. A representative example: Databento — commercial facts.
  2. Share a dataset or piece of compute. If your organisation can contribute data under a research licence, or compute under an academic credit, the natural anchor is one of the existing fiches. The correspondence is monthly cadence : we answer within a week.
  3. Propose a use-case. The programme runs five concrete use cases indexed on the corpus — see scenario matrix §1. A new use case lands as a draft proposal on the same surface.

Contact

contact@serie-research.dev. Cadence is monthly — we answer within a week.