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Noptus/README.md

Raphaël Caillon

AI Specialist at Solace, based in Paris. Previously SAP and Deeplink Medical.

I build event-driven AI systems and data pipelines, and study how to evaluate them reliably.

Selected work

  • Backtests as Reward Signals — adaptive research, false discoveries and reproducible experiments. Working paper.
  • Numerai Solstice — ensemble learning, era-level evaluation and prediction neutralization.
  • Solace Trading Lab — order matching, market-data projections and deterministic replay.
  • Factorio Agent Lab — agent coordination through a serialized action queue. Integration prototype.
  • Scoop — an account-intelligence product experiment and its public website.

Projects use AI assistance; implementation details and validation are documented in each repository.

Daily algorithm practice on LeetCode. Outside work: origami and running.

LinkedIn · Email

Popular repositories Loading

  1. numerai-solstice numerai-solstice Public

    Numerai v6 research with purged walk-forward validation, official NCORR scoring and reproducible CPU experiments.

    Python 2

  2. solace-trading-lab solace-trading-lab Public

    Event-driven trading simulator: typed event contracts, price-time matching, market-data projections and validated recording/replay.

    Python 1

  3. Noptus Noptus Public

    AI engineering, event-driven systems, quantitative research and product experiments.

  4. factorio-sam-demo factorio-sam-demo Public

    AI-assisted Factorio agent-coordination prototype: serialized priority actions, explicit uncertain outcomes and offline broker/bridge tests.

    Python

  5. backtests-as-reward-signals backtests-as-reward-signals Public

    Controlled experiments on adaptive backtest overfitting, with auditable agent traces, frozen artifacts and reproducibility checks.

    Python

  6. Scoop Scoop Public

    Account-intelligence product experiment. Responsive website, fictional sample brief and a local-only sample-request helper.

    HTML