About

I am Florian Maillard, an engineer and PhD in engineering science. My work has covered scientific research, electrochemical systems, railway engineering, verification and validation, certification, data analysis, and technical documentation.

I use this website to turn practical work and research into durable, verifiable documentation.

Background

My academic training began with mathematics and physics in the French MPSI–MP preparatory programme, followed by an engineering degree from ENSI Poitiers and a PhD at the Pprime Institute.

My doctoral research investigated lithium-ion battery diagnosis through electrochemical-noise analysis. This work combined experimental electrochemistry, signal processing, feature extraction, and the physical interpretation of measured fluctuations.

My industrial experience has included batteries, verification and validation, and railway certification and authorisation. These fields differ in their objects, but they share a central problem: producing evidence strong enough to support a technical decision.

Areas of interest

  • electrochemical energy systems, especially batteries and fuel cells;
  • signal processing, modelling, and scientific computing;
  • systems engineering, requirements, traceability, and certification;
  • Python automation and reproducible technical workflows;
  • Debian GNU/Linux, Emacs, Org mode, and free software;
  • self-hosting, network security, and long-term preservation of knowledge;
  • open standards, interoperability, and digital autonomy.

Engineering approach

I value solutions that are physically justified, testable, maintainable, and understandable by someone other than their original author. In practice, this means making assumptions explicit, keeping units and data provenance visible, versioning code and configuration, and separating observations from interpretations.

Automation is useful when it removes repetitive work while increasing traceability. It is harmful when it merely hides an uncontrolled process behind another layer of software. The same applies to artificial intelligence: it can accelerate exploration and drafting, but engineering conclusions still need identifiable evidence and human accountability.

Why publish here

Most useful technical knowledge begins as scattered commands, experimental notes, scripts, discussions, and lessons learned after something failed. This site is where I consolidate that material into explanations that can be read, checked, and reused.

I do not aim for a fixed publication frequency. A smaller number of complete and maintained pages is more valuable than a stream of superficial updates.

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