PUBLICATIONS & KNOWLEDGE SHARING

Scientific articles, books and training

A selection of my scientific articles, writing projects and training courses.

20+peer-reviewed journal publications
14+conferences
All my publications on Google Scholar

A selection of recent articles

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2026JOURNAL ARTICLE

Progress in Additive Manufacturing

Predicting interlayer bond strength in FDM-printed PETG parts: an experimental and machine-learning study

André Chateau Akué Asséko, Adélaïde Leroy, Benoît Cosson

2024JOURNAL ARTICLE

Journal of Advanced Joining Processes · 10, 100252

Characterization and modeling of laser transmission welded polyetherketoneketone (PEKK) joints: influence of process parameters and annealing on weld properties

Marcela Matus-Aguirre, Benoît Cosson, Christian Garnier, Fabrice Schmidt, André Chateau Akué Asséko et al.

2024JOURNAL ARTICLE

Journal of Advanced Joining Processes · 9, 100186

Investigating laser intensity profile and light scattering effects in the transmission laser welding process of 3D printed parts

Thi-Ha-Xuyen Nguyen, André Chateau Akué Asséko, Anh-Duc Le, Benoît Cosson

Generative AI in scientific and technical work

A scientist checks sources, data analyses and documents produced using generative AI.ARTICLE SUBMITTED

Techniques de l’Ingénieur

Effectively integrating generative AI into scientific and technical work

An article on integrating generative AI into scientific and technical activities.

Forthcoming publication · Date not announced
ACADEMIC YEAR2026–2027First semester
DOCTORAL TRAINING · UNIVERSITY OF LILLE

Responsible use of AI in research

A doctoral training course at the University of Lille, planned for the first semester of the 2026–2027 academic year, focusing on the responsible integration of AI into research activities.

Discuss this course

MY BOOK PROJECTS

Three books to understand and use AI

Click a cover to discover the book.

Build an AI strategyExplore the five-step approach
UNDERSTAND · CHOOSE · IMPLEMENT

Integrating AI into your work responsibly

Building an AI strategy starts with your work: what would you like to improve?

Understanding what AI can do and where it goes wrong, identifying useful applications, preparing data and organising human oversight: I develop a step-by-step approach to move from a concrete need to considered and evaluated use.

Human–AI cooperation: questioning, analysing and verifying results
AI provides support. Humans define the goals, verify results and retain responsibility for decisions.
  1. Understand AI

    Discover how it works, its capabilities and its limitations, to understand what can be entrusted to it and what needs checking.

  2. Start with your needs

    Define what you want to improve, identify practical uses and choose an initial task suited to your resources.

  3. Prepare your resources

    Check the availability and reliability of data, choose tools and develop the necessary skills.

  4. Establish rules for use

    Protect people and their information, clarify responsibilities and set boundaries for actions entrusted to AI.

  5. Test and improve

    Experiment within a limited scope, compare results with and without AI, then adjust before using it regularly.

This content is being prepared and will be added in a future update.

Titan

An initial idea. A practical approach.

Titan is getting ready…