Houssem SaidiParis
I bring new technology into maintenance work and stay with it until it holds up in production.
I head the Industry 5.0 Lab at Berger‑Levrault, a French software publisher. I wrote the 2026–2030 research and innovation roadmap for its maintenance software business unit and I run it; hiring, budget and doctoral supervision for the lab’s researchers, engineers and PhD students sit with me. I work with group product leadership on how to bring AI into the product without rewriting its core.
The technology depends on the problem: a generative-AI assistant connected to the CMMS, a technician scheduling optimiser taken to market, augmented and assisted reality for field technicians, spare-parts optimisation in which every recommendation is checked by simulation.
I hold a PhD in computer science from the University of Toulouse, in human‑computer interaction, an engineering degree and MSc in interactive systems and robotics, and an MSc in artificial intelligence. I have published at ACM CHI, the leading venue in the field, and work with Inria and CNRS.
Selected workWhere each piece stands
Two products on the market, a paid MVP in use on site, an assistant going to market and a programme moving to proof of concept. The line marks the stages I carried each one through; a hollow marker means that stage is under way.
Augmented remote assistance
From an idea to a product clients pay for, with an industrialisation budget won from management.
More detail
Prototype, client trials, a proof of concept tested hard enough to show real interest, a first paying client, then an industrialisation budget won from management. I stayed on through industrialisation as the domain expert.
Technician scheduling optimiser
Builds maintenance technicians’ schedules. Taken from proof of concept to commercial product under my responsibility.
More detail
The lab took it from proof of concept to commercial product under my responsibility, and a first paying client runs it in production.
Augmented-reality maintenance assistant
From the first idea to a paid MVP on manufacturing sites, then an assisted-reality mode on lightweight glasses.
More detail
Product lead on an AR assistant connected to the CMMS. Field evaluations with technicians and storekeepers showed that spatial anchoring mattered little for most of their tasks, which led me to specify an assisted-reality mode on lightweight glasses, ahead of the HoloLens and Magic Leap end of life. Certification kept blocking defence and public-utility sites, so I designed around it: the glasses run as a passive display driven from a device the client has already certified.
Generative-AI assistant for maintenance
Answers from the client’s own technical documentation and works inside the CARL Source CMMS.
More detail
I ran the user-discovery sessions at client sites. Industrialisation was co-piloted with the product teams, who own the CMMS side, while my team built the maintenance layer on a data pipeline from a sibling AI lab. I also supervise the smart-glasses track, which puts the assistant in front of technicians hands-free.
Spare-parts optimisation
Forecasting and operational research, with every recommendation checked by simulation before anyone applies it.
More detail
I found the subject in an upstream study and argued it onto the roadmap at high priority. Three prototypes run as APIs, validated on seven years of a public operator’s data. Next comes a proof of concept that end users can test.
Our work doesn’t end once a product is on the market. On the CMMS’s map and 3D asset module, we support the product team and keep innovating around it: we revisited how users interact with 3D models, and started work on querying them in natural language.
Deployed with clients in food processing, retail, semiconductors, industrial equipment and public utilities.
Industrialisation means building a product out of the proof of concept or MVP. On the market means it is sold to clients.
Expertise
Fields I know first-hand, from the work above.
AI in mature industrial software
How to bring AI into a product with a long installed base without rewriting its core, and how to move the work from a lab into product teams.
Optimisation for maintenance
Technician scheduling and spare-parts decisions, with simulation to check a recommendation before it reaches the field.
Generative AI on maintenance data
Assistants that answer from a client’s own documentation and act inside the CMMS.
Augmented and assisted reality
From head-worn AR to lightweight glasses, including what certification allows on sensitive sites.
Field evaluation with technicians
Discovery and evaluation sessions with technicians and storekeepers on client sites, using the methods of human-computer interaction research.
Publications
Interaction techniques for exploring complex data in large display spaces
Doctoral thesis, University of Toulouse III, 2018. Supervised by Emmanuel Dubois and Marcos Serrano.
Read the thesis- 2022BL.MixedR: Augmenting Traditional Maintenance Procedures to Better Exploit the Capabilities of Head-Worn ARPETRA ’22, ACM
- 2021HoloBar: Rapid Command Execution for Head-Worn AR Exploiting Around the Field-of-View InteractionACM CHI 2021
- 2019On-Body Tangible Interaction: Using the Body to Support Tangible Manipulations for Immersive EnvironmentsIFIP INTERACT 2019, Springer
- 2017TDome: A Touch-Enabled 6DOF Interactive Device for Multi-Display EnvironmentsACM CHI 2017
Education
- University of Toulouse III Paul Sabatier, IRITPhD, computer science (human‑computer interaction)2018
- UPSSITECH, University of Toulouse IIIEngineering degree and MSc, interactive systems and robotics2015
- USTHB, AlgiersMSc, artificial intelligence (intelligent computer systems)2012
Career
- 2024Head of the Industry 5.0 LabBerger-Levrault, R&D and Technology Innovation division
- 2020R&D engineerBerger-Levrault
- 2018Research engineerIRIT, University of Toulouse III
- 2013Software engineerALGEOFLEET, Algiers. Maintenance-management and logistics-tracking tools
Contact
Maintenance innovation, industrial AI, or a project you are still scoping. I read everything and answer in French or English.
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