Thomas Bouvier

I collaborate with scientists to research, create, and optimize scalable, ML-accelerated pipelines that help answer broad scientific questions in X-ray science and materials discovery. I hold a PhD from Inria in High-Performance Computing (HPC) and am specialized in this field. In tandem with these efforts, I also work on low-level performance characterization on GPU platforms.

Research work

I am a PhD student at Inria de l’Université de Rennes, supervised by Alexandru Costan and Gabriel Antoniu. My research interests cover various aspects of continual learning workloads in distributed settings (HPC, clouds and edge devices). In 2022, I did a student appointment at Argonne National Laboratory, Chicago with Bogdan Nicolae, trying to scale such workloads on many GPUs. My research field could be referred to as “Systems for AI”.

I hold a degree in electrical engineering from INSA Rennes. In 2019, I did an internship at Snips, Paris working on the integration of an AI voice assistant on edge devices. I then joined Inria as an engineer to develop a software prototype which addresses the limitations of state-of-the-art storage solutions for stream processing.

Publications

Check out my profiles at HAL, ORCID, OpenAlex, Scholar.

Conference papers

Journal papers

PhD dissertation

Teaching

Research projects

I participated in the ACROSS project, UNIFY Associate Team, JLESC Towards CL at Scale, PEPR Cloud.

Duties

I am a member of Sciences, Environment and Society group in Rennes: we are questioning our research areas in the light of current and future climate challenges. Besides, I have reviewed 10+ papers for IEEE IPDPS, ACM/IEEE CCGrid, ACM/IEEE Supercomputing, IEEE Big Data, ACM HPDC, Springer Computing journal.