CV

PhD student in computer science

Lyon, France

My thesis tackles polyhedral compilation, in the context of sparse inputs

• Polyhedral compilation, compilers, sparse matrix

Intern at Kalray

Grenoble, France

Integration of the TVM compiler on the MPPA manycore architecture

• ML compilers, FPGA, Inference

Research intern at Inria

Lyon, France

Development of a compiler pass for scalar promotion using the Polyhedral model. Work later published at COMPAS'22

• Polyhedral compilation, scalar promotion, register pressure

Research intern at Aston University

Birmingham, United Kingdom

Development of a scientific tool simulating Taylor–Couette flows

• Navier Stokes approximation, BLAS

PhD

Ecole Normale Supérieure de Lyon

Computer science

• Automatic Specialization of Sparse Program for Machine Learning and HPC

Master

Ecole Nationale Supérieur d'Informatique pour l'Industrie et les Entreprises

Computer science

• High Performance Computing

Automatic Specialization of Polyhedral Programs on Sparse Structures

15th International Workshop on Polyhedral Compilation Techniques (IMPACT'25)

This paper presents an algorithm to specialize a dense polyhedral program on sparse inputs. Our approach is able to propagate the input sparse structure across the computation and to keep only the necessary computations computing non-zero values.

A Polyhedral Approach for Scalar Promotion

Conférence francophone d'informatique en Parallélisme, Architecture et Système (COMPAS 2025)

In this paper, we address array scalarization, a technique to turn temporary arrays into a collection of scalar variables to be allocated to registers.