Host Institution: UCL
Duration: 36 Months
Contact person: François Glineur
Objectives: Develop a common framework to accurately describe first-order methods and their applicability to specific formulations or equivalent reformulations of optimization problems in data science, and predict the corresponding computational cost.
I was born and raised in Burgundy, France where I attended preparatory classes for engineering school to prepare entrance exams of French "Grandes Ecoles" (competitive engineering schools). In 2018, I enrolled in Grenoble INP Ensimag where I attended various applied mathematics courses. For my Master thesis, I visited the LCSL departement at University of Genova to work on accelerated first-order methods for kernel machines.
Motivation: During my studies, I had the chance to intern at various research facilities working on speeding up the resolution of large-scale learning problems. This field has a great variety of open research problems. This PhD is an excellent opportunity to tackle some of these problems within an international research environment.
Hobbies: I enjoy mountain hiking, football and voluntary teaching.