Adrien Sardi.
I’m a researcher at Nokia Bell Labs and a PhD student at Inria, working on generative AI models and energy management for 6G distributed networks.
Hi, my name is
About Me
I’m a researcher at the Nokia Bell Labs. My research focuses on generative artificial intelligence models and energy management/control of resources (GPU&CPU, bandwidth, memory) within 6G distributed networks. In parallel, I am also a PhD student at the national research center for informatics in France (Inria) under the supervision of Dr. Frédéric Giroire, Dr. Sara Alouf and Dr. Joanna Moulierac as part of an industrial thesis agreement between the two labs.
Before my PhD, I graduated from ENSTA Paris and École Polytechnique, two of the top French Engineering Schools. Passionate about research topics, modelisation and problem solving, I completed my final year of engineering studies at ENSTA with a specialization in Applied Mathematics. In parallel, I took the joint master’s program at École Polytechnique and Université Paris Saclay: M.Sc. Applied Mathematics for Life Sciences.
I like to work on interesting projects so don’t hesitate to contact me!
Here are some of my research interests:- Mathematics
- Computer Science
- Energy Efficiency
- Machine Learning
- Generative AI
- Optimisation
News
I took part in the NPS Hackathon organized by Nokia NPS - Apr 2025
1st to 4th of April 2025
Experience
Jan 2025 - present
I am currently working as a researcher at Nokia Bell Labs.
Network Systems Security and Research Department
- Development of a method for estimating the energy consumption of an artificial intelligence model prior to its execution, in order to introduce energy as a new design metric for AI models.
- Design of approaches for energy-efficient optimization of computing resources in Edge-to-Cloud architectures.
- Prospects for application in AI model selection, network orchestration, and network standardization.
Apr 2024 - Sep 2024
I’ve worked as a quantitative analyst intern in the Risk Department of Société Générale, within the Climate Risk team.
- Development of physical risk assessment models. Measurement of the impact of a flood on the bank’s portfolio.
- Use of climate data and statistical modeling. Programming in R and Python.
- Teamwork with researchers, production of a research dissertation and an academic presentation.
I’ve worked as a research assistant for the UMR Génétique Quantitative et Evolution – Le Moulon joint research unit of AgroParisTech, INRAE, CNRS and Université Paris-Saclay. I was under the supervision of Dr. Tristan Mary-Huard and Dr. Laurence Moreau.
- Construction of a Machine Learning model for the prediction of varieties robust to environmental stresses based on their genotype.
- Advanced using of R for parameter inference by maximum likelihood (Torch).
- Teamwork with researchers, production of a research dissertation and an academic presentation.
May 2022 - Aug 2022
I’ve worked as a research assistant at the Department of Mathematics of the University of Pavia, under the supervision of Dr. Andrea Moiola and Dr. Emile Parolin.
- Working independently, developing new theoretical results in numerical analysis.
- Developing a new mathematical tool in Julia.
- Writing a research thesis and presenting my results in front of an academic jury.
Education
Jan 2025 - present
Ph.D. in Computer Science
Université Côte d'Azur & Inria- Subject: Generative artificial intelligence models and energy management of resources within 6G distributed networks.
- Development of statistical models and software tools to predict and optimize the energy consumption of AI models. Advisors: Dr. Frédéric Giroire, Dr. Sara Alouf and Dr. Joanna Moulierac.
2023 - 2024
M.Sc. in Applied Mathematics
Ecole Polytechnique- Graduated with honors, supervised by Dr. Sylvie Meleard and Dr. Camille Coron.
- Master’s thesis: “Identification of Plant Varieties Robust to Environmental Stress.”
2020 - 2024
M.Eng.Sc. in Applied Mathematics
ENSTA ParisFrench Engineering degree, specialized in Applied Mathematics with comprehensive knowledge across various mathematical domains:
- Probabilities (Stochastic calculus, Martingales, Markov chains),
- Advanced statistics,
- Optimization,
- Numerical Analysis
- Parallel Computing,
- Computer Science.
Teaching
Continuous Optimization: Theory and Algorithms II
Teaching Assistant, M.Sc. program at ENSTA Paris — Winter 2026.
Continuous Optimization: Theory and Algorithms I
Teaching Assistant, M.Sc. program at ENSTA Paris — Fall 2025. The course covers advanced topics in continuous optimization, including convex analysis, duality theory, and algorithmic strategies for solving large-scale optimization problems.
Get in Touch
I like to work on interesting projects so don’t hesitate to contact me!