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Andrew Mary Huet de Barochez

Ph.D Student at LISTIC

Andrew Mary Huet de Barochez is a Ph.D student in computer science at Université Savoie Mont-Blanc at the LISTIC laboratory, France. Its thesis topic concerns the energy consumption optimization of machine learning frameworks in heterogeneous platforms. This work is supervised by Stéphan Plassart and Sébastien Monnet. Before that, he studied at Polytech Annecy-Chambéry and obtained an engineer's degree (equiv. Master of Science in Engineering). His research interests include energy optimization, parallel computing, distributed systems, and heterogeneous systems.

Projects

Current work involves developping DAHL, a machine learning framework focusing on energy efficiency for heterogeneous hardware. On-going progress can be viewed in the Lab page.

Previously, a Federated Learning simulator called Falafels was developped during a previous internship. However the project has been archived and is no longer developped. See the publication and associated talk bellow for more details.

Publications

• Falafels: A tool for Estimating Federated Learning Energy Consumption via Discrete Simulation.
  A. Mary Huet de Barochez, S. Plassart, S. Monnet, AINA 2025.

Talks

• DAHL: Energy-Efficient Machine Learning on Heterogeneous CPU using Task-based Programming.
  Showing first results concerning DAHL.
  French computer science conference in Parallelism, Architecture and Systems (COMPAS 2026).
• Towards sustainable and resilient AI: frugal and energy-aware distributed machine learning platforms.
  Continuity of work regarding Falafels, and introduction to DAHL.
  GDR RSD / ASF Winter School on Distributed Systems & Networks (Winter School 2026).
• Falafels: A tool for Estimating Federated Learning Energy Consumption via Discrete Simulation.
  Presenting my work on Falafels.
  The 39th International Conference on Advanced Information Networking and Applications (AINA 2025).

Teaching

• Networks and Distributed Systems (28h), Practical work (TD).
  Practicing networks configuration on Virtual Machines using Kathará: Routing, Proxy, Firewall.
  Engineer degree in Computer Science, 2nd year.
• Operating Systems (35h), Practical work (TD/TP).
  Teaching systems and linux basics: Binary, File Systems, Bash, X86 Assembly.
  Higher school preparatory classes, 1st year.
• Behavior and Dynamic Modeling (48h), Practical work (TP).
  Deepening Object Oriented Programming knowledge: Design Patterns, UML, Java.
  Engineer degree in Computer Science, 2nd year.
• Large scale Distributed Systems (28h), Practical work (TP).
  Managing projects to implement a Distributed Hash Table (DHT): Discrete event simulation, Java, Python.
  Engineer degree in Computer Science, 2nd year.
• Algorithmic and Data Bases (24h), Practical work (TP).
  Introduction to programming and databases to a novice audience: C, Python, SQL.
  Masters work-study students, 1th year.