Jean‐Luc Gaudiot

About

Jean-Luc Gaudiot is a pioneering figure in the design of heterogeneous computing architectures for real-time, energy-constrained autonomous systems. His research focuses on bridging the gap between high-performance computing and embedded systems, particularly for robotic vision and Simultaneous Localization and Mapping (SLAM) applications. Gaudiot’s major contributions include the development of runtime frameworks that dynamically manage task execution across diverse hardware—from mobile accelerators to cloud resources—to optimize both performance and energy efficiency. His flagship work, the Π-RT framework, enables robots to simultaneously perform autonomous navigation and other vision tasks with unprecedented energy savings, a breakthrough that has garnered 19 citations since 2021. He also introduced π-Hub, a large-scale video learning and retrieval system for heterogeneous platforms, and has advanced embedded system architectures specifically tailored for SLAM, the core technology behind autonomous vehicles and augmented reality. With a career spanning foundational work in computer architecture and a sustained focus on practical, deployable solutions, Gaudiot’s research directly impacts the next generation of intelligent, power-aware robotic systems.

Research Focus

Key Achievements

Top Papers

1. 1
   Π-RT: A Runtime Framework to Enable Energy-Efficient Real-Time Robotic Vision Applications on Heterogeneous Architectures

   19 citations · 2021
2. 2
   <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="d1e326" altimg="si6.svg"><mml:mi>π</mml:mi></mml:math>-Hub: Large-scale video learning, storage, and retrieval on heterogeneous hardware platforms

   4 citations · 2019
3. 3
   Embedded Systems Architecture for SLAM Applications

   3 citations · 2017

Key Collaborators

Contact & Links