Elena Vanneaux - Research

Main Collaborators

I have the pleasure of working with passionate and inspiring students:

PhD Students

Mathis Fleuriel (since January 2025). Co-supervised with Olivier Simonin.
Funding: project ANR VORTEX.
Thesis Title: Graph-based Collaborative Exploration with a Swarm of Drones.
Béatrice Garcia Cegarra (since April 2025). Co-supervised with David Filliat and Quentin Picard.
Funding: a scholarship from AMIAD Center.
Thesis Title: Hierarchical Control for Drone Swarms in Adversarial Environments.
Yacine El Yamani (since Octobre 2025). Co-supervised with Goran Freshe and Hanna Krasowski.
Funding: a scholarship from F4C Center.
Thesis Title: Predictive Safety Shields for Reinforcement Learning Agents.

Former Students of Mine

Master Students

Diego Fleury De Moraes (June - August 2025). Co-supervised with Goran Freshe.
M1 Thesis Title: A Study on Reversibility in Automata, Reinforcement Learning, and Dynamical Systems.
Yacine El Yamani (March - August 2025). Co-supervised with Hanna Krasowski.
M2 Thesis Title: Predictive Safety Shields for Reinforcement Learning Agents in Multi-Agent Scenarios.

The results of the internship has been accepted at IFAC WC 2026! Nice start for your Ph.D., Yacine!

Pin Jin (June - August 2024). Co-supervised with Hanna Krasowski.
M1 Thesis Title: Predictive Safety Shield for Dyna-Q Reinforcement Learning.

The results of the internship has been presented at ECC2025! Good job, Pin!

Mathis Fleuriel (March 2024 - August 2025). Co-supervised with Olivier Simonin.
M2 Thesis Title: Graph-based Collaborative Exploration with a Swarm of Drones.

The results of the internship has been presented at ECMR2025! Congratulations, Mathis!

Current Projects

I am currently involved in the following projects:
ANR VORTEX: Vision-based Reconfigurable Drone Swarms for Fast Exploration (2023-2027)

Coordinator: Olivier Simonin

My role: M2 intern adviser, co-adviser of Ph.D. student (since 2024)

Partners: CITI, ENSTA Paris, Lab-STICC, LS2N, ONERA

Description: The project proposes a new approach to exploring unknown indoor environments using a fleet of autonomous drones (UAVs). We propose to define a strategy based on swarm intelligence that exploits only vision-based behaviors. The fleet will deploy as a dynamic graph and self-reconfigure according to events and discovered areas. Without requiring mapping or wireless communication, the drones will coordinate by mutual perception and communicate by visual signs. This approach will be developed with RGB and event cameras to achieve fast and low-energy navigation. Performance, swarm properties, and robustness will be evaluated by building a demonstrator extending a quadrotor prototype developed by the consortium.

Former Projects
The projects I have been involved in the past:

ANR TRAITS: Trustworthy AI through Propagating Sets (2021 - 2024)

Coordinators: Goran Freshe and Matthias Althoff

My role: M1 intern adviser, co-adviser of Ph.D student (2022-2024)

Partners: ENSTA Paris (ENSTA), TU Munchen (TUM)

Description: The project focuses on developing a monitoring module to control systems using "black-box" algorithms. These algorithms are particularly suited to dynamic systems where unpredictable interactions make traditional modeling difficult, such as in autonomous vehicles or robotics. This project explores reinforcement learning (RL), an approach where agents learn based on their interactions with the environment, but which raises safety concerns. To address this challenge, a new method based on deterministic abstractions has been implemented, ensuring that agents comply with safety specifications while simplifying the synthesis of alternative controls if the agent's proposed control does not meet the specification. This approach thus enhances the reliability and safety of autonomous agents.

AID FARO: Le projet Fondements des Algorithmes de RObots en essaims (2021-2025)

Coordinator: Eric Goulbaut

My role: Researcher postdoctoral (2021-2022)

Partners: Ecole Polythehnique, ENSTA Paris, Telecom Paris, ENSTA Bretagne

Description: The FARO project focuses on the development of new algorithms (model-driven and/or data-driven) and new validation methods to ensure the proper functioning of drones in swarms, on land, in the air, or at sea.

ERC PROCSYS: Towards Programmable Cyber-physical Systems: a Symbolic Control Approach (2017-2023)

Coordinator: Antoine Girard

My role: Ph.D. Student (2018-2021)

Partners: CNRS

Description: The PROCSYS project develops a high-level CPS language based on hybrid automata, enabling rich behavior specification and efficient controller synthesis. It addresses symbolic control challenges: scalability through parsimonious models and lazy synthesis and robustness via novel symbolic controller methods. The project advances distributed CPS contract design, data-driven abstraction, and symbolically guided predictive control.

Main Collaborators

Current Projects

Former ProjectsThe projects I have been involved in the past:

Former Projects
The projects I have been involved in the past: