Here are, in no particular order, a few of my research interests and some projects I have enjoyed working on.

Engineered Living Material

Postdoc, MIT, 2018 - 2019

This is currently my main research project and my first as a Postdoctoral Associate, on which I am working under the direct supervision of Prof. Neri Oxman and in close collaboration with Profs. Christopher Voigt, Cullen Buie, and Timothy Lu. The ambitious goal of this project is to program and simulate the growth of a multicellular aggregate, compile the virtual genotype of the simulated organisms into real DNA, and subsequently implant this into real cells. At present, the model organism of interest is Escherichia coli.

We want to be able to design a phenotype and have the program output the corresponding DNA code (genotype).

I have developed a specialized agent-based simulation engine, a logic-gate based virtual gene regulatory network and a machine learning framework that heavily relies on evolutionary algorithms. The machine learning part is particularly fascinating, as it applies to both the calibration of the simulation (trying to reduce the reality gap) and the inverse problem (finding the correct genotype for a desired phenotype).

  • Viva in Silico: A position-based dynamics model for microcolony morphology simulation.

    Artificial Life Conference, 2018
  • + journal article soon

MecaCell & Cell Physics Simulation

2014 - 2019

Since a considerable amount of my research required state of the art cell physics simulation, I developed a specialized cell physics engine. MecaCell is an open-source platform for the agent-based simulation of cells, with a strong focus on modularity and performance. Depending on the core physics model used, it is able to handle several millions of cells on a conventional CPU. It is a lightweight platform designed with artificial life and morphogenetic engineering in mind. It has been in use throughout most of my PhD and for my current Postdoc - and it keeps getting better.

  • MecaCell: an Open-source Efficient Cellular Physics Engine

    Artificial Life Conference, 2015
  • Viva in Silico: A position-based dynamics model for microcolony morphology simulation.

    Artificial Life Conference, 2018
  • Learning Aquatic Locomotion with Animats

    ECAL, 2017
  • MecaCell on github

Artificial Gene Regulatory Networks

University of Toulouse, 2014 - 2018

I have used and researched better representation of aGRNs both as cell controllers (for cell cycle regulation) and as controllers for more abstract problems (for example, in this video, a GRN was evolved to control a ship).

This research gave insights on the dynamics of these complex systems and allowed for interesting improvements and variations in their design, encoding, and evolvability.

  • A comparison of Genetic Regulatory Network Dynamics and Encoding

    GECCO, 2017
  • Dangerousness Metric for Gene Regulated Car Driving

    Evostar, 2016
  • Artificial Gene Regulatory Networks for Agent Control

    Evolutionary Computation in Gene Regulatory Network Research
  • Investigating Artificial Cells’ Spatial Proliferation with a Gene Regulatory Network

    Procedia computer science, 2017

Genetic Algorithm Framework

University of Toulouse, 2014 - 2018 + MIT, 2018 - 2019

My research led me to use a wide variety of evolutionary computations & genetic algorithms that, in some cases, required a degree of customization and versatility that I didn't find in other libraries. I've thus put everything together in a fun modern C++ project that keeps growing.

github logo

Self Assembly of cells through differential adhesions

EPFL, 2016

This is a soft robotics research project I worked on while a visiting PhD student at EPFL in Pr. Dario Floreano's team. By letting each deformable cell unit define its adhesion pattern, unconnected cells can, through random motion, assemble into desired geometric structures, such as the formation of snowflakes patterns.

Evo-Devo Research

University Of Toulouse, 2015 - 2018

Starting from a single cell with identical local rules governing communication, growth, and specialization, a varied panel of morphologies can develop. These environmental rules and cell controllers can be discovered and explored through various evolutionary computation tools. In many of this research and experiments, virtual creatures are composed of cells housing an artificial Gene Regulatory Network (GRN). The GRN is evolved in order to favor the organisms that would best fit their environment and its energy constraints.

One of my main interest in this area is in studying how very simple fitness functions make for the emergence of complex phenotypes. For example, in a series of experiments that I did during my PhD, the organism only have to "survive"; the complex phenotypes and life-like behaviors emerge from the simulation constraints (mostly related to energy). Here, an example of growth and auto-organisation into shells (nutritive cells feeding a shield of very resistant cells), and another example showing the emergence of roots and leaves (to produce energy from simulated sunlight and nutrients buried in the ground).

  • Self-organization of symbiotic multicellular structures

    Artificial Life Conference, 2014
  • Evolved developmental strategies of artificial multicellular organisms

    Artificial Life Conference, 2016
defensive and nutritive cells organized in clusters


French Robotics Cup team in Toulouse, 2015 - 2019

This is more of a hobby than a "true" research project, but, to me, being a part of such a great robotics team was an invaluable opportunity to apply and improve my electronics skills, as well as some computer vision and planning algorithms.

I have designed, from scratch, the electronics of the two robots of our team that had to compete in the french robotics cup. I also wrote some low-level code and helped with computer vision algorithms. Overall, this was an incredible experience, especially since we have had excellent results (Innovation Price in 2016, First Runner-Up in 2017 and 2019, and 3rd at the European Robotics Cup in 2017).

electronics cards I designed for the robots

Applications to Cancer simulation + Evolutionnary dynamics of the immune system

University of Toulouse + ITAV & INSERM - 2015 - 2016

My cell simulation software has been used to model tumor spheroids and study the formation of a necrotic core due to various constraints (oxygen & nutrient depletion and mechanical constraints mostly). Combining this software with evolutionry computations, I have also helped with the simulation of the evolutionary dynamics of the "arms race" between the immune system and melanoma.

spheroid tumor