I build intelligent robots that interact with people and adapt to unforeseen situations. In particular, my research explores questions from early language acquisition to how communication improves collaborative manufacturing between humans and robots.
A thorough scientist and a creative problem solver, I am passionate about advancing robots' aptitude as our work partners and social peers. In addition to my background in machine learning, I am also a resourceful engineer with extensive experience on programming custom-made robots as well as commercial platforms.
Building intelligent robots that interact with humans and adapt to unforeseen situations is the aim of the fields of developmental and social robotics. This integrative endeavor combines prospect from many other domains, covering mathematics, computer sciences, and cognitive sciences. In particular, I use robots as tools to better understand the human mind, and take inspiration from knowledge about infants' cognitive development or human social interactions to improve robots' capabilities.
Understanding the mechanisms that underly the development of perceptual, motor, and linguistic abilities is my main subject of interest. I study these questions in the context of early language acquisition, learning by imitation, concept emergence, human-robot collaboration, and multimodal learning. More than each individual topic, I focus on similarities and interconnections between them.
I am currently a postdoctoral associate in the social robotics laboratory at Yale university. I completed my PhD in computer science within the Flowers team at INRIA Bordeaux under the supervision of Pierre-Yves Oudeyer. I am an alumni of École polytechnique and the MVA master (mathematics for vision and machine learning).
More detailed information is available on my résumé.