People

Giuseppe Paolo is a Senior Research Scientist at Huawei Technologies France where he pursues research in machine learning and reinforcement learning. He received his Ph.D. in computer science from Sorbonne University in 2021. The Ph.D. was done at ISIR in Sorbonne University, under the supervision of Stéphane Doncieux, and at AI-Lab in Softbank Robotics Europe, under the supervision of Alban Laflaquière, with a focus on the intersection between evolutionary algorithms and reinforcement learning algorithm to tackle sparse rewards problems.

Giuseppe Paolo received his M.Sc. in Robotics, Systems and Control at ETH Zurich in 2018 and the engineering degree from the Politecnico di Torino in 2015. He also did two research internships at RAM-Lab at the Hong Kong University of Science and Technology and at IBM Research Zurich. 

Antoine Cully is Lecturer (Assistant Professor) at Imperial College London (United Kingdom). His research is at the intersection between artificial intelligence and robotics. He applies machine learning approaches, like evolutionary algorithms, on robots to increase their versatility and their adaptation capabilities. In particular, he has recently developed Quality-Diversity optimization algorithms to enable robots to autonomously learn large behavioural repertoires. For instance, this approach enabled legged robots to autonomously learn how to walk in every direction or to adapt to damage situations. 

Antoine Cully received the M.Sc. and the Ph.D. degrees in robotics and artificial intelligence from the Pierre et Marie Curie University of Paris, France, in 2012 and 2015, respectively, and the engineer degree from the School of Engineering Polytech’Sorbonne, in 2012. His Ph.D. dissertation has received three Best-Thesis awards.  He has published several journal papers in prestigious journals including Nature, IEEE Transaction in Evolutionary Computation, and the International Journal of Robotics Research. His work with Jean-Baptiste Mouret was recently featured on the cover of Nature (Cully et al., 2015) and received the "Outstanding Paper of 2015" award from the Society for Artificial Life (2016), and the French "La Recherche" award (2016).

Adam Gaier is a research scientist at the Autodesk AI Lab where he pursues basic research in evolutionary and machine learning and the application of these techniques to problems in design and robotics. He received masters degrees in Evolutionary and Adaptive Systems form the University of Sussex and Autonomous Systems at the Bonn-Rhein-Sieg University of Applied Sciences, and a PhD from Inria at the University of Lorraine -- where his dissertation focused on tackling expensive design problems through the fusion of machine learning, quality diversity, and neuroevolution approaches. His PhD work received recognition at top venure across these fields: including a spotlight talk at NeurIPS (machine learning), multiple best paper awards at GECCO (evolutionary computation), and a best student paper at AIAA (aerodynamics design optimization).