Emmanuel Daucé is associate professor at the Ecole Centrale de Marseille, doing his research in Computational Neuroscience at the Institut de Neurosciences des Systèmes (France), a joint research unit (Inserm/ CNRS / Aix-Marseille Université). His research lies at the crosssroad of machine learning, artificial intelligence and neuroscience, seeking to develop innovative computational models and methods though remaining consistent with the principles of biological systems.

He graduated from the Ecole Nationale Supérieure d'Electronique, d'Electrotechnique, d'Informatique et d'Hydraulique de Toulouse (1995), and obtained a Ph.D in Knowledge Representation and Formal reasoning from the Ecole Nationale Supérieure de l'Aeronautique et de l'Espace (2000), under the supervision of Bernard Doyon (Inserm) and Manuel Samuelides (ISAE), on learning and plasticity in artificial neural networks with random recurrent connectivity graphs ( Daucé et al, 1998 ). He contributed to extend the model to multiple populations (Daucé et al. ,2001), and spatio-temporal sequence learning (Daucé et al., 2002).
He joined the Institut des Sciences du Mouvement in Marseille in 2001, where he contributed to develop neurally plausible reinforcement schemes in closed-loop control systems (Daucé, 2004, Daucé and Dutech, 2010), address spike-timing dependent plasticity in balanced networks of spiking neurons (Henry et al, 2006, Daucé, 2014) and develop models of dynamic retention in discrete neural-fields (Daucé, 2004).
He more recently joined Viktor Jirsa's group at the Institut de Neurosciences des Systèmes, at the Faculté de Médecine de La Timone (Marseille), where he contributed to develop on-line learning methods for non-stationary data streams - adapted to the case of Brain Computer Interfaces (Daucé and Thomas, 2014), and participated in modelling brain non-stationarities with simple neural-mass dynamics on large-scale connectivity graphs (Golos et al., 2015).