Speaker: Pedro Gonçalves, VIB.AI and KU Leuven

Abstract: Mechanistic modeling aims to explain observed phenomena in terms of underlying causes, but identifying the parameters for which a model is consistent with complex and stochastic data is challenging. I will describe our recent developments in simulation-based inference allowing us to scalably retrieve the model parameters from data, and how we apply them to a range of neuroscience problems at the single neuron and neural circuit levels.

Short bio: Pedro Gonçalves is a Group Leader at VIB.AI and an Associate Professor at KU Leuven Departments of Computer Science and Electrical Engineering. He is also a member of KU Leuven ELLIS unit (European Laboratory for Learning and Intelligent Systems, https://ellis.eu/. Before starting his lab, Pedro did a postdoc with Maneesh Sahani at the Gatsby Unit, UCL, London, followed by a postdoc in Jakob Macke’s lab at the University of Tuebingen, Germany. His PhD was supervised by Christian Machens at Ecole normale superieure, Paris.

Pedro's lab works at the intersection between machine learning and computational neuroscience. More details at https://goncalveslab.sites.vib.be/en

Date & Time: Tuesday March 03, 2026 - 11am to 12pm

Location: 1.18, Building B28, Montefiore Institute