Neural Data

The neural basis of cognition is not going to be solved by maths alone. We need rich behavioural data and flourishing collaborations between experimentally and theoretically minded folk. In this session, talks will explore new and exciting neural data—whether it be fMRI, electrophysiology, or otherwise—that may or may not yet have an explanation, with a particular focus on data that points to new computational paradigms in brain processing.

• Dr Valeria Fascianelli (Zuckerman Institute, Columbia)
• Dr Francesca Mignacco (Princeton)

• Professor Wolfgang Maass (Technische Universität Graz)
• Professor Eve Marder (Brandeis University)

• Professor Alex Cayco-Gajic (ENS)
• Dr Jenelle Feather (Flatiron Institute)
• Dr. Joao Barbosa (Institute for Neuromodulation)
• Dr. John Vastola (Harvard University)

• Isabel M Cornacchia (University of Edinburgh)
• Philipp Werthmann (Institute for Neuromodulation)
• Rajat Saxena (Norwegian University of Science and Technology)
• Svenja Küchenhoff (University of Oxford)
• Alon Baram (University of Oxford)
• Ruben Tammaro (University of Tübingen, Germany)

Neural Theory

While neuroscientists have increasingly powerful deep learning models that predict neural responses, it is not clear that these models are correspondingly increasing our understanding of what neurons are actually doing. In this session, we will take a more mechanistic approach to understanding how networks of neurons afford complex computations, both by considering mechanistic neural models along with mathematical theories that say how neurons should behave and crucially why they behave that way.

• Dr James Whittington (University of Oxford; Stanford University)
• Yasmine Ayman (Harvard)

• Professor Christine Constantinople (New York University)

• Dr Juan Gallego (Imperial)
• Professor Vijay Namdoodiri (Weill Institute for Neurosciences, UCSF)
• Professor Annegret Falkner (Princeton Neuroscience Institute)
• Dr Francesca Migancco (Princeton University)
• Dr Valeria Fascianelli (Columbia)
• Dr Chris Hillar (New Theory AI)

• Jesseba Fernando (Northeastern University)
• Albert Albesa Gonzalez (Imperial College London)
• Dr Alexander Rivkind (Cambridge)
• Joseph Warren (Sainsbury Wellcome Centre - UCL)
• Samuel Liebana (UCL)

Cognitive Science

How should an intelligent agent behave in order to best realize their goals? What inferences or actions should they make in order to solve an important computational task? Cognitive science aims to answer these questions at an abstract computational level, using tools from probability theory, statistical inference and elsewhere.

In this session we will discuss how such optimal behavior should change under different conditions of uncertainty, background knowledge, multiple agents, or constraints on resource. This can be used to understand human behavior in the real world or the lab, as well as build artificial agents that learn robust and generalizable world models from small amounts of data.

• Dr Ruairidh Battleday (Harvard/MIT)
• Dr Colin Conwell (Harvard/MIT)

• Dr Kim Stachenfeld (Google DeepMind)
• Dr Ida Momennejad (Microsoft Research)

• Professor Bonan Zhao (Edinburgh)
• Professor Lisa-Marie Vortmann (University of Groningen)
• Dr Mathias Sablé-Meyer (Harvard / MIT)
• Dr. Dan Nicolau (King's College)
• Professor Eran Eldar (Hebrew University of Jerusalem)

• Aslan Satary Dizaji (University of Michigan)
• Ishan Kalburge (University of Cambridge)
• Kai Sandbrink (University of Oxford)
• Dr Paxon Frady (UC Berkeley)
• Li Wenjie (Carnegie Mellon Univeristy)
• Dr Anita Keshmirian (Forward College Berlin)

Artificial Intelligence

Machine learning and artificial intelligence (AI) aim to create algorithms that solve difficult problems and simulate complex intelligent behavior. Many of these algorithms are based on findings and theory from the study of the brain and mind.

Recent rapid advances in these fields have seen the creation of algorithms and agents that can—finally—solve complex real-world problems across a wide range of domains. What are these advances and how can we take them further? What remains beyond their capacity and how can we overcome that? What might forever lie beyond their capabilities—or will anything?

• Michael Lepori (Brown University)
• Dr Ivana Kajic (Google DeepMind)

• Professor Jay McClelland (Director, Center for Mind, Brain, Computation and Technology, Stanford)
• Professor Juergen Schmidhuber (Director, KAUST AI Initiative)

• Dr Chen Sun (Google DeepMind)
• Dr Ivana Kajic (Google DeepMind)
• Dr Naomi Saphra (Harvard)

• Can Demircan (Helmholtz Munich)
• Professor Constantine Dovrolis (The Cyprus Institute / Georgia Tech)
• Dr Venkatakrishnan Ramaswamy (Birla Institute of Technology & Science Pilani)
• Andrea Albert (HUN-REN Wigner Research Centre for Physics)
• Domonkos Martos (HUN-REN Wigner Research Centre for Physics)
• Jack Brady (Max Planck Institute for Intelligent Systems)

Radisson Blu Resort & Spa, Split

Our venue is the gorgeous Radisson Blu Resort and Spa in Split.

The Radisson Blu is a 45 minute walk from the Old Town, or a 20 minute bus ride.

See below for information on booking rooms at the hotel with discounted prices.