Computation and Cognition Conference 2025

Join us for CCC 2025

If you're looking for opportunities to share your research on the intersection of cognition, AI, and neuroscience, or if you want to connect with peers, network with potential collaborators, and engage with new ideas, join us for the Computation and Cognition Conference in Halifax on August 15 2025.

The conference provides a forum for researchers in cognitive science, neuroscience, and AI, focused on understanding the computations that underlie behavior. Our goal is to deepen and strengthen the interactions between our disciplines, and to discover the ways in which each research community can benefit from the successes of others.

We encourage participation from engineers, experimentalists and theoreticians investigating brain and behaviour in humans and animals. Our discussions will cover research in the following areas, as well as many others:

Understanding commonalities and differences between biological and AI systems
Using techniques from ML and AI to model brain and behaviors, and building biologically-inspired AI
Understanding how people reason in real-world tasks through the lens of computation
Measuring and expanding the representational competencies of modern AI systems
Mechanistic interpretability of deep neural network models and the science of deep learning
Revealing principles of brain connectivity and dynamics at multiple scales
Using psychophysical techniques to relate sensory inputs to behavioral responses
Developing cognitive- or neural-level models of perception, cognition, emotion, and action
Representation learning and representational alignment

We will have an exciting lineup of invited speakers, a poster session for students and faculty, and several parallel workshops. This event is open to all, whether you’d like to present a poster, network, or simply attend and enjoy the conversations. Everyone is invited to join us and be a part of this exciting interdisciplinary exchange!

Call for Posters

Poster spots are assigned on a first-come, first-served basis, with a set number reserved per CS and Psychology. Confirmed presenters will receive further details, including poster dimensions. To help up plan and allocate space for your posters, we need to have your poster abstract in advance. There are two Best Poster Awards, chosen by the organizing committee.

June 15, 2025: Poster abstract submission opens
July 15, 2025: Poster abstract submission deadline

Invited Speakers

Dr. Kevin Ellis

Cornell University

Kevin Ellis is an Assistant Professor in the Computer Science Department at Cornell University. His research is focused on Neuro-Symbolic AI, Program Synthesis, and Cognitive Science, and integrates symbolic reasoning with neural networks to develop human-like learning from limited data in AI. Dr. Ellis completed his Ph.D. at MIT, where he was advised by Dr. Josh Tenenbaum and Dr. Armando Solar-Lezama. He is perhaps best known for the Dreamcoder paper.

Dr. Tianmin Shu

Johns Hopkins University

Tianmin Shu is an Assistant Professor in the Department of Computer Science at Johns Hopkins University, with a secondary appointment in the Department of Cognitive Science. His research advances human-centered AI by integrating machine learning, RL, and social psychology to develop engineering machine social intelligence. His work encompasses areas such as model-based Theory of Mind reasoning, social scene understanding, neurosymbolic methods, and social learning. He completed his Ph.D. in Statistics at University of California, Los Angeles.

Dr. Stephanie Denison

University of Waterloo

Stephanie Denison is a Professor of Psychology at the University of Waterloo. Dr. Denison primarily studies infant and child development from a cognitive science perspective, examining questions about the origins of the mind and the domain-general statistical learning mechanisms that young learners have access to, as well as how those interact with domain-specific learning mechanisms. She also examines the development of heuristics and biases, and how algorithmic strategies for updating information (such as variants of simple algorithms like “win-stay, lose-shift”) characterize children’s belief revision over time.

Venue

Kenneth C. Rowe Management Building,
Dalhousie University,
Halifax, Nova Scotia

Organisers

Marta Kryven, Assistant Professor of Computer Science, Psychology and Neuroscience (marta.kryven@dal.ca)

Aaron Newman, Professor and Chair, Psychology and Neuroscience, Computer Science, Psychiatry, Surgery, Pediatrics

Raymond Klein, Professor Emeritus, Psychology and Neuroscience, Computer Science

Simal Dolek, Graduate Student, Psychology and Neuroscience (simal.dolek@dal.ca)

Xijie Zheng, Graduate Student, Computer Science

Xuemin Yu, Graduate Student, Computer Science

Ryan McCarthy, Event Coordinator, AI Institute