2023 Complexity-GAINs students & faculty

Program Overview

Intelligence reflects a capacity for decision-making and action that is accurate, consistent, and adaptive with respect to reality. A prerequisite for, and arguably the core of, intelligence, therefore, is an accurate mental representation of the real world. How are such representations encoded? While neuroscientists focus increasing effort on understanding encoding in the activities of neurons, the recognition of intelligence in artificial neural networks and animal and human collectives raises key questions about the nature of representation beyond neuronal substrates. The Intelligence & Representation summer school will analyze and extend modern empirical and mathematical theories of representation across diverse intelligent systems, with the aim of uncovering generalizable, universal principles of representation. Ph.D. students will spend two weeks, among an international cohort of students and faculty, addressing key open questions in the nature of representation, including methodological advances and challenges. Students will acquire tools to apply in their own research. A key element of this school is to give the same weight to the origin or creation of representations and coding as is given to matters of inference. Specific topics to be covered include: brain and cognition, definitions of intelligence, and knowledge systems. This program aligns with SCGB goals in developing an integrated understanding of cognition at the level of Principles & Systems, and strengthens a diverse and global research community working towards these goals.. This program took place August 13 to August 25 in Cambridge, UNITED KINGDOM.


Group Projects



Stavros Anagnou


University of Hertfordshire (UK)


Nathaniel Imel


University of California, Irvine (US)


Jessica Dai


University of California, Berkeley (US)


Robin Na


Massachusetts Institute of Technology - MIT (US)


Haoxue Fan


Harvard University (US)


Virginia Ulichney


Temple University (US)




Polyphony Bruna


University of California, Merced (US)


Fionn O'Sullivan


Trinity College Dublin (IE)


Julie Hayes


University of New Mexico (US)


Jesse van Oostrum


Hamburg Institute of Technology (DE)


Nana Obayashi


Ecole Polytechnique Federale de Lausanne (CH


Daria Zakharova


London School of Economics and Political Sciences (UK)




Caitlin Mace


University of Pittsburgh (US)


Marie Teich


Max Planck Institute for Mathematics in the Sciences (DE)


Nana Obayashi


École Polytechnique Fédérale de Lausanne (CH)


Fan Ye


University of Cambridge (UK)




Ben Lipkin


Massachusetts Institute of Technology - MIT (US)


Scott Wilson


University of Cambridge (UK)


Charlotte Merzbacher


University of Edinburgh (UK)


Chase Yakaboski


Dartmouth College (US)




Sydelle de Souza


University of Edinburgh (UK)


Sara Varetti


Scuola Internazionale Superiore di Studi Avanzati (IT)


Ata Karagoz


Washington University in St. Louis (US)


Maren Wehrheim


Goethe-Universität (DE)


Mitchell Ostrow


Massachusetts Institute of Technology - MIT (US)




Valentin Forch


Technische Universität Chemnitz (DE)


Cody Moser


University of California, Merced (US)


Jack Goffinet


Duke University (US)





David Krakauer

Guest Faculty & Teaching Fellows

Nyhat Ay • information geometry | Erica Cartmill • social cognition | Maell Cullen • theoretical neuroscience | Jacob Foster • evolutionary dynamics of ideas | John Krakauer • motor learning & memory representations | Melanie Mitchell • artificial intelligence systems |  Orit Peleg • biological communication signals

Program News

Apply now for Complexity–GAINs International Summer School (from SFI)
Recap: Complexity-GAINs International Summer School (from SFI)
Complexity-GAINS : The first SFI–CSH summer school has started (from Complexity Science Hub Vienna)
Complexity-GAINS : Toward a multifaceted and integrative science (from Complexity Science Hub Vienna)

This program was made possible through the support of the National Science Foundation under Grant No. 2106013 (PI David Krakauer), IRES Track II: Complexity advanced studies institute - Germany, Austria, Italy, Netherlands (Complexity-GAINs). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the investigator(s) and do not necessarily reflect the views of the National Science Foundation.