Cooperative AI Events

Cooperative AI Summer School

Aims and Focus
The Cooperative AI Summer School is designed to provide students and early-career professionals in AI, computer science, and related disciplines with a firm grounding in the emerging field of cooperative AI.

The program for the summer school will range from the "foundations" to the "frontiers" of the field, with lectures delivered by those at the forefront of cooperative AI research. The foundational aspects of the program will explore the objectives and key concepts of cooperative AI, delving into the theoretical underpinnings of the main challenges and opportunities associated with improving the cooperative intelligence of advanced AI systems. Participants will also be exposed to cutting-edge developments on the frontiers of cooperative AI research, which build upon recent progress in areas such as language modelling and multi-agent reinforcement learning.

In addition, the summer school will provide the opportunity for participants to share their own work, and to build connections with others in, or entering, the field. The Cooperative AI Foundation is committed to the growth of a diverse and inclusive research community, and we especially welcome applications from underrepresented backgrounds. Further information about financial assistance for attendees can be found below.

Recordings of the lectures from our 2023 summer school can be found on the Cooperative AI Foundation's YouTube channel. The 2024 lectures will cover new topics, with the opportunity for participants to build a base of common knowledge ahead of the summer school through our Cooperative AI curriculum.

19 - 23 June 2024
Santa Cruz, US
Free / $350 / $700
26 April 2024
10 May 2024


Edward Hughes
Staff Research Engineer, Google DeepMind

Edward Hughes is a Staff Research Engineer at DeepMind. His research pioneers the field of Cooperative AI, algorithms that work in partnership with each other and humans. His work lies at a crossroads linking multi-agent reinforcement learning with sociology and economics. Edward received his PhD in Theoretical Physics from Queen Mary University of London on applications of string theory to particle scattering. He read Mathematics at Cambridge University, where he graduated with Distinction.

Edward’s publications are available on Google Scholar.

Noam Brown
Researcher, OpenAI

Noam Brown is a Researcher at OpenAI. Before that, he worked on multi-agent artificial intelligence at Facebook AI Research, with a particular focus on imperfect-information games. He co-created Libratus and Pluribus, the first AIs to defeat top humans in two-player no-limit poker and multiplayer no-limit poker, respectively. He has received the Marvin Minsky Medal for Outstanding Achievements in AI, was named one of MIT Tech Review's 35 Innovators Under 35, and his work on Pluribus was named by Science Magazine to be one of the top 10 scientific breakthroughs of the year. Noam received his PhD from Carnegie Mellon University, where he received the School of Computer Science Distinguished Dissertation Award.

Fei Fang
Assistant Professor, Carnegie Mellon University

Fei Fang is Leonardo Assistant Professor at the Institute for Software Research in the School of Computer Science at Carnegie Mellon University. Before joining CMU, she was a Postdoctoral Fellow at the Center for Research on Computation and Society (CRCS) at Harvard University, hosted by David Parkes and Barbara Grosz. She received her Ph.D. from the Department of Computer Science at the University of Southern California advised by Milind Tambe (now at Harvard). Her research lies in the field of artificial intelligence and multi-agent systems, focusing on integrating machine learning with game theory. Her work has been motivated by and applied to security, sustainability, and mobility domains, contributing to the theme of AI for Social Good. She is the recipient of the IJCAI-21 Computers and Thought Award. She was named to IEEE Intelligent Systems’ “AI’s 10 to Watch” list for 2020. She received an NSF CAREER Award in 2021.

Nisarg Shah
Assistant Professor, University of Toronto

Nisarg Shah is an Associate Professor of computer science at the University of Toronto. He has been recognized as part of "Innovators Under 35" by MIT Technology Review Asia Pacific in 2022 and "AI's 10 to Watch" by IEEE Intelligent Systems in 2020. He is also the winner of the 2016 IFAAMAS Victor Lesser Distinguished Dissertation Award and the 2014-2015 Facebook PhD Fellowship. Shah conducts research at the intersection of computer science and economics, addressing issues of fairness, efficiency, elicitation, and incentives that arise when humans are affected by algorithmic decision-making. His recent work develops theoretical foundations for fairness in fields such as voting, resource allocation, and machine learning. He has co-developed two not-for-profit websites, and, which have helped more than 200,000 users make provably fair and optimal decisions in their everyday lives. He earned his PhD in computer science at Carnegie Mellon University and was a postdoctoral fellow at Harvard University.

Joseph Halpern
Professor, Cornell University

Joseph Halpern received a B.Sc. in mathematics from the University of Toronto in 1975 and a Ph.D. in mathematics from Harvard in 1981. In between, he spent two years as the head of the Mathematics Department at Bawku Secondary School, in Ghana. After a year as a visiting scientist at MIT, he joined the IBM Almaden Research Center in 1982, where he remained until 1996, also serving as a consulting professor at Stanford. In 1996, he joined the Computer Science Department at Cornell University, where he is currently the Joseph C. Ford Professor and was department chair 2010-14. Halpern's major research interests are in reasoning about knowledge and uncertainty, security, distributed computation, decision theory, and game theory. Together with his former student, Yoram Moses, he pioneered the approach of applying reasoning about knowledge to analyzing distributed protocols and multi-agent systems. He has coauthored 5 patents, three books ("Reasoning About Knowledge", "Reasoning about Uncertainty", and "Actual Causality"), and over 360 technical publications.

‍Gillian Hadfield
Director, Schwartz Reisman Institute for Technology and Society
Professor, University of Toronto

Gillian Hadfield is the inaugural Schwartz Reisman Chair in Technology and Society, Professor of Law, Professor of Strategic Management at the University of Toronto and holds a CIFAR AI Chair at the Vector Institute for Artificial Intelligence.  She is a Schmidt Sciences AI2050 Senior Fellow. She was the inaugural Director of the Schwartz Reisman Institute for Technology and Society from 2019 through 2023. Her research is focused on the study of human and machine normative systems; safety and governance for artificial intelligence (AI); and innovative design for legal and dispute resolution systems in advanced and developing market economies.  She has also long studied the markets for law, lawyers, and dispute resolution; and contract law and theory. She teaches Contracts and Governance of AI.

Michael Dennis
Research Scientist, Google DeepMind

Michael Dennis is a Research Scientist at DeepMind. His work has focused on the automatic generation of environments suitable for training RL agents. These works vary from co-creating the GenIE generative environment model -- trained from unlabeled internet videos -- to helping to pioneer the field of Unsupervised Environment Design (UED) for automatically generating curricula of environments. His research aims to bridge the gap between classical decision theory, and modern deep learning. Before joining Deepmind, he received his Ph.D from the Center for Human-Compatible AI at UC Berkeley.

More speakers to be announced soon!


Programme Details

The summer school will take place between Wednesday 19 June and Sunday 23 June, beginning with a welcome reception on the evening of Wednesday 19 June. The full schedule will be announced closer to the event.


Thursday 20th June 2024






Friday 21st June 2024






Saturday 22nd June 2024








Please fill out this form to apply for your place at the Cooperative AI Summer School by 23:59 AoE (UTC-12) on 26 April 2024. Applications from underrepresented backgrounds are especially welcome. Notification of acceptance will be provided by 10 May 2024 at the latest. If accepted, you will be invited to confirm your registration by responding with further details and making any required payments.

The cost of the summer school is USD 350 for students and independent researchers, and USD 700 for faculty and other working professionals. This includes a hotel room for four nights (Wednesday, Thursday, Friday, Saturday), dinner on the first night, and all breakfasts and lunches.

CAIF is committed to ensuring that no-one who wishes to attend the summer school is prevented from doing so due to a lack of funding. If you do not have an institution or employer that is able to cover the registration fee, you will have the opportunity to request your fee to be waived. You will be asked to upload a letter of support from your academic supervisor or equivalent. If you would not be able to attend without additional financial support (to cover your flights, for example), please contact us, and we will also be happy to discuss this with you.


Cooperative AI Foundation

The mission of the Cooperative AI Foundation is to support research that will improve the cooperative intelligence of advanced AI for the benefit of all.

Visit sponsor website


Will the summer school be in-person, virtual, or hybrid? Will there be recordings?

The summer school is in-person only, although recordings will be available on the Cooperative AI Foundation's YouTube channel.

Who is eligible for this summer school?

Anyone (over the age of 18) can apply to the summer school, and we especially encourage applications from under-represented backgrounds. We expect all applicants to have at least a basic grounding in AI and the relevant mathematical background to contemporary AI research.

How will you decide whether or not I am accepted?

If the summer school is oversubscribed, we will prioritise those who: provide the strongest evidence of their interest in cooperative AI; are already pursuing graduate studies or working in a relevant field; come from under-represented backgrounds. All else equal, we will also aim to prioritise those weren't able to attend past summer schools or who might not be able to attend future summer schools (e.g. due to the location of the summer school).

Will I receive any ECTS points or certification for participating?

The Cooperative AI Foundation is unable to provide any kind of formal academic credit for participating in the summer school. We are, however, able to provide a digital certificate of participation for all attendees, which your institution may be willing to accept as a form of academic credit.

What do I need to do if I am travelling to the US for this event?

If you are travelling to the US for this event, and you are a citizen of an eligible country, you must apply for a Visa Waiver before you travel. There is a fee of $21 USD You can do this using this link: You will need to have at least six months remaining on your passport after the date you intend to leave the US. If you are not a national of a Waiver Program country, you will need to apply for a visa for entry to the US. CAIF can provide a letter to facilitate this process if needed.

What payment methods do you accept?

If you are accepted, we will send you a Stripe link, and you can pay by credit or debit card.

What is your cancellation policy?

Cancellations at least 30 days before the start of the summer school will be refunded 50% of the registration fee, but cancellations less than 30 days before the start of the summer school will not be entitled to receive any refund. If it is possible to fill your place with another applicant, we may, at our discretion, fully reimburse you.

Can I apply to have my fees waived, or for any other financial support?

CAIF is committed to ensuring that no-one who wants to attend is prevented from doing so due to a lack of funding. Further details of the support we offer can be found above. Please contact us if you have any questions regarding this.

What kinds of costs will I need to pay myself or get reimbursed separately?

Travel to and from the summer school; dinners on the second, third and fourth nights (Thursday, Friday, Saturday); visa application costs; and other travel expenses. Please also see the answer to the previous question.

I have a question that isn’t answered here. How do I contact you?

Please use our contact form.