Call for Applications: 2026 Summer School on Reinforcement Learning (Shanghai) with Richard S. Sutton

[wenyi...@gmail.com]

Dear colleagues,

We are pleased to announce the Call for Applications for the 2026 Summer School on Reinforcement Learning, a three-week in-person program to be held in Shanghai in July 2026.

The program is jointly organized by Shanghai Innovation Institute (SII), the School of Artificial Intelligence at Shanghai Jiao Tong University (SJTU), and Openmind Research Institute. It will be led by Professor Richard S. Sutton, 2024 ACM A.M. Turing Award laureate and one of the founding figures of reinforcement learning.

The summer school includes two related activities:

1. Intelligence Frontiers: Advanced Reinforcement Learning Course
   This is the main public student track. Applications are now open for senior undergraduate students, Master's students, and Ph.D. students.

2. Intelligence Pioneers: Advanced Research Seminar on Reinforcement Learning
   This is a research seminar for young scholars working on reinforcement learning and related areas. It will be organized mainly as an internal and invitation-only activity, with discussions centered on long-term research directions such as the Alberta Plan. Scholars interested in the seminar may contact the organizers by email.

Program overview:

• Time: July 2026, three weeks; exact dates to be announced
• Venue: Shanghai Innovation Institute, No. 3, Lane 699, Huafa Road, Xuhui District, Shanghai, China
• Format: Core lectures by Prof. Sutton on Mondays, Wednesdays, and Fridays; practical projects on Tuesdays and Thursdays
• Content: Advanced reinforcement learning, following topics from Part II and Chapter 17 of Sutton and Barto, Reinforcement Learning: An Introduction, 2nd edition, including function approximation, on/off-policy learning, policy gradients, general value functions, and agent architectures
• Activities: Lectures, TA recitations, coding sessions, group research projects, poster presentations, final assessment, and office hours with Prof. Sutton
• Certificate: A certificate of completion will be awarded to participants who successfully complete the program requirements

Eligibility for the public student course:

The public student track, Intelligence Frontiers: Advanced Reinforcement Learning Course, is open to senior undergraduate students (third year and above), Master's students, and Ph.D. students in AI, Computer Science, Automation, Mathematics, Statistics, or related fields. Applicants should have a solid foundation in reinforcement learning and be prepared for an intensive course and project schedule.

Capacity:

80-100 students.

Fees and accommodation:

The program is tuition-free. Participants are responsible for their own travel and meal expenses. Student dormitory accommodation may be provided by Shanghai Innovation Institute for out-of-town participants.

Application for the public student course:

• Application deadline: June 7, 2026
• Online interviews may be arranged depending on the application pool
• Admission notifications are expected in mid-June 2026
• Application form: https://sii-czxy.feishu.cn/share/base/form/shrcnzD7ehu7GgFqr43iXQGy9hf

Please note that the application form above is for the public student course only. The Advanced Research Seminar is not a regular open-enrollment course; interested young scholars should contact the organizers directly.

Additional information:

• Official announcement: https://www.sii.edu.cn/2026/0530/c60a1078/page.htm
• Shanghai Innovation Institute (SII): https://www.sii.edu.cn/
• Shanghai Jiao Tong University (SJTU): https://en.sjtu.edu.cn/
• School of Artificial Intelligence, SJTU: https://sai.sjtu.edu.cn/
• Openmind Research Institute: https://www.openmindresearch.org/

Contact:

For questions about the student course, please contact:
qc...@sii.edu.cn

For inquiries about the Advanced Research Seminar on Reinforcement Learning for young scholars, please contact:
ying...@sjtu.edu.cn

We would be grateful if you could share this announcement with students and colleagues who may be interested in advanced reinforcement learning.

Best regards,

The 2026 Summer School on Reinforcement Learning Organizing Team