AI and Brain Computation

Suzhou, China 

Course Time:August 9 - August 22, 2021
Application Deadline: April 30, 2021


Organized by:

Si Wu, Peking University

Jun Zhang, University of Michigan

Taro Toyoizumi, RIKEN Center for Brain Science

Gabriella Vigliocco, University College London

The course aims to introduce state-of-the-art methods in AI, machine learning, and statistical analysis as applied to key issues in computation and cognitive neuroscience. Talented and highly-motivated PhD students at all levels as well as postdoctoral fellows/junior scholars with either 1) experimental background while interested in learning quantitative skills; or 2) theoretical background while interested in applying their computation skills to cognitive neuroscience are welcome to apply. There are no geographical restrictions of applicants.

The course will consist of two parts. The First Week will focus on teaching mathematical skills, computational models, and Python-based programming (with practical sessions). The Second Week will focus on introducing students to advanced research topics in the field. Students are expected to complete hand-on projects during the course. Our objective is to train students to apply learned AI and computational skills to solve cognitive neuroscience problems.


2021 Confirmed lecturers include :

Yanchao Bi, Beijing Normal University

Kenji Doya, Okinawa Institute of Science and Technology

Jia Liu, Tsinghua University

James McClelland, Stanford University

Naftali Tishby, Hebrew University

Xiaojing Wang, New York University

Bin Yu, UC Berkeley

and more....


Please note stipends are available to offset tuition costs. No payment is due until the selection decisions are made but any applicant requiring support should request this in writing during the online application. The admissions process is need-blind, your financial situation will not be considered before admission decisions are made. 

*The above pricing has been adjusted only for 2021 course programs to reflect changes in certain teaching methods/approaches that will be adopted in this course during the period of covid-19 pandemic.