Rava A. da Silveira rava at ens.fr
Thu Jun 25 12:52:47 CEST 2020

*CN**EURO **2020*

*Theoretical and Computational Neuroscience Summer School*

*17 to 23 August 2020  —  Online, hosted by Tsinghua University, Beijing*


*About CNeuro*

              How intelligence and behavior emerge from complex and
intricate interactions within the brain remains a deep and unsolved
mystery, central to an exciting area of interdisciplinary research. The
past decade has seen rapid progress in experimental tools that now make it
possible to monitor and manipulate brain circuits in unprecedented detail.
This evolution presents challenges and opportunities for both
experimentalists and theorists, as the complex algorithmics of brain
function and the intricate interactions among neurons cannot be approached
with experiments alone. Mathematical theory is instrumental in the
emergence of theoretical insights and frameworks that can help guide
experimental work and identify unifying principles of brain function.

              The aim of the one-week summer school will be to introduce
students with a strong quantitative background (in mathematics, physics,
computer science, and engineering) to the emerging field of theoretical and
computational neuroscience. The course will bring together leading
scientists in the field, who will deliver lectures, take part in
small-group discussions, and share their personal experience and views on a
range of research topics. The distinguishing feature of CNeuro is the
emphasis it places on the role of systematic mathematical theory for
understanding the brain, in part by stressing the connections between
neuroscience, statistics, machine learning, and artificial intelligence.
The summer school will serve as a pedagogical introduction to some of the
methods particularly relevant to exploring these connections.

*Course Structure and Curriculum*

Each day will include three hours of lectures as well as two hours of
discussions among students and faculty, in small groups. Topics will touch
upon the biophysics and dynamics of neurons and network, neural coding,
models of learning and other cognitive function, as well as machine
learning and Bayesian approaches. There will be the possibility for
students to work on problem sets and initiate independent projects.


Rava Azeredo da Silveira (ENS)

Stella Christie (Tsinghua University)

Damon Clark (Yale University)

Carina Curto (Penn State University)

Ralf Haefner (University of Rochester)


Daniel Lee (Cornell University)

Songting Li (Shanghai JiaoTong University)

Zhaoping Li (MPI of Biologial Cybernetics)

Cristina Savin (NYU)

Eric Shea-Brown (University of Washington)

Sara Solla (Northwestern University)

Sen Song (Tsinghua University)

Louis Tao (Peking University)

Xiaoqin Wang (Johns Hopkins University)

Quan Wen (USTC)

Hang Zhang (Peking University)

Kechen Zhang (Johns Hopkins University)

Douglas Zhou (Shanghai JiaoTong University)

*Application and deadline*

Please submit CV and personal statement by 15 July 2020, at
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