[Comp-neuro] ONLINE SUMMER SCHOOL IN COMPUTATIONAL NEUROSCIENCE, August 2020
Rava A. da Silveira
rava at ens.fr
Mon Jun 8 16:42:48 CEST 2020
*Theoretical and Computational Neuroscience Summer School*
*17 to 21 August 2020 — Online, hosted by Tsinghua University, Beijing*
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, theoretical
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.
Larry Abbott (Columbia University, USA)
Rava Azeredo da Silveira (Ecole Normale Supérieure, France)
Damon Clark (Yale University, USA)
Ralf Haefner (University of Rochester, USA)
Yu Hu (HKUST, Hong Kong)
Daniel Lee (Cornell University, USA)
Sen Song (Tsinghua University, China)
Eric Shea-Brown (University of Washington, USA)
Louis Tao (Peking University, China)
Xiaoqin Wang (Johns Hopkins University, USA)
Quan Wen (University of Science and Technology of China)
Kechen Zhang (Johns Hopkins University, USA)
Douglas Zhou (Shanghai JiaoTong University, China)
*Application and deadline*
Please submit CV and personal statement at
http://brain.tsinghua.edu.cn/CNeuro, by 30 June 2020.
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