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SUMMARY:Paradigms for data-driven discovery and control in biological syst
ems - Professor Nathan Kutz (Dept of Applied Mathematics University of Was
hington)
DTSTART;VALUE=DATE-TIME:20210122T140000Z
DTEND;VALUE=DATE-TIME:20210122T150000Z
UID:https://talks.ox.ac.uk/talks/id/2f083698-1026-404c-8933-6a0fc4587b26/
DESCRIPTION:A major challenge in the study of biological systems is that o
f model discovery: turning data into reduced order models that are not jus
t predictive\, but provide insight into the nature of the underlying syste
m that generated the data. We introduce a number of data-driven strategies
for discovering nonlinear multiscale dynamical systems and their embeddin
gs from data. Such data-driven methods can be used in the biological scie
nces where rich data streams are affording new possibilities for the under
standing and characterization of complex\, networked systems. In neurosci
ence\, for instance\, the integration of these various concepts (reduced-o
rder modeling\, equation-free\, machine learning\, sparsity\, networks\, m
ulti-scale physics and adaptive control) are critical to formulating succe
ssful modeling strategies that perhaps can say something meaningful about
experiments. These methods will be demonstrated on a number of neural sy
stems. I will also highlight how such methods can be used to quantify cog
nitive and decision-making deficits arising from neurodegenerative disease
s and/or traumatic brain injuries (concussions).\nSpeakers:\nProfessor Nat
han Kutz (Dept of Applied Mathematics University of Washington)
LOCATION:Mathematical Institute\, Woodstock Road OX2 6GG
URL:https://talks.ox.ac.uk/talks/id/2f083698-1026-404c-8933-6a0fc4587b26/
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DESCRIPTION:Talk:Paradigms for data-driven discovery and control in biolog
ical systems - Professor Nathan Kutz (Dept of Applied Mathematics Universi
ty of Washington)
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