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BEGIN:VEVENT
UID:1516d78876003f8fe699615cead5f62f
CATEGORIES:D'Atri Memorial Lectures, Mathematical Physics Seminar
CREATED:20210226T161803
SUMMARY:How Materials Can Learn How to Function
LOCATION:zoom
DESCRIPTION:<p style="text-align: center;"><span style="font-family: Times New Roman; f
 ont-size: medium;"> <b><span style="font-family: 'Helvetica',sans-serif;"><
 span style="font-size: medium;">Andrea Liu - University of Pennsylvania</sp
 an></span></b></span></p><p style="text-align: center;"><span style="font-f
 amily: Times New Roman; font-size: medium;"> <span style="font-size: medium
 ;"><span style="color: #203864;"><span style="font-family: Times New Roman;
 ">Wednesday, March 3, </span></span><b><span style="color: #203864; font-fa
 mily: 'inherit',serif;">10:45AM</span></b></span></span></p><p style="text-
 align: center;"><span style="font-family: Times New Roman; font-size: mediu
 m;"> <b><span style="font-family: Times New Roman; font-size: medium;">“How
  Materials Can Learn How to Function”</span></b></span></p><p style="text-a
 lign: center;"><span style="font-family: Times New Roman; font-size: medium
 ;"> <b><span style="font-family: 'Calibri',sans-serif; font-size: 11pt;"><s
 pan style="font-family: Times New Roman; font-size: medium;"><span style="f
 ont-size: medium;"><span style="font-family: Times New Roman;"><span style=
 "color: black;">Abstract: </span>How does learning occur? In the context of
  neural networks, learning occurs via optimization, where a loss function i
 s minimized to achieve the desired result. But physical networks such as me
 chanical spring networks or flow networks cannot minimize such a loss funct
 ion by themselves—they need the help of a computer. An alternative is to en
 code local rules into those networks so that they can evolve under external
  driving to develop function. For example, if the springs in a mechanical n
 etwork have equilibrium lengths that grow if the springs are stretched, and
  shrink when the springs are compressed, the network will naturally evolve 
 under applied stresses. I will describe how both of these strategies—global
  minimization of a loss function as well as training by local rules--can be
  used to teach materials how to perform functions inspired by biology, such
  as the ability of proteins (e.g. hemoglobin) to change their conformations
  upon binding of an atom (oxygen) or molecule, or the ability of the brain’
 s vascular network to send enhanced blood flow and oxygen to specific areas
  of the brain associated with a given task.</span></span></span></span></b>
 </span></p><p><span style="font-family: Times New Roman; font-size: medium;
 "> </span></p>
CONTACT:Andrea Liu - University of Pennsylvania
DTSTAMP:20260829T003531
DTSTART;TZID=America/New_York:20210303T103000
DTEND;TZID=America/New_York:20210303T113000
SEQUENCE:0
TRANSP:OPAQUE
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