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SUMMARY:IC Colloquium: Learning hidden signatures in biomedical data acros
 s space and time
DTSTART:20221017T161500
DTEND:20221017T173000
DTSTAMP:20260916T050215Z
UID:924c7afebbca2a92265acc26a3b90c9009dbf3741dc66d555715f3b6
CATEGORIES:Conferences - Seminars
DESCRIPTION:By: David van Dijk - Yale University\nVideo of his talk\n\nAbs
 tract\nNew biomedical measurement technologies\, including single-cell seq
 uencing and imaging modalities\, contain a wealth of information that prom
 ise unparalleled insight into biology. However\, our ability to model and 
 analyze this information is currently limited by the high dimensionality a
 nd large sample numbers inherent to these datasets. In this talk\, I will 
 present a number of recently developed algorithms that can discover hidden
  signatures in large biomedical datasets\, including brain imaging recordi
 ngs and single-cell sequencing data. These algorithms are inspired by idea
 s from manifold learning\, graph-signal processing\, computer vision\, and
  natural language processing\, and provide new representations of spatiote
 mporal data that allow meaningful insight into the underlying biology.\n\n
 Bio\nDr. David van Dijk is an Assistant Professor in the departments of Co
 mputer Science and Internal Medicine at Yale University where he leads a r
 esearch group focusing on the development of ML/AI algorithms for large bi
 omedical datasets. Dr. van Dijk completed his PhD in Computer Science at t
 he University of Amsterdam and the Weizmann Institute of Science where he 
 used ML to decipher links between DNA sequence and gene activity. Dr. van 
 Dijk moved on to postdoctoral fellow positions at Columbia University and 
 Yale University where he developed manifold learning and machine learning 
 algorithms for single-cell genomic data. His current research focus is in 
 developing machine learning algorithms\, inspired by ideas from computer v
 ision and natural language processing\, that are capable of discovering un
 derlying principles of biological functioning from large biomedical datase
 ts\, including single-cell RNA sequencing\, health records\, medical imagi
 ng\, and brain activity recordings. Dr. van Dijk is recipient of the Dutch
  Research Council Rubicon fellowship and the NIH R35 Maximizing Investigat
 ors' Research Award.\n\nMore information
LOCATION:BC 420 https://plan.epfl.ch/?room==BC%20420 https://epfl.zoom.us/
 j/69403386243?pwd=bnFGZXJxUWh1dVVMUS9tMGYzQVhIdz09
STATUS:CONFIRMED
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