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SUMMARY:IC Colloquium: Learning hidden signatures in biomedical data acros
 s space and time
DTSTART:20221017T161500
DTEND:20221017T171500
DTSTAMP:20260510T165038Z
UID:033cfb14f159bcb3eaf97672b57aa9671586f8d800c3dd4120396172
CATEGORIES:Conferences - Seminars
DESCRIPTION:David van Dijk\nBy: David van Dijk - Yale University\n\nAbstr
 act\nNew biomedical measurement technologies\, including single-cell seque
 ncing and imaging modalities\, contain a wealth of information that promis
 e unparalleled insight into biology. However\, our ability to model and an
 alyze this information is currently limited by the high dimensionality and
  large sample numbers inherent to these datasets. In this talk\, I will pr
 esent a number of recently developed algorithms that can discover hidden s
 ignatures in large biomedical datasets\, including brain imaging recording
 s and single-cell sequencing data. These algorithms are inspired by ideas 
 from manifold learning\, graph-signal processing\, computer vision\, and n
 atural language processing\, and provide new representations of spatiotemp
 oral data that allow meaningful insight into the underlying biology.\n \n
 Biography\nDr. David van Dijk is an Assistant Professor in the departments
  of Computer Science and Internal Medicine at Yale University where he lea
 ds a research group focusing on the development of ML/AI algorithms for la
 rge biomedical datasets. Dr. van Dijk completed his PhD in Computer Scienc
 e at the University of Amsterdam and the Weizmann Institute of Science whe
 re he used ML to decipher links between DNA sequence and gene activity. Dr
 . van Dijk moved on to postdoctoral fellow positions at Columbia Universit
 y and Yale University where he developed manifold learning and machine lea
 rning algorithms for single-cell genomic data. His current research focus 
 is in developing machine learning algorithms\, inspired by ideas from comp
 uter vision and natural language processing\, that are capable of discover
 ing underlying principles of biological functioning from large biomedical 
 datasets\, including single-cell RNA sequencing\, health records\, medical
  imaging\, and brain activity recordings. Dr. van Dijk is recipient of the
  Dutch Research Council Rubicon fellowship and the NIH R35 Maximizing Inve
 stigators' Research Award.\n \n 
LOCATION:BC 420 https://plan.epfl.ch/?room==BC%20420 https://epfl.zoom.us/
 j/69403386243?pwd=bnFGZXJxUWh1dVVMUS9tMGYzQVhIdz09#success
STATUS:CONFIRMED
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