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UID:20251126T010023EST-0206XjJuN9@132.216.98.100
DTSTAMP:20251126T060023Z
DESCRIPTION:High-throughput Single-cell Biology: the Challenges and Opportu
 nities for Machine Learning Scientists\n\nThe immune system does a lot mor
 e than killing “foreign” invaders. It’s a powerful sensory system that can
  detect stress levels\, infections\, wounds\, and even cancer tumors. Howe
 ver\, due to the complex interplay between different cell types and signal
 ing pathways\, the amount of data produced to characterize all different a
 spects of the immune system (tens of thousands of genes measured and hundr
 eds of millions of cells\, just from a single patient) completely overwhel
 ms existing bioinformatics tools. My laboratory specializes in the develop
 ment of machine learning techniques that address the unique challenges of 
 high-throughput single-cell immunology. Sharing our lab space with a clini
 cal and an immunological research laboratory\, my students and fellows are
  directly exposed to the real-world challenges and opportunities of bringi
 ng machine learning and immunology to the (literal) bedside.\n\n \n
DTSTART:20170310T203000Z
DTEND:20170310T213000Z
LOCATION:room 1205\, Burnside Hall\, CA\, QC\, Montreal\, H3A 0B9\, 805 rue
  Sherbrooke Ouest
SUMMARY:Nima Aghaeepour CIHR Fellow\, an ISAC Scholar\, and an OCRF Ann Sch
 reiber Investigator at Stanford University
URL:/mathstat/channels/event/nima-aghaeepour-cihr-fell
 ow-isac-scholar-and-ocrf-ann-schreiber-investigator-stanford-university-26
 6899
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