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Deep Learning in Biomedicine and Genomics: An Introduction and Applications to Next-generation Sequencing and Disease Diagnostics

December 4, 2017 @ 6:30 pm - 8:30 pm PST

Speaker: Mark DePristo, Head of Deep Learning for Genetics and Genomics at Google



  • We will review the history and taxonomy of machine learning and artificial intelligence
  • We will introduce deep learning, covering both what it is and why its so exciting.
  • We will review a highlight a few deep learning applications to biomedical problems across the field
  • We will do a deep dive into three recent deep learning applications from Google Brain:
  • Detection of cancer cells in pathology images
  • Detection of diabetic retinopathy from fundus images of the eye
  • Calling SNP and indel variants in next-generation sequencing data

Biography: I’m Mark DePristo, a Google software engineer since 2015. I lead the Google Brain Genomics team where we work on advancing the capabilities and applications of deep learning tech in TensorFlow for genomics problems. Before joining Google I was Vice President of Informatics at SynapDx, a Google Ventures-backed startup developing a blood-based test for Autism. And before that I was Co-Director of Medical and Population Genetics at the Broad Institute where I created and led the ~10 person team that developed the GATK, the dominant software for processing next-generation DNA sequencing data. I have an BA in Computer Science and Math from Northwestern, a PhD in Biochemistry from University of Cambridge where I was a Marshall fellow, and finally postdoc’d at Harvard to study antibiotic resistance evolution. My academic articles are widely published with more than 28,000 citations.


IEEE SCV Computational Intelligence Society


Texas Instruments Building E Conference Center

2900 Semiconductor Drive
Santa Clara, CA United States