NOT JUST A BLACK BOX; INTERPRETABLE DEEP LEARNING FOR GENOMICS

Part 2 of our Healthcare, Life Sciences and AI series is focused on Genomics. Computational biology and individualized medicine are two of the most transformational disciplines for AI and we expect Deep Learning to produce huge gains. We're excited to feature emerging research and discuss the role deep learning has in the future of healthcare, biology and medicine. Join us on Nov. 30th to kick off our first technical track talk, Avanti Shrikumar: Not Just a Black Box, Interpretable Deep Learning for Genomics. 

See Slide Deck:  Interpretable Deep Learning for Genomics

TECHNICAL LEVEL:

Deep Learning: Advanced. Biology: Advanced

SPEAKER:

Avanti Shrikumar

Avanti is a second-year Ph.D student in the Department of Computer Science at Stanford, advised by Professor Anshul Kundaje. She has develop broadly-applicable methods to make deep learning models interpretable, and has applied these methods to study regulatory genomics. Avanti has a Bachelor's in Computer Science with Molecular Biology from MIT and spent a year working as a developer for the Healthcare team of Palantir Technologies before starting her PhD. Her most recent research is published here: arxiv.org/abs/1605.01713

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FOOD & DRINKS:

Sponsored by H20.ai, Sub-sandwiches and Beer and non-alcoholic drinks. Thanks!

CODE OF CONDUCT:

Our conference is dedicated to providing a harassment-free conference experience for everyone, regardless of gender, gender identity and expression, age, sexual orientation, disability, physical appearance, body size, race, ethnicity, religion (or lack thereof), or technology choices. We do not tolerate harassment of conference participants in any form. Sexual language and imagery is not appropriate for any conference venue, including talks, workshops, parties, Twitter and other online media. Conference participants violating these rules may be sanctioned or expelled from the conference without a refund at the discretion of the conference organizers. For full version, please see: confcodeofconduct.com.

IMPORTANT: 

This event is limited to 150 people. You MUST be pre-registered to attend. Registration must include your First and Last name, and some of our venues require ID for entry. You do not need to print a paper ticket. We will be checking people in the building lobby. Questions or comments? Leave a comment below, or tweet to us @SVAIresearch

DISSCUSSION: