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Deep Learning to Accelerate Drug Development: An NYC Symposium

Deep Learning to Accelerate Drug Development: An NYC Symposium

Tuesday, November 13, 2018, 8:30 AM - 6:15 PM EST

The New York Academy of Sciences, 7 World Trade Center, 250 Greenwich St Fl 40, New York

Presented By

Roche

The New York Academy of Sciences

 

Technological advances in artificial intelligence, especially in the field of deep learning, hold the potential to transform modern drug discovery and development. In recent years, the accumulation of multi-faceted big data in medicine offers exciting new opportunities to apply state-of-the-art deep learning advances to pressing global health challenges. However, significant ground-work in applying this research is still critically needed before real breakthroughs can happen.

In this symposium, we will bring together the best minds from the biopharmaceutical industry and academic deep learning communities to create focused dialogues and research collaborations in New York City. The meeting will feature exciting new opportunities on topics including mobile health and sensors, medical and pathology imaging, genomics, computer vision and robotics for lab automation, and electronic health records (EHRs), and beyond.

Registration

Member
$60
Nonmember Academia, Faculty, etc.
$105
Nonmember Corporate, Other
$160
Nonmember Not for Profit
$105
Nonmember Student, Undergrad, Grad, Fellow
$70
Member Student, Post-Doc, Fellow
$25

Scientific Organizing Committee

James Cai, PhD,  Roche
James Cai, PhD,
Roche
Wei-Yi Cheng, PhD,   Roche
Wei-Yi Cheng, PhD,
Roche
Nicholas Tatonetti, PhD,   Columbia University
Nicholas Tatonetti, PhD,
Columbia University
Sara Donnelly, PhD,   The New York Academy of Sciences
Sara Donnelly, PhD,
The New York Academy of Sciences
Sonya Dougal, PhD,   The New York Academy of Sciences
Sonya Dougal, PhD,
The New York Academy of Sciences

Keynote Speaker

Olivier Elemento, PhD,   Weill Cornell Medical College
Olivier Elemento, PhD,
Weill Cornell Medical College

Speakers

Wei-Yi Cheng, PhD,   Roche
Wei-Yi Cheng, PhD,
Roche
Noémie Elhadad, PhD,   Columbia University
Noémie Elhadad, PhD,
Columbia University
Thomas Fuchs, PhD,   Memorial Sloan Kettering Cancer Center
Thomas Fuchs, PhD,
Memorial Sloan Kettering Cancer Center
Casey Greene
Casey S. Greene, PhD
Perelman School of Medicine, University of Pennsylvania
Nima Mesgarani, PhD,   Columbia University
Nima Mesgarani, PhD,
Columbia University
Narges Razavian, PhD,   NYU School of Medicine
Narges Razavian, PhD,
NYU School of Medicine
Fabian Schmich,  PhD, Roche
Fabian Schmich,
PhD, Roche
Heidi Schambra, MD,   NYU School of Medicine
Heidi Schambra, MD,
NYU School of Medicine
Nicholas Tatonetti, PhD,   Columbia University
Nicholas Tatonetti, PhD,
Columbia University
Olga Troyanskaya, PhD,   Princeton University
Olga Troyanskaya, PhD,
Princeton University

Presenting Partner



Tuesday

November 13, 2018

8:30 AM

Continental Breakfast and Registration

9:00 AM

Introduction and Welcome Remarks

Speakers

Sonya Dougal, PhD
The New York Academy of Sciences
James Cai, PhD
Roche
9:15 AM

Keynote Lecture: Artificial Intelligence in Cancer Genomics and Therapy

Speaker

Olivier Elemento, PhD
Weill Cornell Medical College
10:00 AM

Networking Coffee Break

Session 1: Applying Deep Learning to Develop Novel Health Sensors

Session Chairperson
Nick Tatonetti
10:30 AM

Counting Reps: Quantitating Rehabilitation Dose After Stroke

Speaker

Heidi Schambra, MD
NYU Langone
11:00 AM

Deep Learning-Enabled Remote Gait and Mobility Monitoring Using Mobile Phones Sensor Data

Speaker

Wei-Yi Cheng, PhD
Roche
11:30 AM

Speech Processing In The Human Brain Meets Deep Learning

Speaker

Nima Mesgarani, PhD
Columbia University
12:00 PM

Networking Lunch

Session 2: Deep Learning Approaches for Genomics

Session Chairperson
Wei-Yi Cheng
1:00 PM

Deciphering the Genome: From Deep Learning to Deep Knowledge

Speaker

Olga Troyanskaya, PhD
Princeton University
1:30 PM

Opportunities and Obstacles for Deep Learning in Drug Development

Speaker

Casey S. Greene, PhD
Perelman School of Medicine, University of Pennsylvania

Session 3: Advanced Image Analysis Using Deep Learning

Session Chairperson
Wei-Yi Cheng
2:00 PM

To Be Confirmed

Speaker

Thomas Fuchs, PhD
Memorial Sloan Kettering Cancer Center
2:30 PM

Image-based Convolutional Neural Networks for Decision Support in Monoclonal Cell Line Development

Speaker

Fabian Schmich, PhD
Roche
3:00 PM

Networking Coffee Break

Session 4: Deciphering Real World Data with Deep Learning Methods

Session Chairperson
James Cai
3:30 PM

Deep Learning on Medical Records for Disease Prediction and Biomarker Discovery

Speaker

Narges Razavian, PhD
NYU School of Medicine
4:00 PM

Phenotyping Endometriosis through Modeling of Self-Tracking Data

Speaker

Noemie Elhadad, PhD
Columbia University
4:30 PM

Estimating Disease Heritability Using 14 Million Patients' Records

Speaker

Nick Tatonetti, PhD
Columbia University Irving Medical Center
5:00 PM

Neworking Reception and Poster Viewing

6:00 PM

Closing Remarks and F1000 Poster Prize Presentation

Speaker

James Cai, PhD
Roche
6:15 PM

Adjourn