Deep Learning to Accelerate Drug Development: An NYC Symposium

Deep Learning to Accelerate Drug Development: An NYC Symposium

Tuesday, November 13, 2018

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.

Call for Abstracts

Abstract submissions are invited for a poster session. For complete submission instructions, please visit our online portal. The deadline for abstract submission is Friday, September 14, 2018.

Students and postdocs whose abstracts are accepted for poster presentation will receive complimentary meeting registration.

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
Deadline:
110
days
left

Scientific Organizing Committee

Deep Learning to Accelerate Drug Development: An NYC Symposium
James Cai, PhD, Roche Innovation Center New York
Deep Learning to Accelerate Drug Development: An NYC Symposium
Wei-Yi Cheng, PhD, Roche Innovation Center New York
Deep Learning to Accelerate Drug Development: An NYC Symposium
Nicholas Tatonetti, PhD, Columbia University
Deep Learning to Accelerate Drug Development: An NYC Symposium
Sara Donnelly, PhD, The New York Academy of Sciences
Deep Learning to Accelerate Drug Development: An NYC Symposium
Sonya Dougal, PhD, The New York Academy of Sciences

Speakers

Deep Learning to Accelerate Drug Development: An NYC Symposium
Wei-Yi Cheng, PhD, Roche Innovation Center New York
Deep Learning to Accelerate Drug Development: An NYC Symposium
Joel Dudley, PhD, Icahn School of Medicine at Mount Sinai
Deep Learning to Accelerate Drug Development: An NYC Symposium
Noémie Elhadad, PhD, Columbia University
Deep Learning to Accelerate Drug Development: An NYC Symposium
Thomas Fuchs, PhD, Memorial Sloan Kettering Cancer Center
Deep Learning to Accelerate Drug Development: An NYC Symposium
Nima Mesgarani, PhD, Columbia University
Deep Learning to Accelerate Drug Development: An NYC Symposium
Narges Razavian, PhD, NYU School of Medicine
Deep Learning to Accelerate Drug Development: An NYC Symposium
Fabian Schmich, PhD, Roche
Deep Learning to Accelerate Drug Development: An NYC Symposium
Heidi Schambra, MD, NYU School of Medicine
Deep Learning to Accelerate Drug Development: An NYC Symposium
Nicholas Tatonetti, PhD, Columbia University
Deep Learning to Accelerate Drug Development: An NYC Symposium
Olga Troyanskaya, PhD, Princeton University

Presenting Partner