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Program

Monday, January 11, 2021 

Opening Keynote Session
6-7 p.m. 

Title to be announced
John Quackenbush, Harvard School of Public Health, Boston, Massachusetts

Opening Reception 
7-8:30 p.m. 

Tuesday, January 12, 2021 

Continental Breakfast 
7-8 a.m. 
Plenary Session 1: Learning from Images: Pathology 
8-10 a.m. 

Unsupervised resolution of intra- and inter-tumoral heterogeneity using deep learning 
Phedias Diamandis, University of Toronto – University Health Network, Toronto, ON, Canada 

Additional speakers to be announced

Break  
10-10:30 a.m. 
Plenary Session 2: Learning from Images: Radiomics 
10:30 a.m.-12:30 p.m. 

Deep learning for automated quantification of tumor phenotypes
Ahmed Hosny, Dana Farber Cancer Institute, Boston, Massachusetts

Title to be announced
Hugo Aerts, Brigham and Women’s Hospital, Boston, Massachusetts

Radiomics: Medical images are quantitative data for diagnosis, prognosis, prediction, follow-up, and clinical trials
Philippe Lambin, MAASTRO Clinic, Maastricht, The Netherlands

Lunch Break (lunch on your own) 
12:30-2:30 p.m. 
Plenary Session 3: Learning from Images: Multiplex Imaging and Small Molecule Design 
2:30-4:30 p.m. 

Title to be announced
Garry P. Nolan, Stanford University School of Medicine, Stanford, California

Interpreting the cancer genome through physical and functional models of the cancer cell 
Trey Ideker, UC San Diego School of Medicine, La Jolla, California

Additional speaker to be announced

Poster Session A (with light refreshments) 
4:30-7 p.m. 

Wednesday, January 13, 2021 

Continental Breakfast 
7-8 a.m. 
Plenary Session 4: Learning from Genome Biology 
8-10 a.m. 

Machine learning approaches in cancer genomics 
Olga Troyanskaya, Princeton University, New York, New York

AI for variant interpretation 
Rachel Karchin, Johns Hopkins University, Baltimore, Maryland

Additional speaker to be announced

Break 
10-10:30 a.m. 
Plenary Session 5: Learning from Clinical Genomics 
10:30 a.m.-12:30 p.m. 

Title to be announced
Jinghui Zhang, St. Jude Children’s Research Hospital, Memphis, Tennessee

Exploring the dark corners of DNA in clinical cancer genomics 
Matija Snuderl, New York University Langone Medical Center, New York, New York

Methods to map the dynamics of tumor progression: Initiation, drug response and metastasis 
Dana Pe’er, Memorial Sloan Kettering Cancer Center, New York, New York

Poster Session B (and lunch) 
12:30-3 p.m. 
Plenary Session 6: Clinical Implementation of Machine Learning Models in Oncology 
3-5 p.m. 

AI for precision medicine: Clinical insights 
Constance Lehman, Massachusetts General Hospital, Boston, Massachusetts

Clinical deployment of machine learning based radiation treatment planning 
Thomas Purdie, Techna Institute for the Advancement of Technology for Health, Toronto, ON, Canada 

Multi-scale modeling of cancer patients 
Olivier Gevaert, Stanford University, Stanford, California

Thursday, January 14, 2021 

Continental Breakfast 
7-8 a.m. 
Panel 1:  Development of Data Resources, Data Standards, Access Policy, Reproducibility, Benchmarking  
8-10 a.m. 

Benjamin Haibe-Kains, University Health Network Princess Margaret Hospital, Toronto, ON, Canada 

Monica Marie Bertagnolli, Brigham and Women’s Hospital, Boston, Massachusetts

Additional speaker to be announced

Break 
10-10:30 a.m.     
Panel 2: Challenges and Opportunities in Machine Learning Algorithms for Cancer Research 
10:30 a.m.-12:30 p.m. 

Title to be announced
Regina Barzilay, Massachusetts Institute of Technology, Cambridge, Massachusetts

Title to be announced
Quaid Morris, Sloan Kettering Institute, New York, New York

An interpretable deep learning system for automatic medical image segmentation 
Bo Wang, University of Toronto, Toronto, ON, Canada 

Cancer genomics with machine learning – An FDA regulatory science perspective 
Weida Tong, Food and Drug Administration-National Center for Toxicological Research, Jefferson, Arkansas

Closing Remarks 
12:30-12:45 p.m. 

Regina Barzilay, Massachusetts Institute of Technology, Cambridge, Massachusetts
Thomas J. Fuchs, Memorial Sloan-Kettering Cancer Center, New York, New York
Benjamin Haibe-Kains, Princess Margaret Cancer Centre, Toronto, ON, Canada 
Trey Ideker, UC San Diego School of Medicine, La Jolla, California
Garry P. Nolan, Stanford University School of Medicine, Stanford, California
Trevor J. Pugh, Princess Margaret Cancer Centre, Toronto, ON, Canada