Realizing the potential of biomedical data sciences in population health and biomedicine by advancing state-of-the-art research, the Second Penn Conference on Big Data in Biomedical and Population Health Sciences at the will offer insights from thought leaders in eight influential areas of big data.
Registration is Now Open!
Agenda
AGENDA For Monday, September 19, 2022 - (Day 1)
8:00 AM – REGISTRATION AND BREAKFAST (BRB Lobby)
8:45 AM – Opening remarks, Introduction
Hongzhe Li, PhD(link is external), Perelman Professor of Biostatistics, Epidemiology and Informatics
Enrique Schisterman, PhD(link is external), Chair, Department of Biostatistics, Epidemiology and Informatics
Session One (3 talks) EHR, Large Electronic Databases and Behavioral Economics
Chair: Jinbo Chen, PhD(link is external) - University of Pennsylvania
9:00 AM - Tianxi Cai, PhD(link is external), John Rock Professor of Population and Translational Data Sciences, Harvard University
Real world evidence with multi-institutional EHR data
9:30 AM - Ravi Parikh, MD(link is external), Assistant Professor, Department of Medical Ethics and Health Policy and Medicine, University of Pennsylvania
Conversation Connect: Machine learning and behavioral economics to improve serious illness communication
10:00 AM - Eleanor Pullenayegum, PhD(link is external), Associate Professor, Hospital for Sick Children, and the University of Toronto Dalla Lana School of Public Health
Longitudinal studies using EHR data: handling irregular and informative assessment times
10:30 AM – 11:00 AM COFFEE BREAK (BRB Lobby)
Session Two (2 talks): Dynamic COVID Risk Assessment
Chair: Hongzhe Li, PhD(link is external) - University of Pennsylvania
11:00 AM - Yuanjia Wang, PhD(link is external), Professor of Biostatistics, Columbia University
Dynamic COVID risk assessment accounting for community exposures from a spatial-temporal transmission model
11:30 AM - Jing Huang, PhD(link is external), Assistant Professor, University of Pennsylvania
Characterizing the dynamics of pandemic and preparing for speedy and accurate response
12:00 PM–1:30 PM LUNCH BREAK AND POSTER SESSION (BRB lobby)
Session Three (3 talks) Genomics Data and Health Disparity
Chair: Hongzhe Li, PhD(link is external) - University of Pennsylvania
1:30 PM - Kari North, PhD(link is external), Professor of Epidemiology, University of North Carolina, Chapel Hill
Genomics and Research Disparities: Turning a New Leaf
2:00 PM - Eimear Kenny, PhD(link is external), Professor of Genetics and Genomic Science, Ichan School of Medicine at Mount Sinai
Population Genetics in an Era of Genomic Health
2:30 PM - Sarah Tishkoff, PhD,(link is external) David and Lyn Silfen University Professor in Genetics and Biology, University of Pennsylvania
Global Genomics and Health Equity
3:00 PM – 3:30 PM BREAK
Session Four (3 talks) Single Cell Genomics and Multi-omics Data Integration in Translation Research
Chair: Mingyao Li, PhD(link is external), - University of Pennsylvania
3:30 PM - Christina Kendziorski, PhD,(link is external) Professor of Biostatistics, University of Wisconsin at Madison
Statistical methods for spatial transcriptomics
4:00 PM - Yang Xie, PhD(link is external), Raymond D. and Patsy R. Nasher Distinguished Chair in Cancer Research, UT Southwestern
Integrating imaging and genomic information to analyze spatial molecular profiling data
4:30 PM - Genevieve Stein-O’Brien, PhD(link is external), Postdoctoral Fellow, Johns Hopkins University
Transfer learning for precision medicine via latent spaces
5:00 PM - RECEPTION AND POSTER SESSION (BRB Lobby)
6:30 PM - DINNER (for invited speakers and session chairs)
AGENDA For Tuesday, September 20, 2022 - (Day 2)
8:00 AM-9:00 AM BREAKFAST (BRB Lobby)
Session Five (3 talks): Big Data in Biomedical Imaging and Applications
Chair: Taki Shinohara, PhD(link is external) - University of Pennsylvania
9:00 AM - Despina Kontos, PhD(link is external), Matthew J. Wilson Associate Professor, University of Pennsylvania
Radiomics, Radiogenomics, and AI: The Role of Computational Imaging in Precision Cancer Care
9:30 AM - Nico Dosenbath, MD, PhD(link is external), Associate Professor of Neurology, Washington University
Brain-wide association studies (BWAS): The underpowered sample paradox
10:00 AM - Ying Guo, PhD(link is external), Professor of Biostatistics, Emory University
Statistical learning with neuroimaging for reliable and reproducible brain network analysis
10:30 AM-11:00 AM COFFEE BREAK (BRB Lobby)
Session Six (2 talks) Nutrition, Microbiome and Metabolomics
Chair: Hongzhe Li, PhD(link is external) - University of Pennsylvania
11:00 AM - Eran Segal, PhD(link is external), Professor, Weizmann Institute of Science
Personalized medicine based on deep human phenotyping
11:30 AM - Jordan Bisanz, PhD(link is external), Assistant Professor, Penn State University
Leveraging big data and strain diversity for mechanistic microbiome research
12:00 PM-1:00 PM LUNCH BREAK AND POSTER SESSION (BRB Lobby)
Session Seven (3 talks) Cancer Data Science
Chair: Qi Long, PhD(link is external) - University of Pennsylvania
1:00 PM - Colin Begg, PhD(link is external), Chair and Attending Biostatistician, Memorial Sloan Kettering Cancer Center
Interpretation of Rare Genomic Variants from a Statistical Perspective
1:30 PM - Yu Shen, PhD(link is external), Conversation with a Living Legend Professor and Chair ad interim, Department of Biostatistics,
The University of Texas MD Anderson Cancer Center, Houston, TX
Learning from Big Data: Simulated Data and Real-World Data
2:00 PM - Rebecca Hubbard, PhD, Professor of Biostatistics, University of Pennsylvania
Deriving complementary evidence on cancer care and outcomes from clinical trials and real-world data
2:30 PM–3:00 PM BREAK
Session Eight (3 talks): Modern Development and Applications of Causal Inference
Chair: Nandita Mitra, PhD(link is external) - University of Pennsylvania
3:00 PM - Eric J. Tchetgen Tchetgen(link is external), PhD, Luddy Family President’s Distinguished Professor, The Wharton Schoo
Negative Control Methods to De-bias Test-Negative Design Studies of COVID-19 Vaccine Effectiveness
3:30 PM - Joseph Hogan, PhD(link is external), Professor of Biostatistics, Brown University
Dynamically updated generative models for causal and predictive inference from EHR and surveillance data
4:00 PM - Linda Valeri, PhD(link is external), Assistant Professor of Biostatistics, Columbia University
Bayesian kernel machine regression for environmental mixtures
4:30 PM - CONCLUDING REMARKS AND PRESENTATION OF BEST POSTER AWARDS
Event Type
- Affiliate Award Fund Eligible
- NISS Sponsored