![DBEI and PSOM logos. Third Penn Conference on Big Data in Biomedical and Population Health Sciences. September 18 & 19, 2023. Biomedical Research Building, Perelman School of Medicine, University of Pennsylvania. Register: [QR CODE]](http://dbei.nmsdev3.com/sites/default/files/uploads/event-images/Penn_Big_Data_2023.png)
Realizing the potential of machine learning and artificial intelligence (AI) in population health and biomedicine
The Third Penn Conference on Big Data in Biomedical and Population Health Sciences will be held on September 18-19, 2023 at the Perelman School of Medicine's Biomedical Research Building (421 Curie Boulevard, Philadelphia, PA) and will convene thought leaders from eight influential areas of big data.
Registration is open!
REGISTRATION FEES
NOTE: This is a hybrid event. There is limited capacity available for in-person registration. If you are unable to register for in-person attendance, please pick one of the available virtual options.
NOTE: This is a hybrid event. There is limited capacity available for in-person registration. If you are unable to register for in-person attendance, please pick one of the available virtual options.
| $400 | General registrants outside of the University of Pennsylvania |
| $200 | Virtual attendance for general registrants outside of the University of Pennsylvania |
| $300 | Postdocs and students outside of the University of Pennsylvania |
| $150 | Virtual attendance for postdocs and students outside of the University of Pennsylvania |
| WAIVED | DBEI/CCEB/IBI faculty, Penn/CHOP faculty, postdocs, students, or affiliates of sponsors (in-person or virtual) |
POSTER PRESENTATIONS
Attendees are invited to submit posters about their related work to be presented during the reception on the evening of September 18, 2023. If interested, please submit your poster after registering. NOTE: We can accept a limited number of posters - first come, first serve.
ACCOMMODATIONS
Information on hotel accommodations are available on the registration page.
AGENDA FOR DAY 1 - Monday, September 18, 2023
8:00 AM: REGISTRATION AND BREAKFAST (BRB Lobby)
8:45 AM: OPENING REMARKS AND INTRODUCTION
Hongzhe Li, PhD - Perelman Professor of Biostatistics, Epidemiology and Informatics; Vice Chair of Integrative Research, Department of Biostatistics, Epidemiology and Informatics
Enrique Schisterman, PhD - Chair, Department of Biostatistics, Epidemiology and Informatics
Emma A. Meagher, MD - Senior Vice Dean, Clinical & Translational Research, Perelman School of Medicine; Vice President, University of Pennsylvania Health System
SESSION ONE: AI IN MEDICINE AND LEARNING HEALTH SYSTEMS (x3 talks)
Chair: Hongzhe Li, PhD - University of Pennsylvania
9:00 AM: Artificial Intelligence in Medicine
Rene Vidal, PhD - Rachleff University Professor, University of Pennsylvania
9:30 AM: Harnessing Clinicial Nursing Data for Predictive Analytics and Decision Support in the Hospital Setting
Kenrick Cato, PhD, RN, CPHIMS, FAAN - Professor of Informatics, Children's Hospital of Philadelphia
10:00 AM: Sensory Interventions: Real-Time Integration of Passive Sensing and Adaptive Passive Interventions
Tanzeem Choudhury, PhD - Roger and Joelle Burnell Professor in Integrated Health and Technology, Cornell Tech
10:30 AM - 11:00 AM: COFFEE BREAK (BRB Lobby)
SESSION TWO: CAUSAL INFERENCE IN BIOMEDICINE AND PUBLIC HEALTH (x2 talks)
Chair: Eric Tchetgen Tchetgen, PhD - University of Pennsylvania
11:00 AM: Target Trials and Structural Nested Models: Emulating RCTs using Observational Longitudinal Data
James Robins, PhD - Mitchell L. and Robin LaFoley Dong Professor of Epidemiology, Harvard University
11:30 AM: Machine Learning for Causality
Konrad Körding, PhD - Penn Integrated Knowledge (PIK) Professor, Bioengineering and Neuroscience, University of Pennsylvania
12:00 PM - 1:30 PM: LUNCH BREAK (BRB Lobby)
SESSION THREE: BIAS AND ALGORITHM FAIRNESS OF AI IN MEDICINE (x3 talks)
Chair: Qi Long, PhD – University of Pennsylvania
1:30 PM: Robust and Equitable Uncertainty Estimation
Aaron Roth, PhD - Henry Salvatori Professor of Computer and Cognitive Science, University of Pennsylvania
2:00 PM: Biomedicine in the Age of LLM
James Zou, PhD - Assistant Professor of Biomedical Data Science, Stanford University
2:30 PM: Causal and Counterfactual Views of (Un)Fairness in Automated Decision Making
Razieh Nabi, PhD - Rollins Assistant Professor of Biostatistics and Bioinformatics, Emory University
3:00 PM - 3:30 PM: BREAK
SESSION FOUR: PRECISION NUTRITION, BACTERIA, VIRUS AND HOST INTERACTIONS (x3 talks)
Chair: Stefanie Hinkle, PhD - University of Pennsylvania
3:30 PM: Statistical and Machine Learning Approaches for Investigating Virus-Host Interactions
Fengzhu Sun, PhD - Professor of Quantitative and Computational Biology and Mathematics, University of Southern California
4:00 PM: Deep Learning for Precision Nutrition
Yang-Yu Liu, PhD - Associate Professor of Medicine, Harvard Medical School
4:30 PM: Neighbors, Friends, and Foes: Spatial Statistical Analysis for Biofilm Image Data
Jacqueline Starr, PhD - Associate Professor, Harvard Medical School
5:00 PM: RECEPTION AND POSTER SESSION (BRB Lobby)
6:30 PM: DINNER (invited speakers and session chairs)
AGENDA FOR DAY 2 - Tuesday, September 19, 2023
8:00 AM: BREAKFAST (BRB Lobby)
SESSION FIVE: IMPACT OF LARGE CLAIM DATABASE AND REAL-WORLD EVIDENCE (x3 talks)
Chair: Alexis Ogdie-Beatty, MD, MSCE - University of Pennsylvania
8:30 AM: Lessons from the Observational Health Data Sciences and Informatics Community
Patrick Ryan, PhD - Vice President of Observational Health Data Analytics, Janssen Research & Development
9:00 AM: Reproducible and Transparent Public Health Surveillance and Research Using Real-World Data
Darren Toh, DSc - Professor of Population Medicine, Harvard Medical School
9:30 AM: Linking Large Datasets to Augment Research in Transplantation and Study Variation in Care
Therese Bittermann, MD, MSCE - Assistant Professor of Medicine and Epidemiology, University of Pennsylvania
10:00 AM - 10:30 AM: COFFEE BREAK (BRB Lobby)
SESSION SIX: BIO HEALTH TECH, MOBILE HEALTH AND WEARABLE DEVICES (x3 talks)
Chair: Ian Barnett, PhD - University of Pennsylvania
10:30 AM: Multi-State Rate Modeling of Physical Activity Dynamics Using Accelerometer Data
Peter Song, PhD - Professor of Biostatistics, University of Michigan
11:00 AM: Multi-Modal Machine Learning for Biomedicine
Fei Wang, PhD - Director, Institute of AI for Digital Health; and Associate Professor of Population Health Sciences, Weill Cornell Medicine
11:30 AM: Predictive Modeling with mHealth Data to Personalize Psychotherapy
Samprit Banerjee, PhD, MStat - Associate Professor of Biostatistics, Weill Cornell Medicine
12:00 PM-1:00 PM: LUNCH BREAK (BRB Lobby)
SESSION SEVEN: COMPUTATIONAL NEUROSCIENCE (x3 talks)
Chair: Russell Takeshi Shinohara, PhD - University of Pennsylvania
1:00 PM: Reproducible Analysis and Visualization of iEEG Data
Michael Beauchamp, PhD - Professor of Neurosurgery, University of Pennsylvania
1:30 PM: Graph Learning for Functional Neuronal Connectivity
Genevera Allen, PhD - Associate Professor of Electrical and Computer Engineering and Statistics, Rice University
2:00 PM: Mental Effort in a Network Economy
Dani Bassett, PhD - J. Peter Skirkanich Professor, University of Pennsylvania
2:30 - 3:00 PM: BREAK
SESSION EIGHT: MACHINE LEARNING AND STATISTICAL IMAGING
Chair: Kristin Linn, PhD - University of Pennsylvania
3:00 PM: Machine Learning for Integrated Precision Diagnostics: Examples from Clinical Neuroscience
Christos Davatzikos, PhD - Wallace T. Miller Sr. Professor of Radiology; Professor of Electrical and Systems Engineering, and Informatics, University of Pennsylvania
3:30 PM: Mapping the Mind: Modeling Brain Connectivity and Its Link to Behavior
Yize Zhao, PhD - Associate Professor of Biostatistics, Yale University
4:00 PM: Density-on-Density Regression
Yi Zhao, PhD - Assistant Professor of Biostatistics and Health Data Science, Indiana University
4:30 PM: CONCLUDING REMARKS
