Next Seminar
Time: Friday, May 14, 1:30pm-3pm EST
Topic: Broader and deeper engagement in biomedical data science
Moderator: Dr. Hongzhe Li, Vice Chair of Research Integration, DBEI
Our panelists are:
- Dr. Enrique Schisterman, Chair of DBEI
- Dr. Jeff Morris, Director of Division of Biostatistics
- Dr. Jason Moore, Director of Division of Informatics and Director of IBI
- Dr. Alexis Ogdie-Beatty, Deputy Director of CCEB
A wide range of topics will be discussed, including:
- The role of computational thinking and inferential thinking in biomedical data science and data science life cycle
- Data bias, algorithm bias and fairness, AI for health care equity
- Trustworthy machine learning algorithm, privacy and reproducibility
- Promise of AI in health care and health care equity
- Challenges and opportunities in deeper engagement in biomedical data science research at Penn
- Modernization of PhD training in data science
- Open discussion
Connect to the full meeting from a computer or device:
https://bluejeans.com/659613804?src=join_info
Connect for audio only: 1.408.419.1715 or 1.408.915.6290
Meeting ID: 659 613 804
Questions? Contact Janine Pritchard
Additional Information:
• All attendees will be muted (camera and audio) upon entry. You can unmute when you wish to ask a question at the appropriate time.
• Depending on the device you use, you may be required to download BlueJeans
One Friday each month, we will meet virtually to discuss a theme in data science, featuring local, national and international speakers. Presented by the DBEI, the CCEB, and the Center for Statistics in Biomedical Big Data (CSBBD), the series will provide an open forum to learn frontier topics, to promote collaborations, and to engage participants in a discussion about biomedical data science.
Past Seminars
Time: Friday, April 16, 1-3 p.m. EST
Topic: Getting to the cause of complex diseases – state of the art on Mendelian randomization
1:00 p.m. : Dr. Qingyuan Zhao, University Lecture, Cambridge University
Mendelian randomization: Old and new insights
2:00 p.m. : Dr. Stephen Burgess, Programme Leader, MRC Biostatistics Unit, Cambridge University
Recent developments in Mendelian randomization
Time: Friday, February 12, 1-3 p.m. EST
Topic: Data Science Innovations in Single Cell Genomics and Medical Imaging
1:00 p.m. : Sarah Ryan, PhD, Instructor of Biostatistics, University of Pennsylvania
Cluster Activation Mapping with Applications to Medical Imaging
1:40 p.m. : Elizabeth Sweeney, PhD, Assistant Professor, Weill Cornell Medicine
Image Analysis Tools for Quantitative Susceptibility Maps in Multiple Sclerosis Lesions
Time: Friday, December 11, 1-3 p.m. EST
Topic: Mobile health and Digital Phenotyping
1 p.m.: Joshua F. Baker, MD Assistant Professor of Medicine
Cell phone location data and trends in COVID-19 Infections
1:30 p.m.: Jukka-Pekka Onnela, PhD, Associate Professor of Biostatistics
Smartphone-based Digital Phenotyping: Data, Methods, Case Studies
Time: Friday, November 13, 1-3 p.m. EST
Topic: Dynamics of Single Cell Genomics
1 p.m.: Eugene Katsevich, PhD, Assistant Professor of Statistics
Statistical Analysis of Single Cell CRISPR Screens
1:30 p.m.: Mingyao Li, PhD, Professor of Biostatistics
Applications of Deep Learning in Single Cell Genomics
2 p.m.: Katalin Susztak, MD, PhD, Professor of Medicine
Single Cell Genomics – Methods and Applications for Kidney Health and Disease
Time: Friday, October 16, 1-3 p.m. EST
Topic: Delve Into EHR Data and New Linkages in Public Data Sources
1 p.m. Mary Regina Boland, MA, MPhil, PhD, Assistant Professor of Informatics
Linking Multiple Public Data Sources Towards Understanding the Role of Hydraulic Fracturing Chemicals on Hormonal Regulation
1:30 p.m. Yong Chen, PhD, Associate Professor of Biostatistics
Distributed Learning for Electronic Health Records Data
2:15 p.m. Rebecca Hubbard, PhD, Professor of Biostatistics
The Role of Data Provenance in EHR Phenotyping and Analysis
Time: Friday, September 18, 1-3 p.m. EST
Topic: Promise and Challenge of EHR in Biomedical Research
1 p.m. James Zou, PhD, Assistant Professor of Biomedical Data Science, Stanford University.
Computer vision to deeply phenotype human diseases across physiological, tissue and molecular scales
2 p.m. Arjun Magge, PhD, Research Scientist, University of Pennsylvania.
Deep Learning Pipelines for Toponym Resolution in Scientific Articles
2:30 p.m. Ian Barnett, PhD, Assistant Professor of Biostatistics, University of Pennsylvania.
Neural Networks for Clustered and Longitudinal Data Using Mixed Effects Models
Organizing the series are committee members Ian Barnett, PhD; Sean Hennessy, PharmD, PhD; Graciela Gonzalez Hernandez, MS, PhD; Hongzhe Li, PhD; Mingyao Li, PhD; Li Shen, PhD; and Douglas Wiebe, PhD. Our co-presenters are the Department of Biostatistics, Epidemiology and Informatics and the Center for Clinical Epidemiology and Biostatistics.