The Foundations of Biomedical Data Science
The Foundations of Biomedical Data Science virtual seminar series consists of regularly scheduled weekly webinar presentations covering the basics of data management, representation, computation, statistical inference, data modeling, & other topics relevant to “big data” biomedicine. The seminar series will provide essential topic introductions suitable for individuals at all levels of the biomedical and computational sciences community. All video presentations will be streamed for live viewing, recorded, & posted online for future viewing & reference. Be sure to also visit our Biomedical Data Science Innovation Lab webpage for the lecture schedule (see link below). Based in the School of Arts and Sciences and the School of Data Science at the University of Virginia, this virtual seminar series is made possible by a grant from the National Institute of General Medical Sciences (1R25GM139080). UVA IRB-SBS #7080
BDSIL 2025
BDSIL 2024 Slideshow
BDSIL 2024 Video
Biomedical Data Science Seminar Series
Clinical Trial Readiness for Neurodevelopmental Disorders: On the Road to Precision Health
Biomedicine & the Foundations of Data?
Computationally & Statistically Efficient Distributed Inference with Theoretical Guarantees
Genomic Fingerprinting & Representation
Imaging Informatics
Theoretical Foundations & Software Infrastructure for Biological Network Databases
Molecular Data & the Microbiome
"Why the Cloud Matters for Data Science"
Big Brain Data Science & Predictive Health Analytics
Leveling the Playing Field Applying FAIR Principles to Your Daily Data Tasks
Principles of Scientific Knowledge Engineering
Big Data Technologies for Biomedical Knowledge Discovery
Avoiding the Tower of Babel: the Role of Data Description Standards in Biomedical Imaging
Collaborative & Scalable Open Source Data Science: Deep Learning, Optimization & Education
DataScience@NIH: Current State, Future Directions
Considerations & Limitations for Clinical Data
Reproducibility
Ethical Issues in Data Science
Why Data Sharing & Reuse Are Hard To Do?
Open Science
Data Visualization Tools & Communication
Causal Inference
Data Issues: Multiple Testing, Bias, Confounding, Missing...
Bayesian Inference
Algorithms & Optimization