Decoding the Data Ecosystem
Decoding the Data Ecosystem
Podcast Description
ABOUT THE PODCAST
Host Bio
Allissa Dillman, PhD, Training and Engagement Director for the CFDE Training Center, is the founder and CEO of BioData Sage LLC, a company focused on providing a holistic approach to data science integration in the biomedical and biological science fields. She works with clients in industry, academia, government, and the nonprofit sector to create and support training programs on bioinformatics, cloud computing, and the tools and standards for reproducible data science practices for scientific and lay communities. She also creates community events, such as hackathons, where broad communities work towards solving real biomedical data challenges. Dr. Dillman is a member of the adjunct faculty at Montgomery College and has over 10 years of experience working for the National Institutes of Health (NIH). Her work focuses on lowering the barriers of entry for data science and cloud computing. She received her PhD in computational neuroscience as part of the graduate partnership program between NIH and the Karolinska Institute, Sweden.
Why Listen?
Decoding the Data Ecosystem: A CFDE Training Center Podcast is more than just a podcast; it's a community for anyone passionate about the potential of omics research to solve complex biological puzzles and address pressing health challenges. Whether you're a seasoned researcher, a student just starting out, or simply curious about the future of biology, this podcast offers valuable insights, inspiring stories, and practical advice to guide your journey through the world of omics research training and education.
Availability
Find Decoding the Data Ecosystem on your favorite podcast platform, including Spotify, Apple Podcasts, Google Podcasts, and more. Subscribe today to stay updated with the latest episodes and join the conversation shaping the future of omics research training and education. This podcast is hosted by Oak Ridge Associated Universities (ORAU). Learn more at orau.org.
Podcast Insights
Content Themes
The podcast focuses on omics research, bioinformatics, and data science in the biomedical field, with episodes covering topics like the FAIR principles for data accessibility, navigating complex datasets, and enhancing reproducibility in research. For example, one episode discusses the CFDE Data Resource Center's role in integrating large datasets to empower scientific discoveries.
ABOUT THE PODCAST
Host Bio
Allissa Dillman, PhD, Training and Engagement Director for the CFDE Training Center, is the founder and CEO of BioData Sage LLC, a company focused on providing a holistic approach to data science integration in the biomedical and biological science fields. She works with clients in industry, academia, government, and the nonprofit sector to create and support training programs on bioinformatics, cloud computing, and the tools and standards for reproducible data science practices for scientific and lay communities. She also creates community events, such as hackathons, where broad communities work towards solving real biomedical data challenges. Dr. Dillman is a member of the adjunct faculty at Montgomery College and has over 10 years of experience working for the National Institutes of Health (NIH). Her work focuses on lowering the barriers of entry for data science and cloud computing. She received her PhD in computational neuroscience as part of the graduate partnership program between NIH and the Karolinska Institute, Sweden.
Why Listen?
Decoding the Data Ecosystem: A CFDE Training Center Podcast is more than just a podcast; it’s a community for anyone passionate about the potential of omics research to solve complex biological puzzles and address pressing health challenges. Whether you’re a seasoned researcher, a student just starting out, or simply curious about the future of biology, this podcast offers valuable insights, inspiring stories, and practical advice to guide your journey through the world of omics research training and education.
Availability
Find Decoding the Data Ecosystem on your favorite podcast platform, including Spotify, Apple Podcasts, Google Podcasts, and more. Subscribe today to stay updated with the latest episodes and join the conversation shaping the future of omics research training and education. This podcast is hosted by Oak Ridge Associated Universities (ORAU). Learn more at orau.org.
Description
In this episode, Allissa Dillman talks with John Kwagyan about the transformative potential of Artificial Intelligence (AI) and Machine Learning (ML) in genomics and personalized medicine as well as the promise of these technologies in analyzing complex biological data to advance disease prediction, prevention, and personalized treatments. They also discuss machine learning models, the differences between machine learning and statistical learning, explainable AI, and ethical considerations, as well as the skills future researchers will need to thrive in the AI-genomics landscape.
Guest Bio
John Kwagyan, PhD, is a Statistician and Graduate Associate Professor of Public Health at Howard University College of Medicine, and serves as co-Director of Biostatistics, Epidemiology and Research Design (BERD) at the Georgetown-Howard Universities Center for Clinical and Translational Science (GHUCCTS). He is co-PI of the Public Health Informatics and Technology program for District of Columbia (PHIT4DC), and PI (Data Science Core) of the recently funded Howard-Hopkins Comprehensive Alliance in Cancer Research and Education (H2CARE). His research interests include statistical genetics and predictive modelling of clustered data with applications to clinical and public health outcomes.
Disclaimer
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