NHLBI Data Science Panel
Data Science Ecosystem of BioData Catalyst presented by Olga Brazhnik
Ever growing diverse BioData Catalyst (BDC) community of practice works collaboratively to solve technical and scientific challenges in accelerating efficient biomedical research that drives discovery and scientific advancement, leading to novel diagnostic tools, therapeutics, and prevention strategies for heart, lung, blood, and sleep disorders.
Trustworthy, Inclusive and Responsible AI presented by Asif Rizwan
There have been concerns regarding the general trustworthiness of AI algorithms due to model accuracy, algorithmic biases against underrepresented communities, robustness, and a general lack of understanding of the predictions of these algorithms. In this talk we will review key trustworthy AI principles that are necessary to establish trust in AI systems.
Synthetic Data for Biomedical Research presented by Asif Rizwan
Gaining access to health data is a major barrier in developing and validating new AI methods for clinical applications. Synthetic data can be used for testing theories, training next generation data scientists and developing AI/ML models before they can be used with real-world data.
Olga Brazhnik, PhD, NHLBI Data Scientist co-leads BioData Catalyst team and works on synergizing data science activities across NHLBI. Following her mission to empower individuals and communities with data, knowledge and tools in the process of creating their health, she brings together a broad spectrum of disciplines, from computer science to transformative leadership and trustworthy sustainable engagement. Originally a computational physicist, Olga facilitated the adoption of innovative approaches in biomedical computing and informatics, collaborative technologies, data and knowledge integration, modeling, and visualization, and led a variety of interagency initiatives in open science and innovation (in collaboration with HHS and OSTP).
Asif Rizwan, PhD, NHLBI Health Scientist Administrator (Program Director) actively manages NIH research awards that include genetic, proteomic, and metabolomic tools and systems biology approach. His academic and research training have given him a background in a wide diversity of scientific disciplines including Biomedical engineering, diagnostics, data science and health equity through Technology. Asif also serves as a program staff on initiatives to support whole-genome sequencing and other omics and data analyses. He serves as a Program Manager for NIH RADx Tech initiative, a dedicated Congressional appropriation to speed innovation in the development, commercialization, and implementation of technologies for COVID-19 testing. Asif is involved with workforce development in AI/ML, biomedical data repository and biomedical knowledgebase, ethical development and use of AI/ML in biomedical and behavioral Sciences at NIH.