Real-Life Challenges and Opportunities in AI and Health
Catherine Ordun, VP at Booz Allen Hamilton
12-1 pm Mon. Nov. 25, 2024 in ITE 406 & online
Lunch provided for those attending in-person, please RSVP with this form. Additional Q&A session 1-2pm in ITE 406.
In academic research, we often find ourselves constrained to focus on algorithms and training data to develop novel architectures and frameworks. However, in real-life applications for customers, there are significantly more challenges that we should consider. When it comes to AI and Health in the Federal Government, it goes beyond algorithms and toward understanding the limitations of data and the complexities of AI integration into different platforms and systems. In this talk, Catherine Ordun will provide an overview of insights from her work leading AI development at Booz Allen Hamilton. We will walk through different real-life vignettes to help illustrate how to evaluate varying levels of complexity in AI development, from algorithms to deployment.
Dr. Catherine Ordun received her Ph.D in Information Systems from the University of Maryland, Baltimore County, with her dissertation on Multimodal Deep Generative Models for Cross Spectral Image Analysis. She has published papers at top AI conferences including NeurIPS, ICML, AAAI, MICAII, KDD, and a variety of IEEE conferences in image processing and biometrics. She is a Vice President at Booz Allen Hamilton, leading the AI Rapid Prototyping team, having led client delivery in the firm for thirteen years across health, defense, and intelligence accounts for data science, natural language processing, computer vision, and now, multimodal/multitask systems. Before Booz Allen, she worked in the U.S. Intelligence Community. She has a B.S. in Applied Biology from Georgia Tech, a Masters in Public Health from Emory University, and an MBA from George Washington University.
UMBC Center for AI