Jason Moore, Chair of the Department of Computational Biomedicine and Director of the Center for Artificial Intelligence Research and Education (CAIRE) at Cedars-Sinai Medical Center in Los Angeles, CA, speaks with Pitt’s HexAI podcast host, Jordan Gass-Pooré, about his work, the strategic investments his center is making in technology and specialized human expertise to support advanced AI research and about the incorporation of AI and AI agents into precision health.

They speak in depth about the recent and rapid emergence of agentic AI, which is expected to have a significant impact on healthcare and how his team’s work is advancing the field. They also touch on vetting, deploying, and monitoring AI models for clinical use; explainable AI, trust, and transparency; using AI chatbots to improve the patient experience; the importance of building effective collaborations between industry and academia; and Cedar-Sinai’s new PhD program in Health AI.

Peter Maurer, Assistant Professor of Molecular Engineering at the University of Chicago Pritzker School of Molecular Engineering, speaks with Pitt’s HexAI podcast host, Jordan

Gass-Pooré, about the future impact of quantum sensing on biomedical research and diagnostics.

Peter's research lab leverages the extreme environmental sensitivity of quantum systems to develop powerful sensors suitable for cutting-edge biological research that are optically addressable and can operate under ambient conditions. He outlines both near-term and future applications of powerful quantum sensors in pathology and laboratory medicine. He provides a key example of how these sensors could enable a new type of nanoscale NMR spectroscopy, capable of measuring magnetic fields from biomolecules to non-invasively probe their chemical information and signaling pathways. In the near future, he points to diagnostic tools, currently being developed by companies, that use the unique optical signatures of quantum sensors for highly sensitive, background-free protein detection in small volumes. For the long term, he envisions the technology as a "field opener" for studying protein aggregation in neurodegenerative diseases like Alzheimer's and Parkinson’s.

Peter outlines how AI can be applied to analyze complex data from sensors that respond to multiple environmental factors and highlights the challenge of bringing together experts from quantum technology, biophysics, and medicine who can "talk each other's language.” He also touches on how the use of synthetic data in quantum sensing is a "completely under-appreciated" area with the potential to analyze complex environmental properties that would otherwise be missed by looking at single types of measurements. To advance the field from academic proofs-of-concept to clinical tools, he stresses the need for collaboration with academic and industry partners who can help engineer robust, "turnkey" systems that can be widely tested and used.

The University of Pittsburgh Health and Explainable AI podcast is a collaborative initiative between the Health and Explainable AI (HexAI) Research Laboratory in the Department of Health Information Management at the School of Health and Rehabilitation Sciences, and the Computational Pathology and AI Center of Excellence (CPACE), at the University of Pittsburgh School of Medicine.

Hosted by Jordan Gass-Pooré, a health and science reporter, this podcast series explores the transformative integration of responsible and explainable artificial intelligence into health informatics, clinical decision-making, and computational medicine. From reshaping diagnostic accuracy to enhancing patient care pathways, we'll highlight how AI is creating new bridges between researchers, clinicians, and healthcare innovators. 

Led by Ahmad P. Tafti, Hooman Rashidi and Liron Pantanowitz, the HexAI podcast is committed to democratizing knowledge around ethical, explainable, and clinically relevant AI. Through insightful conversations with domain experts, AI practitioners and students will spotlight the latest breakthroughs, discuss real-world applications, and unpack the challenges and opportunities that lie ahead in responsible AI in healthcare. So whether you're a student, practitioner, researcher, or policymaker, this is your gateway to the future of AI-powered healthcare

Karen Colbert, an AI strategist, data scientist, and Lead Math Faculty at Keweenaw Bay Ojibwa Community College, speaks with Pitt HexAI Producer, Brent Phillips about tribal colleges and their mission and vision to revitalize language and culture through education, the indigenization of math and teaching math, computing and data science in the AI age, collaboration tools, data sharing and privacy, explainability and storytelling, project ideation, AI applications, data annotation, and life lessons for students.

Karen Colbert is an AI strategist, data scientist, keynote speaker, and a nationally recognized advocate for STEM education. She currently serves as the General Education Department Chair and Lead Math Faculty at Keweenaw Bay Ojibwa Community College, a Tribal College, where she advances data and computational literacy for Indigenous students. Notably, Karen became the first Data Carpentries Instructor and Trainer among all Tribal Colleges, pioneering efforts to bridge the digital divide in higher education. Her passion lies in ensuring that non-traditional, re-entry, and adult learners are not left behind in the AI revolution. Karen is passionate about sharing her insights on “digital sovereignty in the age of AI.” Specifically, she has a deep interest in exploring how AI is reshaping education, research, and opportunity, challenging educators to lead with cultural integrity as technology evolves. 

She also has an upcoming book 'The Algorithm wasn't Built for Us: Reclaiming the Future of AI, Education, and Culture' available July 4 on Amazon. Visit her website: https://www.karencolbert.com/

Anatea Einhorn, Research Assistant with the University of Pittsburgh’s Health and Explainable AI Research Laboratory, speaks with Pitt HexAI podcast host Jordan Gass-Pooré about her work and studies linking artificial intelligence and machine learning, statistics and public health, and about explainable AI, the future of work, and the importance of exchange programs and working abroad. Jordan and Anatea dig into data and data analysis, differences between personal health and public health, and into explainability from a public health perspective.

Janneta Tabakov, Enterprise Growth Lead with Perplexity who focuses on AI in biotech and biopharma speaks with Pitt HexAI Podcast host Jordan Gass-Pooré about her work at Perplexity, a popular and fast-growing new AI-powered answer engine that’s redefining search and information discovery in the AI era. Janneta and Jordan discuss how Perplexity (https://www.perplexity.ai/) makes information discovery clear, trustworthy, and accessible, especially in fields like health, medicine, and science and they touch on Janneta’s prior work at Arima Genomics, the field of 3D genomics, Hi-C technology and the visualization and mapping of DNA structures.

The episode is geared towards introducing students and healthcare professionals to new AI-powered search tools and information discovery processes. The episode highlights how tools like Perplexity are advancing explainable AI in information discovery by making the search and synthesis process transparent, interactive, and easy to understand, helping users not only find answers, but also understand the reasoning and evidence behind them.

Janneta and Jordan also discuss the accelerating pace of AI innovation and the dynamic momentum that startups like Perplexity are driving in the industry, setting new benchmarks in healthcare and research.

Yanshan Wang (PhD, FAMIA), Vice Chair for Research and Assistant Professor of Health Informatics at the University of Pittsburgh, speaks with Pitt HexAI podcast host Jordan Gass-Pooré.

Yanshan is also the interim Director of Generative AI with the University of Pittsburgh's Computational Pathology and AI Center of Excellence and he leads the Clinical Natural Language Processing and Artificial Intelligence Innovation Laboratory (PittNAIL). Jordan and Yanshan discuss his journey into biomedical and health informatics, his role as Vice Chair of Research, his views on explainable AI, private sector engagement around AI transparency, and on emerging generative AI models and computational resources at Pitt. Yanshan closes the interview with advice for students on setting up research projects.

Pitt HexAI podcast host Jordan Gass-Poore’ speaks with three talented young student researchers from Ukraine who participated in the RAI for Ukraine program, a fully remote academic research program launched by NYU in partnership with the Ukrainian Catholic University (UCU) in Lviv, Ukraine. The program conducts cutting-edge collaborative research on a range of responsible AI topics in collaboration with mentors from other U.S. and European universities.

Participating students: Yaroslav Klym, Vladyslav Protsenko, and Danylo Reznyk discuss the RAI for Ukraine program, their journeys into the initiative, their experiences working with the AMIIE Lab at Pace University and the HexAI Lab at the University of Pittsburgh, as well as provide insights into their research and forthcoming papers.

The RAI for Ukraine program and participating initiatives like Pitt's HexAI lab help provide high-quality research opportunities to students in Ukraine, helping to strengthen research capacity in responsible and explainable AI.

Dr. Xenophon Papademetris, Professor of Biomedical Informatics & Data Science, and Radiology & Biomedical Imaging at Yale School of Medicine speaks with Pitt HexAI guest host Jamie Gramz, Senior Director of Digital Strategy and Business Development with Siemens Healthineers. Jamie and Dr. Papademetris discuss Xenophon’s experience in medical image analysis, machine learning, and software development and his involvement in the development of medical image analysis software as well as his involvement in Yale’s Certificate Program in Medical Software and Medical AI. Jamie and Dr. Papademetris also discuss Xenophon’s textbook “Introduction to Medical Software: Foundations for Digital Health, Devices and Diagnostics” and his Coursera online class “Introduction to Medical Software”, the importance of medical software and AI education as well as the importance of interdisciplinary collaboration in AI for healthcare, and they discuss explainability in AI and clinical communications.

Pitt HexAI podcast host Jordan Gass-Poore´ speaks with Beth Bauer about data and digital knowledge in the AI age, exploring foundational, strategic, and people-focused perspectives. Beth, CEO of PosiROI, Co-Founder and CEO of Communities Connected, VP of The DataJam, and Global Board Co-Chair of Program & Projects for the Healthcare Businesswomen Association’s Women in Healthcare Giveback affinity group, is a trailblazer in aligning technology, data, and analytics with people and shared goals. Known for her inspirational public speaking, extensive mentoring, and educational initiatives, Beth has shaped strategies and innovations that empower people through data for over 35 years. In this episode, she and Jordan discuss her insights on data, artificial intelligence, and explainable AI, as well as her work inspiring young people, promoting data fluency, and fostering people-centric, data-informed cultures that drive holistic, intentional outcomes. 

Ashwin Kumar, a PhD candidate at Washington University in St Louis, working on fair resource allocation and explainable AI, speaks with Brent Phillips, Pitt HexAI podcast producer, about the intricacies of fairness in AI systems and about balancing fairness and efficiency in complex systems like ride-sharing and healthcare resource distribution. The discussion dives into AI transparency, human-machine interaction, multi-agent reinforcement learning, and the evolving challenges in ensuring equitable outcomes in AI decision-making. The conversation connects AI's technical workings with real-world ethical concerns.