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.