Hear perspectives from a diverse expert panel of AI clinicians, researchers, computer scientists, and industry leaders:
- Hugh Harvey, MBBS BSc(Hons) FRCR MD(Res) FBIR, Managing Director (Hardian Health): Dr. Harvey is an experienced clinician and health technology advisor, with a focus on leveraging big data and artificial intelligence. He is a board certified consultant radiologist and academic, trained in the NHS and Europe’s leading cancer research center, the Institute of Cancer Research, where he was twice awarded ICR Science Writer of the Year. He has held lead roles at two flagship UK startups, leading to successfully gaining the world-first CE marking for an AI-supported triage service, and the first UK CE mark for a deep-learning medical device. He now serves as board advisor to many AI start-up companies across the globe and retains an academic interest as a board member of the global open source scientific journal Nature: Digital Medicine, and holds an honorary research fellowship at the Institute of Cognitive Neurosciences at UCL.
- Judy Gichoya, MD, MS, Assistant Professor of Radiology (Emory): A multidisciplinary researcher, trained as both an informatician and a clinically active radiologist. She is an assistant professor at Emory University working on Interventional Radiology and Informatics. She has been funded through the Grand Challenges Canada and NSF ECCS. Her career focus is on validating machine learning models for health in real clinical settings, exploring explainability, fairness, and a specific focus on how algorithms fail. She has worked on the curation of datasets for the SIIM (Society for Imaging Informatics in Medicine) hackathon and ML committee. She volunteers on the ACR and RSNA machine learning committees to support the AI ecosystem to advance development and use of AI in medicine. She is currently working on the sociotechnical context for AI explainability for radiology, especially the dimensions of human factors that govern user perceptions and preferences of XAI systems.
- Jefferson Lin, JD, Associate (Fenwick & West LLP): Jefferson represents digital health, life sciences and technology companies in complex transactions. He regularly counsels clients with respect to intellectual property licensing, data privacy and security, and healthcare regulatory issues. Jefferson is particularly active in the digital health community, representing innovative companies focused on administrative automation, telehealth, clinical intelligence, diagnostics, therapeutics and wellness. He is also involved in corporate transactions such as mergers, asset acquisitions and venture capital investments in the digital health and technology spaces.
- Chrissy Watson, JD, MBA, Industrial Contracts Officer (Stanford’s Office of Technology Licensing): Chrissy currently serves as an Industrial Contracts Officer in Stanford’s Office of Technology Licensing where she facilitates University research and collaboration with industry. Prior to joining Stanford, Chrissy practiced law in the public and private sectors as a federal criminal prosecutor, intellectual property litigator, and commercial transactions attorney. As a certified mindfulness meditation teacher, she brings an interdisciplinary approach to legal and business challenges that supports efficient problem solving and effective collaboration.
- Amy Pitelka, JD, Lead Computational Medicine Legal Accelerator (Center for Applied AI, University of Chicago Booth School of Business): Amy Pitelka is leading the Computational Medicine Legal Accelerator and the chief legal officer of Nightingale Open Science both at the Center for Applied AI, University of Chicago Booth School of Business, and the founder of Barker Pitelka PLLC, a legal and policy strategic advisory firm focused on technology startups and social good organizations. Prior to starting her own firm, Amy was the Acting Deputy Administrator and lead Counsel for the United States Digital Service at the White House, where she focused on identifying, combating, and removing key legal and policy hurdles to the USDS’s ongoing efforts to revolutionize the federal government’s use of technology in delivering services to the American people. In her time at the USDS, Amy led the legal effort to unlock key datasets used for health benefits administration to additional human services programs administered by states and counties across the country. Amy has also worked at Dropbox, Google, and Kirkland & Ellis International LLP. She graduated from Harvard Law School.
- Zach Harned, JD, MS, Associate (Fenwick & West LLP): Zach advises on a broad variety of intellectual property matters, with a focus on technology transactions and commercial matters, for clients in the technology, digital health and life sciences industries. He also counsels clients on technology, IP, and open source aspects of venture financings and mergers and acquisitions. While in law school at Stanford, Zach also earned an MS in Symbolic Systems and founded the Stanford AI & Law Society (SAILS).
- Elizabeth Lee, JD, CIPP, CIPM, CHC, CPC, Senior Privacy Officer (Stanford): Elizabeth’s specialty areas are privacy compliance under California CCPA, U.S. HIPAA, Canada PIPEDA, and E.U. GDPR regulations. Elizabeth has technology expertise to advise on privacy-by-design for digital and mobile platforms, data mapping, data classification, data retention, and data protection impact assessment. Before joining Stanford, Elizabeth was the Global Privacy Director at Mckesson Corporation leading consumer, employee HR, digital experience, and cloud privacy programs. Prior to McKesson, Elizabeth worked as the Privacy & Corporate Compliance Manager for Kaiser Permanente Santa Clara Medical Center managing patient concerns, risk assessments, and incident responses for the physician group, health insurance plan, and hospital organizations. Elizabeth earned her B.A. in Economics and Asian Studies from Rice University, and her J.D. from Santa Clara School of Law.
- Akshay Chaudhari, PhD, Assistant Professor of Radiology (Stanford): Dr. Chaudhari is an Assistant Professor of research in the Integrative Biomedical Imaging Informatics at Stanford (IBIIS) section in the Department of Radiology. He is interested in the application of artificial intelligence techniques to all aspects of medical imaging, including automated schedule and reading prioritization, image reconstruction, quantitative analysis, and prediction of patient outcomes. His interests range from developing novel data-efficient machine learning algorithms to clinical deployment and validation of patient outcomes, both for medical imaging acquisition and subsequent analysis. He is also exploring combining imaging with clinical, natural language, and time series data.
This live panel discussion is part of the AI Happy Hour series, brought to you by Stanford AIMI and friends. We cover hot topics in AI in medicine as well as live questions & comments from attendees.
It's casual, insightful, and open to all!