Table leaders will lead focused discussions on prominent themes in engineering in healthcare, encouraging participants to exchange expertise, consider new approaches, and build connections around shared areas of interest.
The goal of this activity is to spark meaningful dialogue across disciplines and build connections that can evolve into fruitful post-symposium collaborations.
Faculty Facilitators: Russell H. Taylor
Postdoctoral Facilitator: Amama Mahmood
Ambient AI systems, which operate “in the background” of clinical environments, can assist clinicians with tasks such as documentation, workflow optimization, and real-time decision support. At this roundtable, participants will discuss current and future opportunities for the use of ambient AI, as well as the challenges of developing systems that work seamlessly together with clinicians, including the integration of advanced speech recognition, contextual understanding, and multimodal sensing technologies—plus considerations for trust, reliability, and workflow alignment.
Faculty Facilitator: Harold P. Lehmann
Postdoctoral Facilitator: Taylor Bobrow
Consumer-facing AI tools like ChatGPT are reshaping how people access health information and manage their care. Participants at this roundtable will discuss how these technologies influence patient behavior and health literacy, as well as early detection and self-management of disease. We will also discuss concerns related to the widespread use of these tools, such as accuracy and privacy, and the impact of these tools on the broader healthcare system, including shifts in patient-clinician dynamics, evolving expectations for digital health guidance, and the need for safeguards that ensure safe, equitable, and trustworthy use.
Faculty Facilitator: Lalithkumar Seenivasan
Postdoctoral Facilitator: Jie Gao
Student Facilitator: Drew Prinster
How are clinical AI tools assessed once they’re deployed? At this roundtable, we will discuss current approaches for tracking and evaluating the performance of AI tools in the clinic, and discuss challenges that arise in practice for continuous monitoring of both traditional predictive models and generative AI applications, including issues of data drift, model degradation, safety oversight, and real-world alignment.
A wide array of vendors currently develop and offer AI tools for healthcare applications (e.g., Epic offers a variety of AI integrations, and various radiology med-device companies offer their own AI tools). Meanwhile, large for-profit AI labs have turned their focus to AI applications in health (e.g., OpenAI). At this roundtable, participants will discuss a central question: What is the role of academia in this landscape in terms of developing and validating AI tools, and how can academic institutions uniquely contribute to transparency, independent evaluation, methodological innovation, and public-interest research in a rapidly commercializing ecosystem?
Faculty Facilitator: Emily E. Haroz
Postdoctoral Facilitator: Danielle Ripsman
How can AI tools be developed, deployed, and evaluated in ways that protect patients, ensure fairness, maintain transparency, and uphold clinical accountability? Participants will consider challenges such as bias, data privacy, regulation, and model reliability, and the responsibilities of clinicians and developers as AI becomes more deeply integrated into healthcare—including questions of governance, real-world monitoring, explainability, equitable access, and the balance between innovation and risk.
Faculty Facilitator: Jeremy D. Brown
Postdoctoral Facilitator: A. Michael West, Jr.
Robotics and AI are reshaping clinical care, from surgical assistance and rehabilitation technologies to automated diagnostics and hospital operations. At this roundtable, participants will discuss current capabilities, emerging innovations, and the opportunities and challenges of integrating intelligent robotic systems into everyday medical practice, including issues of safety, autonomy, workflow fit, human-robot collaboration, and the shifting roles of clinicians as robotic intelligence advances.
Faculty Facilitator: Kimia Ghobadi
Postdoctoral Facilitator: Yeganeh Shahsavar
Student Facilitator: Shanshan Song
AI-enabled wearables and connected devices are transforming continuous care and telehealth by providing real-time monitoring, early detection of health changes, and personalized feedback for patients. Participants at this roundtable will discuss the current and potential benefits of these tools, as well as the challenges of realizing their full potential, including issues of data quality, patient adherence, integration with clinical workflows, equitable access, and the reliability of AI-driven inferences outside controlled environments.
Faculty Facilitator: Gregory D. Hager
Postdoctoral Facilitator: Laura Connolly
AI is transforming disease diagnosis and management by enhancing accuracy, speeding up detection, and enabling personalized treatment strategies. At this roundtable, participants will discuss how machine learning and predictive analytics are being applied to improve clinical decision-making, optimize care pathways, and support better outcomes for patients across a range of conditions—while also grappling with challenges related to data quality, clinical adoption, model transparency, equitable performance, and the translation of algorithmic insights into actionable care.