Agenda | AI & Robotics in Medicine 2025 - Edwardson School of Industrial Engineering - Purdue University

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Monday, December 1

Time	Event
8:30 am – 9:00 am	Arrival & Networking
9:00 am – 9:30 am	Welcome Remarks
9:30 am – 10:15 am	Keynote 1: Robotics and AI: Opportunities and Challenges Richard Satava, MD FACS, PhD(hc) Professor Emeritus of Surgery, University of Washington Medical Center
	Even as this fourth revolution in surgery in 25 years (robotic surgery) continues to gain in acceptance, a much more disruptive change is beginning as the next revolution, Artificial Intelligence, which is just the tip of the iceberg that heralds the transition to remote telesurgery for remote (transcontinental) surgery . When combined with other information systems technologies, imaging systems, Virtual Reality (VR), molecular and genetic manipulation, and nanotechnology (to name a few), diseases will also begin to be cured at the cellular and molecular level, and non-invasively. Such systems are based upon the premise that robotics, AI and automation can bring precision, speed and reliability, especially as surgery ‘descends’ into operating at the cellular and molecular level. In addition when robotics combines with Artificial Intelligence (AI), the 5th and 6th generation (5G and 6G) telecommuications, supercomputing, and telesurgery, there will be an exponential increase in opportunities for innovation on a global scale. However, with these opportunities, there will also be significant challenges, not only technological, but also behavioral, humanitarian, political and ethical issues. The time has come to rethink what the future of robotics with AI can bring to surgery.
10:30 am – 11:30 am	Industry Lightning Presentations Tony Romano- Associate Director, Zimmer Biomet Advances in artificial intelligence and surgical robotics are transforming the future of total knee arthroplasty (TKA), offering new opportunities to understand and optimize the key drivers of patient outcomes and satisfaction. This presentation explores how AI-enabled robotic platforms can move beyond traditional mechanical alignment goals to provide a data-driven, patient-specific approach to knee reconstruction. As robotic systems enhance the precision of implant placement and enable real-time assessment of knee position, soft-tissue behavior, and intraoperative laxity, they generate an unprecedented depth of quantitative information. When combined with AI, these data streams allow surgeons and product teams to examine which variables—alignment, balance, patient morphology, or functional kinematics—most strongly influence postoperative recovery and long-term satisfaction. The session will address the ongoing debate between alignment-focused and balance-focused philosophies, highlighting how AI can help reconcile these approaches by identifying optimal combinations tailored to individual patients. By integrating robotics-driven accuracy with AI-assisted decision support, the next generation of TKA technologies has the potential to improve consistency, personalize surgical strategy, and ultimately elevate the standard of orthopedic care. Gordon G. Wisbach, MD, MBA, CAPT, MC, USN (RET) - Intuitive Surgical — “Surgical AI” Advances in artificial intelligence (AI) are reshaping the future of minimally invasive surgery, offering new opportunities to enhance precision, safety, and clinical decision-making. This presentation highlights Intuitive Surgical’s latest innovations integrating AI-driven capabilities across the surgical continuum—from preoperative planning and intraoperative guidance to postoperative analytics. We will review current applications, including automated tissue identification, real-time procedural insights, and workflow optimization within the da Vinci ecosystem. Emerging research in machine learning, computer vision, and data-enabled training will also be discussed. Together, these developments illustrate how AI can support surgeons, elevate performance, and improve patient outcomes in the next generation of robotic surgery. Timothy Kowalewski,PhD - Associate Professor, University of Minnesota; CTO & Co-Founder, LightSide Surgical Rachel Clipp,PhD - Assistant Director of Medical Computing, Kitware, Inc. — “Towards a Human Physiological Digital Twin with the Pulse Physiology Engine” Kitware is an open source research and development company with a focus on artificial intelligence. We work on projects in the medical space across a range of technical areas including computational physiology, medical triage, image analysis and segmentation, surgical simulation, and cyber-physical systems. Dr. Clipp will provide an overview of Kitware’s expertise in these areas and highlight specific projects related to these areas.
11:30 am – 12:30 pm	Federal Agency Panel Tyler Best, PhD - Acting Director, Health Science Futures, ARPA-H What if we could perform surgery autonomously? Surgery today is tethered to skilled practitioners with specialized training using manual approaches. Endovascular interventionists, for example, must perform intricate maneuvers of rudimentary devices through complex, delicate vessels using only static models and occasional 2D imaging. The availability of experts becomes paramount, creating impediments to care that are acutely felt in remote regions by patients of urgent conditions such as stroke. Contemporary technologies lack the perception, recognition, and therapeutic capabilities to treat patients autonomously, away from the active attention of a specialist. The Autonomous Interventions and Robotics (AIR) program launched by ARPA-H aims to catalyze the development of autonomous surgical robots. Systems that can perform parts, or all, of a procedure without direct human input can have a significant impact in the way surgery is provided, performed, and perceived. AIR approaches critical gaps in the availability and reach of surgery from two distinct angles. Technical Area 1 focuses on endovascular robotics to treat urgent conditions such as stroke where patient outcomes are affected by the availability of specialists. Technical Area 2 focuses on microbots—miniaturized and untethered devices—to enable new paradigms of surgery such as those performed in clinics under minimal supervision. Leveraging bold approaches and cross-disciplinary expertise, ARPA-H hopes to mobilize the shared ingenuity of the community to transform surgical care. Moria Fisher Bittmann, PhD - Program Director, NIH Col. Jeremy Pamplin, MD - Program Manager, Biological Technologies Office, DARPA Shivani Sharma, PhD - Program Director, NSF
12:30 pm – 1:30 pm	Lunch
1:30 pm – 2:15 pm	Keynote 2: AI’s Role in Upscaling Medical Practice Jason J. Corso, PhD Toyota Professor of AI, University of Michigan
	“Hey Siri, Can you measure my left ventricle ejection fraction?” Despite having full control over the zeitgeist, Artificial Intelligence (AI) has yet to live up to its promise in many fields. Medicine, in particular, has significant upside potential with AI—with hospitals closing, a shortage of physicians and other medical professionals, and an instrinsically difficult domain, AI has a unique opportunity to upskill practice, bringing better care and better training to everyone. This talk will explore the problem, potential value, and early methods in upskilling medical practitioners along two axes. First, I will describe how visual AI methods are already impacting the cardiothoracic surgical domain via technical and non-technical assessment for more objective training and review. Second, I will describe how interactive, physically-grounded AI guidance can upskill medical practitioners and bring state of the art care into rural settings, which are among the most challenging settings for healthcare delivery. Ultimately, this talk will provide concrete evidence of the potential AI has in upskilling medical practice.
2:15 pm – 3:15 pm	Academic Lightning Presentations Denny Yu,PhD - Purdue University — “Biobehavioral Sensing for Human-Aware Systems in Medicine” Biobehavioral sensing, e.g., computer vision and physiological monitoring, offers real-time, objective understanding into human cognitive states and behaviors. Integrating this information into robotic and AI systems enables human-aware technologies that dynamically respond to users’ physical state, cognitive load, and situation awareness to support decision-making. This talk will explore opportunities and challenges in biobehavioral AI across healthcare applications. Dimitrios Stefanidis,MD, PhD - Indiana University — “Artificial Intelligence in Surgical Education: Transforming Training, Assessment, and Skill Development” Surgical education faces several challenges related to the introduction of new technologies and techniques, increasing complexity of surgical patients, scrutiny of surgical performance, and optimization of patient outcomes. Artificial intelligence promises to overcome many of these challenges by introducing solutions not available to surgical educators previously. Advances in large language models, computer vision, and deep learning, offer unique opportunities to augment surgical education by enabling objective skill assessment, timely feedback provision on trainee performance, intraoperative guidance, training need identification, decision aid support, simulation training enhancement, and resource utilization. In this presentation, we will review promising applications of AI in surgical education and identify the most pressing needs for AI tool development to enhance surgical training. David Cappelleri,PhD - Purdue University — “AI Opportunities in Microrobotic Surgery” In this talk, I will highlight some recent advances in microrobotic surgical applications, providing examples of different types of families of wireless mobile microrobots driven by external fields for biomedical applications. I will then discuss future opportunities where AI can enhance microrobotic surgical applications in nearly every stage – from design and control to real-time operation and post-procedure analysis. Andrew Gonzalez,MD, PhD - Indiana University — “Labels, ontologies, and tasks: Oh My!!” Mimicking human clinician reasoning requires not only integrating multimodal data but also balancing efficiently training models to learn generalizable representations against clinical trust and verifiability. We discuss best practices for labelling, ontology development, and task formulation in the setting of interdisciplinary teams. We will explore opportunities to scale multimodal multitask learning within the CTSI ecosystem.
3:15 pm – 4:15 pm	Topic Break-out Groups Embodied AI Field & Frontier Medicine Autonomous Labs Simulations, Hubs & Data Sets
4:15 pm – 4:45 pm	Group Discussion Summaries and Next Steps
4:45 pm – 5:00 pm	Closing Remarks
5:00 pm	Networking Reception

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