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Keynote presentation by Dr. David Newman, chief medical officer for virtual care at Sanford.

Panelists: Dr. D. Shivakumar (Revolution Medicines), Dr. P. Woodard (Monument Health), Dr. D. Newman (Sanford)

Moderated by: TBD

Health care is undergoing a historic reinvention. The convergence of advanced AI, digital health agents and physical AI systems is reshaping how we discover, deliver and experience care. This panel brings together leaders from medicine, industry and technology to explore how AI is already transforming the full continuum of health: accelerating drug discovery, enabling earlier and more accurate diagnostics, extending care into homes and rural communities, and powering next-generation intelligent devices.

At the center of this discussion is a critical question: Can AI help solve health care’s longstanding challenges of access, affordability and quality — and do so responsibly?
We will examine:

• Access: How AI-enabled diagnostics, devices and digital health agents are expanding care to underserved and rural populations.
• Affordability: How AI can bend the cost curve through faster drug development, reduced administrative overhead and smarter automation.
• Quality: How AI is improving precision, safety and outcomes while preserving the human connection that defines excellent care.

Panelists will also grapple with the hard questions: Will clinicians lose diagnostic skills? How will payers respond to AI-driven care models? Can integrity be safeguarded as innovation accelerates? What does trustworthy, transparent medical AI look like?

This session will illuminate the models, lessons and real-world implementations emerging today — showing how AI is moving from molecule to market and why our region is uniquely positioned to lead in building a more accessible, resilient and patient-centered health care future.

AI for Computer Vision at ÈÕ±¾avÊÓƵ

This talk will introduce and showcase the capabilities of the Computer Vision Team at ÈÕ±¾avÊÓƵ. Highlights will include intelligent vision systems for civil infrastructure and agriculture, 3D perception and scientific imaging for object pose estimation and reconstruction, and multimodal intelligence for monitoring and information retrieval systems. Applications will include AI-based construction site safety monitoring systems, visual question answering systems and early work on intelligent tutoring systems and explainable AI.

Semhar Michael's Abstract

Nicholas C. Butzin directs the Synthetic Biology and Biocomputing Laboratory at ÈÕ±¾avÊÓƵ where his research bridges genetic circuits, microbial decision-making and computational modeling.

He is the recipient of an NSF CAREER Award for his work on cellular memory and biological control systems and leads interdisciplinary projects advancing the design and analysis of programmable biological systems. He is also a colead on a major EPSCoR-supported initiative developing an AI-driven molecular discovery platform for new antimicrobial agents. This work uses generative AI and high-throughput computational screening to identify molecules that disrupt bacterial cell death pathways, inhibit biofilm maintenance and neutralize fungal toxins. The effort carries broad societal implications — from combating antimicrobial resistance to improving food safety — and builds regional capacity through shared AI/ML infrastructure, expanded assay capabilities, and K–12 and undergraduate STEM training.

Butzin has published extensively in synthetic biology and systems microbiology and is deeply committed to student mentorship and integrating research into undergraduate and graduate education.

ÈÕ±¾avÊÓƵ’s new Center for AI Innovation and Emergent Technologies is shaping a bold, future-focused vision for how land-grant universities can lead in the AI era. This session will introduce attendees to ÈÕ±¾avÊÓƵ’s cross-disciplinary blueprint for bringing artificial intelligence into every corner of teaching, research and community impact — from agriculture and biotechnology to health care, education, VR/XR and beyond.

Participants will learn how the Center is building an AI-across-the-curriculum ecosystem that equips students, faculty and professionals with practical skills: foundational AI literacy, applied problem-solving, responsible use and hands-on experience with emergent technologies. The talk will highlight strategies for designing ethical, unbiased, research-ready AI applications; fostering collaboration across colleges; and preparing South Dakota’s workforce and industries for rapid technological change.

Attendees will leave with a clear understanding of:

• How ÈÕ±¾avÊÓƵ is integrating AI into research, pedagogy and workforce development
• Practical models for building responsible, human-centered AI programs at scale
• Examples of domain-specific innovations emerging across agriculture, biotech, healthcare and immersive technologies
• How universities can partner with industry, government and communities to create economic and educational impact

This session will provide a compelling, actionable look at what it takes to lead AI innovation in a land-grant institution — and how these advances translate into real opportunities for the region and the nation.

Agentic Workflows at Scale: Transforming AI Development Practices

Session Abstract

AI development is shifting from single-model tasks to interconnected, autonomous workflows and teams need new practices to keep up. In this session, attendees will learn how agentic workflows work, why they matter now and how to apply them across real engineering and AI operations environments.

We’ll clarify what agentic means in practical terms — goal-driven agents that plan, remember and execute multistep processes — and show how this model improves scaling, reliability and collaboration. Participants will see concrete examples from software development, MLOps, infrastructure automation, and AI monitoring to understand where agentic systems already outperform traditional approaches.

The session will also equip attendees with a clear framework for governance, guardrails and cost monitoring, including role-based access, auditability, prevention of runaway automation, real-time cost dashboards and agent-level budgeting.

We’ll close with lessons from early adopters, highlighting where teams gained efficiency, where they struggled, and what’s coming next as organizations move toward fully autonomous AI ecosystems.

Attendees will leave with:

• A clear mental model of agentic workflows
• Practical examples they can adopt immediately
• Strategies for governance and cost control
• Insight into the future of scalable AI development

Abstract

Abstract

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