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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), Dr. Govind Thirumalai (Avera Health), Dr. Shivaram Poigai Arunachalam (Mayo Clinic), Erica DeBoer (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 SDSU

This talk will introduce and showcase the capabilities of the Computer Vision Team at South Dakota State University. 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.

Talk Abstract

Many of today’s most important real-world problems involve data that is complex, sparse and unevenly distributed. From forensic handwriting analysis and drug source attribution to detecting rare or anomalous patterns in satellite imagery, we often face hundreds of categories of interest — but only a small number of examples in each. Traditional statistical methods and modern artificial intelligence systems, which typically depend on large, well-balanced datasets, struggle under these conditions.

In this talk, Semhar Michael will present new algorithmic approaches designed to learn reliably from limited data by sharing information across related categories. These methods uncover hidden structure in high-dimensional datasets while improving stability, accuracy and fairness — especially in settings where conventional AI models can be biased or fragile.

Attendees will learn how these techniques can enable more objective evaluation of forensic evidence, support law enforcement and intelligence analysis, and strengthen decision-making in high-stakes environments where data scarcity is the norm rather than the exception. Beyond law and security, the approaches discussed are broadly applicable to scientific, medical and social domains that demand trustworthy insights from small or imbalanced datasets.

This session offers a practical and conceptual look at how next-generation AI can move beyond “big data” assumptions to deliver robust, ethical and impactful results in data-constrained settings.

Nicholas C. Butzin directs the Synthetic Biology and Biocomputing Laboratory at SDSU 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.

South Dakota State University’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 SDSU’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 SDSU 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

Abstract coming soon.

Panelists: Major General Mark Morrell, Martin R. Apprich, Lieutenant Zachary Sorenson, Dan Gunn
Moderated by: TBD

National security is entering a decisive era. The convergence of artificial intelligence, autonomous systems and intelligent decision support is reshaping how nations anticipate threats, protect critical infrastructure and maintain strategic readiness. This panel brings together leaders from defense, intelligence, research and industry to explore how AI is already transforming national security across domains — from cybersecurity and intelligence analysis to logistics, resilience and crisis response.

At the center of this discussion is a critical question: How can the United States harness AI to maintain decisive military and strategic superiority across domains, while ensuring reliable, accountable human control in high-stakes operations? The panel will examine:

Preparedness: How AI enhances early warning, situational awareness and threat detection across cyber, physical and information domains.

Resilience: How intelligent systems support supply-chain integrity, infrastructure protection, disaster response and operational continuity.

Decision Advantage: How AI augments — rather than replaces — human judgment in high-stakes, time-constrained environments.

Panelists will also grapple with the hard questions: How do we guard against adversarial AI, data poisoning and overautomation? What level of transparency and explainability is required for national security systems? How do we ensure a skilled workforce that understands both the power and the limits of AI? And how do public-sector institutions adopt AI responsibly at the speed demanded by modern threats?

This session will surface real-world use cases, governance frameworks and emerging best practices — highlighting how AI is becoming foundational infrastructure for national security, and why regional ecosystems that integrate academia, industry and government are essential to building secure, resilient and trustworthy systems for the future.