Speaker: Ivo D. Dinov, Henry P. Tappan Collegiate Professor, SOCR, DCMB and MCAIM, University of Michigan

Time: Wednesday, September 30, from 2:30 pm to 3:30 pm

Location for in-person participants: 1146 FAB

Zoom link for online audience: https://wayne-edu.zoom.us/j/92845590121?pwd=CpRA5Wa5gzSMn2xiVkR2abD83O5nrH.1

Title: The Realities of Augmented Intelligence

Abstract: This decade, the evolution of computational intelligence (algebraic thought) has reached a critical juncture, shifting the paradigm from Artificial Intelligence (AI) as an autonomous agent to Augmented Intelligence (AuI) as a collaborative partner. This talk navigates 3 topics. First, the technical and philosophical trajectory of this transition, beginning with the historical foundations of Artificial Neural Networks (ANN). Second, one example of a novel mathematical representation framework (complex-time, kime) that supports truly innovative AI inference based on kime-manifolds, with applications in medical imaging, global economic forecasting, and healthcare. And third, AI societal implications, academic mission, and tension between technological acceleration and human values. The reality of augmented intelligence lies not in the creation of a "digital god," but in the sophisticated, mathematically grounded extension of the human mind.

Bio: Ivo Dinov is the Henry Tappan Collegiate Professor at the University of Michigan. He directs the Statistics Online Computational Resource and its foundational and Generative AI Modeling (GAIM) research. Dr. Dinov is the principal developer of complex-time (kime) representation of repeated measurement longitudinal data. The induced spacekime analytics support innovative ML/AI developments using the computationally richer kime-surface representations of time-varying processes. This technique is applicable for modeling many spatiotemporal processes, including medical imaging.

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AIDaS: CAD Seminar Series

Advancing Knowledge, Innovation, and Collaboration in Computation, AI, and Data Science (CAD)

The CAD Seminar Series is a primary seminar series at Wayne State University’s Institute for AI and Data Science (AIDaS). It is a dedicated platform for advancing knowledge, fostering innovation, and promoting collaboration across the fields of Computation, Artificial Intelligence, and Data Science. This series brings together leading experts, researchers, and professionals to explore the latest developments, tackle emerging challenges, and drive forward-thinking solutions at the convergence of these critical disciplines.

Objectives:

• Advance Knowledge: Share cutting-edge research and insights that push the boundaries of what is known in CAD.

• Foster Innovation: Encourage the development of novel ideas and solutions through interdisciplinary dialogue and creative thinking.

• Promote Collaboration: Unite expertise across disciplines and build bridges between academia, industry, and government to address complex problems and create opportunities for joint ventures.

Target Audience: The CAD Seminar Series is designed for a diverse audience, including faculty, researchers, students, and professionals in Computation, AI, Data Science, and related fields. It serves as a forum for exchanging ideas, networking, and contributing to the growth of these rapidly evolving areas. We highly recommend in-person attendance to enhance engagement and networking opportunities with speakers and fellow participants.

Call for Participation: We welcome contributions from researchers, practitioners, and students. Whether presenting your work, participating in discussions, or attending as a learner, your involvement is crucial to the success of this collaborative initiative.