What Makes a Model a Digital Twin? An Atmospheric Science-based Perspective

Speaker: Dr. Dev Niyogi

Professor and William Stamps Farish Chair, The University of Texas at Austin

4:30 P.M. Reception
5:00 P.M. Lecture
Sharp Lecture Hall, Arms Building - California Institute of Technology

Registration is required for this lecture as seating is limited. Register here: https://forms.office.com/r/a2KbwB7KCm

Abstract:

This presentation explores the evolution of digital twins from traditional modeling approaches. While models have long served as the backbone of knowledge representation and scenario development, digital twins have emerged as notable tools in the recent Artificial Intelligence/Machine Learning (AI/ML) era. Though conceptualized over three decades ago, the recent popularization of digital twins into prominence comes with hundreds of applications, accompanied by numerous definitions.

This talk examines a curiosity-driven question: What is the difference between a model and a digital twin? What are some of the characteristics or defining attributes of a digital twin? By analyzing their defining characteristics and applications, the talk will seek to explore this distinction. By virtue of the expertise and applications undertaken, the perspectives is grounded in atmospheric modeling and urban infrastructure applications, but it is suggested that the conclusions and perceptions transcend specific domains, offering generalizable principles applicable across disciplines.

Speaker's Biography:

Dr. Dev Niyogi is a Chair professor at The University of Texas at Austin, and Professor Emeritus at Purdue University. His research seeks to significantly contribute to our understanding of the Earth system, particularly the urban and agricultural landscapes, and the dynamic role of coupled land surface processes on regional hydroclimatic extremes. He leads the Atmospheric Urban Digital Twin activity as part of WMO/World Climate Research Programme Digital Earth initiative.