AI and Data-Driven Approaches for Forecasting, Control, and Model Discovery in Complex Engineering Systems
This talk explores how AI-driven techniques — including machine learning — can enhance time-series prediction, attractor reconstruction, and digital twin development. Topics include supervised and unsupervised prediction of critical transitions in complex systems such as climate and power grids, and data-driven model discovery using Kolmogorov-Arnold Networks.
Case studies cover AI-assisted forecasting of the Atlantic Meridional Overturning Circulation, and a vision for an ongoing project on physical AI addressing fundamental challenges in electrical and computer engineering across multiple disciplines.
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- 400 Isotope Dr.
- Fort Collins, Colorado
- United States 80525
- Building: Engineering
- Room Number: B101
- Starts 09 April 2026 06:00 AM UTC
- Ends 15 April 2026 06:00 AM UTC
- No Admission Charge
Speakers
Walt Slade of K D Johnson, Inc
AI and Data-Driven Approaches for Forecasting, Control, and Model Discovery in Complex Engineering Systems
Biography:
Dr. Shirin Panahi
Assistant Professor of Electrical and Computer Engineering
Bio
Shirin Panahi received her Bachelor’s degree in Electrical Engineering from Sadjad University of Technology, Mashhad, Iran, in 2014. She earned her M.S. and Ph.D. degrees in Biomedical Engineering from Amirkabir University of Technology in Tehran, Iran, in 2016 and 2020, respectively, where her research focused on emergent collective behaviors in neuronal networks.
Following her Ph.D., she joined the University of New Mexico and Arizona State University as a postdoc fellow. Her work has spanned a wide range of topics in complex systems, including dynamical network analysis, model predictive control, and machine learning applications for time-series prediction and control. During her postdoc, she expanded her research into interdisciplinary domains, applying AI-based methods to ecological networks, climate systems, and nonlinear dynamics.
She joined the Department of Electrical and Computer Engineering at Colorado State University in 2025 and is passionate about advancing collaborative, data-driven science at the intersection of engineering, neuroscience, and complex systems. Her research interests are data-driven modeling, neuroscience, time-series prediction, and control in nonlinear and networked systems.
Education
- B.S. 2014 Sadjad University of Technology in Electrical Engineering
- M.S. 2016 Amirkabir University of Technology in Biomedical Engineering
- Ph.D 2020 Amirkabir University of Technology in Biomedical Engineering
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Agenda
Doors Open 6:00pm
Networking from 6:00-6:30pm
Announcements and Welcome-6:30- 6:45 pm, Jim Cale
Did Y'know-6:45-7:00 pm- Scott Evans
Technical Presentation 7:00-8:00 pm, Dr. Panahi
A light snack will be available, probably Pizza and Soft drinks