CENTER FOR DYNAMICS, INTELLIGENCE AND LEARNING SYSTEMS (CDIALS)
Advancing Intelligent Technologies Through Dynamic Systems Research
The Center for Dynamics, Intelligence and Learning Systems (CDIALS) brings together researchers across engineering disciplines to advance the modeling, analysis, control and analytics of dynamic systems. Through innovations in artificial intelligence, machine learning, robotics, transportation systems, biomedical engineering and educational technology, CDIALS develops solutions that improve human health, safety, mobility and learning.
Founded in 2026 through the merger of the Center for Nonlinear Dynamics and Control and the Villanova Center for Analytics of Dynamic Systems, CDIALS represents one of the College of Engineering’s largest interdisciplinary research communities.
ABOUT THE CENTER
Dynamic systems are everywhere—from autonomous vehicles and robotic systems to transportation networks, physiological processes and intelligent educational technologies. Understanding how these systems behave, adapt and learn is essential to solving some of society’s most complex challenges.
The Center for Dynamics, Intelligence and Learning Systems advances research at the intersection of:
- Dynamic Systems
- Artificial Intelligence and Machine Learning
- Data Analytics
- Control Systems
- Robotics and Autonomous Systems
- Biomedical and Physiological Modeling
- Transportation Engineering
- Educational Innovation
By combining physics-based understanding, engineering principles and data-driven intelligence, CDIALS develops technologies that are both innovative and trustworthy.
RESEARCH AREAS
Developing intelligent control systems that enable robots and autonomous technologies to operate safely, reliably and efficiently in complex environments.
Advancing methods that combine machine learning with engineering knowledge to improve prediction, diagnostics, decision-making and system performance.
Applying dynamic systems theory and data analytics to transportation infrastructure, traffic systems, mobility patterns and public safety.
Using advanced modeling, sensing and analytics to improve healthcare, understand physiological processes and support clinical decision-making.
Creating predictive tools that identify system degradation, anticipate failures and improve reliability in engineered and biological systems.
Exploring new approaches to teaching and learning through intelligent technologies, robotics, AI-enabled learning environments and engineering education research.
Center for Dynamics, Intelligence and Learning Systems (CDIALS)
College of Engineering
Villanova University
C. Nataraj, PhD
Director
(610) 519-4994
c.nataraj@villanova.edu
Garrett Clayton, PhD
Co-director
(610) 519-4798
garrett.clayton@villanova.edu