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“Facts are many, but the truth is one.” ― Rabindranath Tagore
The primary focus of CDSL research is to study real-world dynamical systems, both from natural and engineered origins, through an interdisciplinary approach.
At CDSL, we integrate theoretical, experimental, and computational research to create a comprehensive research program with three key objectives:
(Objective 1) study of interactions in real-world networked systems,
(Objective 2) contribute to data analysis tools for modeling real-world interactions and complex systems,
(Objective 3) build bio-inspired robust artificial systems using analytical frameworks.
CDSL research is supported by the National Science Foundation (CMMI-2238359).
CDSL research summary:
Facilities:
Virtual-Reality multi-driver (networked) driving simulators with motion platforms
Dry Electrode EEG Headset (DSI-24 - Wearable Sensing)
Current research projects:
Data-driven multiscale modeling of complex traffic systems utilizing networked driving simulators (NSF CAREER Award)
Relevant publications:
Ramlall, P., & Roy, S. (2025). A Data-Driven Framework for Modeling Car-Following Behavior using Conditional Transfer Entropy and Dynamic Mode Decomposition. Applied Sciences, 15, 9700.
Ramlall, P., & Roy, S. (2025). Data-driven car-following traffic modeling using dynamic mode decomposition (accepted for presentation at MECC 2025)
Ramlall, P., Jones, E., & Roy, S. (2025). Development of a networked multi-participant driving simulator with synchronized EEG and telemetry for traffic research. Systems, 13, 564.
Lane, D., & Roy, S. (2024). Validating a data-driven framework for vehicular traffic modeling. Journal of Physics: Complexity, 5(2), 025008.
Ramlall, P., & Roy, S. (2024). Determining critical vehicle connectivity in connected autonomous vehicles using information theory. IFAC-PapersOnLine, 58(28), 995–1000 (MECC 2024).
Lane, D., & Roy, S. (2023). Using information theory to detect model structure with application in vehicular traffic systems. IFAC-PapersOnLine, 56(3), 367–372 (MECC 2023).
Multimodal collective behavior modeling: integrating visual, auditory, and offset vision sensing using agent-based approaches
Relevant publications:
Ramlall, P., Roy, S., 2025: "The role of sensory cues in collective dynamics: a study of three-dimensional Vicsek models", Applied Sciences
Roy, S., Lemus, J., 2021:"How does the fusion of sensory information from audition and vision impact collective behavior?", Frontiers in Applied Mathematics and Statistics
Lemus, J., Roy, S., 2020: "The Effect of Simultaneous Auditory and Visual Sensing Cues in a Two-Dimensional Vicsek Model", Proceedings of the ASME Dynamic Systems and Control Conference (DSCC)
Past research projects: (click on each topic to learn more)
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