At Computational Analysis and Acceleration Research Group (CARG), we develop data-driven solutions to tackle real-world challenges in biomedical, communications and surveillance applications. We combine physical models with machine learning models that account for uncertainty, ensuring our systems are robust and ready for real-life conditions. Our researchers are involved in all stages of the processing pipeline, from experiment design and data collection to data processing and the development of machine learning models for our applications, including UAV detection and inspection, as well as patient data for wearable and contactless medical solutions. To date, more than 70 graduate students and postdoctoral researchers have been part of our multidisciplinary team.

Areas of Focus:
1. Biomedical & Automotive Innovation We collaborate with medical and industry partners to design signal processing algorithms and machine learning models for patient monitoring and counter-UAS systems.
2. Integrated Modelling & Simulation Our team focuses on modeling and simulation to better understand complex physical problems before deploying practical solutions.
3. Computational Efficiency We harness hardware accelerators—including GPUs and FPGAs—to achieve real-time performance and scalability.

Computational Analysis and Acceleration Research Group

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