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Electrical and Computer Engineering

Biomedical Sensing, Imaging, and Analytics Laboratory


Research Directions 

  1. Deep Learning Classifiers with Optical Coherence Tomography (OCT) Imaging Systems:
  • Develop image classifiers using deep convolutional neural networks (CNN) for quantitative grading of dental caries. 
  • Analyze optical coherence tomography (OCT) images quantitatively for characterization of human oral tissues.
  • In collaboration with Dr. Mina Mahdian of the Stony Brook University School of Dental Medicine, and University of Connecticut Health Center.
  • Received AAOMR XDR Grant (2018-2019).
  1. Photoacoustic Imaging and Sensing Systems 
  • Design and implement a miniaturized and low-cost linear laser scanner controlled by embedded systems for photoacoustic sensing and imaging.
  • Analyze photoacoustic images using machine learning, pattern recognition, and image/signal processing techniques.
  1. Internet of Things (IoT) in Healthcare System using Sensors
  • Develop IoT embedded systems with sensors for health monitoring.
  • Analyze sensor data using machine learning models.