Signal Processing, Image Processing, Graph Signal Processing, Medical Imaging, Magnetic Resonance Imaging, Magnetic Particle Imaging, Machine Learning, Deep Learning, Computer Vision.
Novel framework is proposed to represent sets of time-series signals using non-negative kernel (NNK) graph construction. The original NNK framework is extended to allow explicit delays as part of the graph construction. Propoesed framework is applied on EEG signals.
NNK algorithm is applied on the penultimate layer feature space of a neural network and polytopes are formed around each feature. Polytopes have geometric properties that are shown to be predictive in the neural network’s performance. Geometric properties are also informative for enhancing the manifold representation or designing the types of data augmentation.
The goal is to match ads with the contextually related scenes, and to place ads naturally to the background of the scenes, considering the surface geometry, scene change, saliency, occlusion problem and semantic similarity between the ads and the scenes. Deep learning, speech processing and computer vision techniques were used. Patent application in progress.
The aim is to detect faces and license plates in fish-eye or 360° images and blur them to protect the privacy, using planar transformation, object detection and segmentation techniques.
Simulation and experimental analysis of how the safety limits on human subjects affect the image quality of MPI images, as the ultimate goal is to use MPI as a new medical imaging modality for human scanning. Hardware experiments were conducted with phantom objects and 1D MPI images were attained at different scanning parameters. New receiver coil was designed for the MPI system using Solidworks and Matlab. Image reconstruction simulations were conducted in Matlab.
Bresenham's line algorithm implementation with VHDL programming.
Java project for configuring modems and computers, including UI.
Teaching Assistant in Courses:
EE510-Linear Algebra (Spring 2022)
EE503-Probability (Fall 2021)
EE563- Estimation Theory (Spring 2021)
Teaching Assistant in Courses:
EEE212- Microprocessors (Spring 2015, Summer 2015)
GE301- Science, Technology, and Society (Fall 2015, Spring 2016, Fall 2016, Spring 2017, Fall 2017)
GE304- Technology, Society, and Professional Development Seminar (Spring 2017)
GPA: 3.63/4.00
GPA: 3.52/4.00
GPA: 3.912/4.000
GPA: 3.42/4.00