Ayman Jumaa

Applied Bytetrack to identify and track insulators. Designed a solution to solve the problem of the reidentification of non-unique objects, i.e insulators, using Gunnar Farneback's optical flow algorithm. Python was used for the implementation.

Researched deep learning, convolutional neural networks, and object detection. Worked with C and Python codes to implement training, validation, and inference stages of YOLOv3. achieved an mAP of 99.1% in detecting defective insulators in high voltage power lines.

Developed and designed android applications for small businesses and universities using Java, XML, and MySQL.

Developed and maintained software for small businesses using C++ and MySQL.

Notable coursework: AUTOSAR, Specification and Verification, Integrated Systems, Parallel Programming, Compiler Optimization, Software Design for Embedded Systems.

Graduation Project: Super-Resolution via Sparse Representation over Multiple Learned Dictionaries using Sharpness Measure. ABET-accredited program.

Notable coursework: Electric and Electronic Circuits, Control Theory and Systems Design, Algorithms and Data Structure, Signal Processing, Advanced Programming (C++/Matlab), Operating Systems.