I am a Computer Science researcher, specializing in signal processing, classical machine learning, and deep learning. My BSc was in Electrical Engineering with a minor in Applied Mathematics. This gives me a strong, low-level understanding of the mathematical concepts. I graduated cum laude, and I am a member of the (IEEE-HKN) honor society, and my BSc project was hosted on national TV!
During my MSc, PhD and the research work that I undertook in between them, I was trained on various ML/DL techniques and worked on many types of signals; from sound waves to time-series data, to genomic data, to images and natural language texts. I like to apply the versatile tools I learned/developed to various applications, such as medical images, industrial plants, areal images, and I am always on the lookout for state-of-the-art techniques and modern deep learning tools.
My MSc and PhD were both under the supervision of Prof. Naoufel Werghi. I was awarded The Top Publication Award for my MSc work. I received the Best Paper Award for part of my PhD Thesis. During the year between MSc and PhD, I worked as a Research Associate investigating genomic data, and developed a novel autoencoder-based pipeline of gRNA discovery, which was published in a top 2% journal.
I am currently working on an AI solution to combat health insurance fraud. My solution is patent pending and is in the stage of fund raising.
Ahmad Obeid 