I am a Computer Science expert, 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 magna 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 UAVs, medical images, industrial power 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 and won the Best Paper Award for the year 2026.
I am currently working as a Postdoctoral Research Fellow at KU under the management of Dr. Abdulhadi Shoufan, tackling the area of Secure UTM systems.
Ahmad Obeid 