My name is Mohannad Elhamod. I am a doctoral candidate in Computer Science at Virginia Tech (VT). I am a member of the Science-Guided Machine Learning group, supervised by professor Anuj Karpatne. I have earned an M.Eng degree in Electrical and Computer Engineering at McGill University under the supervision of professor Martin D. Levine. I had also earned a B.S. degree in Computer Engineering at Jordan University of Science and Technology. I have also gained industry experience as a software engineer at Microsoft for over six years.
My research is interdisciplinary and at the intersection of machine learning and scientific discovery in several domains, such as physics and biology. In my research, I work on bridging the gap between machine learning approaches and human knowledge. This effort is quintessential for ensuring that machine learning models, which have pervaded all aspects of life, do not violate priors established by experts. Such effort safeguards the integration of machine learning into science and society. I am also interested in machine learning visualization and explainability. This research direction advocates for machine learning models that are more transparent with their decision-making process, and thus less susceptible to incorporating social biases, and more trustworthy to scientists and experts.
I have always valued my relationships with my teachers and mentors. Over the years, I have strived to take advantage of all teaching opportunities I have come across, including being a teaching assistant for four graduate and undergraduate classes, and being the instructor of record for a capstone senior undergraduate class. My teaching philosophy is centered around engaging with my students at an intellectually stimulating level, and arousing their curiosity to explore.
In my free time, I have enjoyed participating in the community, including serving as a board member of the Computer Science Graduate Council, hosting talks about the struggles of graduate students, doing stand-up comedy, and capturing the beauty in people and places around me with my camera.