SPEAKER: Dr. Ahmad Dhaini, assistant professor of Computer Science at the American University of Beirut (AUB)
ABSTRACT: In this talk, we discuss a case study on how automated solution using computer science methods such as machine learning and image analysis can help in clinical decision-making. Namely, we discuss a novel automated solution that evaluates the presence of corneal haze in optical coherence tomography images for keratoconus patients that underwent cross-linking. Results demonstrate the efficacy and effectiveness of the proposed techniques vis-a-vis manual measurements in a much faster, repeatable and reproducible manner.
BIOGRAPHY: Ahmad Dhaini is currently an assistant professor of Computer Science at the American University of Beirut (AUB), and visiting assistant professor at University of Waterloo, while on leave from AUB. He received his B.Sc. in Computer Science from AUB in 2004, his M.Sc. degree in Electrical and Computer Engineering from Concordia University, Canada in 2006, and his Ph.D. degree in Electrical and Computer Engineering from University of Waterloo, Canada in 2011, where he was granted several research and teaching awards.
Before joining AUB, Dr. Dhaini was a Postdoctoral Scholar at Stanford University, working in the Photonics and Networking Research Laboratory (PNRL) after being awarded the Natural Sciences and Engineering Research Council of Canada Postdoctoral Fellowship (NSERC PDF). He also completed the Stanford Ignite program for entrepreneurship and innovation; it is a mini-MBA program in Stanford’s Graduate School of Business, designed to teach scientists how to convert an idea into a business.
Dr. Dhaini’s research interests cover several themes of optical networks such as fiber-wireless (FiWi) broadband access networks, mission-critical networks, green communications, and software-defined networking. He has been also tackling several research problems related to Biotechnology, especially in medical image analysis, medical wearable devices, and mobile health.
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