Sayan Mandal is a Ph.D. student in Electrical and Computer Engineering at Duke University. His research interests are deep learning, computer vision, and machine learning. He is currently working in the Duke Visual Performance Laboratory (DVPL), where he is developing deep learning models - CNN and transformer networks, to analyze and detect glaucoma progression from time-dependent medical images and clinical data.
A KVPY scholar sponsored by Govt. of India, he received B.Tech. in Aerospace Engineering from the Indian Institute of Technology, Kharagpur in 2019 and then joined DVPL at Duke University Hospital. Most of his research in DVPL is related to developing deep learning algorithms to identify and predict progression of glaucoma in its early stages. Previously, he has developed a machine learning algorithm for detecting drones for Human and Autonomy Lab's Prison Reconnaissance Information System (PRIS) and has briefly worked in the same lab to design and optimize a Naval Aircraft Carrier Simulator.
He is well versed in advanced deep learning, machine learning, and computer vision concepts, including natural language processing. Being in multiple labs and research positions has instilled in him qualities of leadership, communication, self-management, and problem-solving skills. Additionally, having worked as a Graduate Research Assistant for two years and a summer research internship experience, he is proficient in coding languages such as Python and JAVA and libraries such as Pytorch and Keras (Tensorflow).