Rasha Alshawi

Rasha Alshawi is an Assistant Professor in the MS in Data Science program at the University of San Francisco, specializing in deep learning and computer vision. Her research focuses on AI-driven solutions for infrastructure monitoring and public safety, including automated inspection of underground systems like culverts, sewers, and DC motors. She has collaborated with the U.S. Army Corps of Engineers on floodwater control structure projects.

• Education: PhD (in progress) in Engineering and Applied Science at University of New Orleans (2025), MS in Information Technology from Middle Technical University (2017).

Research interests include semantic segmentation, transformer-based NLP models, dataset curation, and AI applications in urban planning. She has held roles as a Research Assistant at Gulf States Center for Environmental Informatics and Teaching Assistant at University of New Orleans.

Publications emphasize advanced neural network architectures like DAU-Net and SHARP-Net for infrastructure defect detection, imbalance-aware segmentation techniques, and sinkhole identification using multiscale filters.