Virginia Tech’s 2022 Fall Commencement ceremony takes place today.
“We wish our graduates at the Sanghani Center all the best as they receive their Ph.D. and master’s degrees and take the next step toward achieving their career goals,” said Naren Ramakrishnan, the Thomas L. Phillips Professor of Engineering in the Department of Computer Science at Virginia Tech and director of the Sanghani Center for Artificial Intelligence and Data Analytics.
Following are the Sanghani Center’s 2022 summer and fall graduates:
Nikhil Muralidhar, advised by Naren Ramakrishnan and Anuj Karpatne, has earned a Ph.D. in computer science. His research interest is in leveraging machine learning to address problems in scientific applications leveraging data and scientific theory. He also received a graduate certificate in Urban Computing. The title of his dissertation is “Science Guided Machine Learning: Incorporating Scientific Domain Knowledge for Learning Under Data Paucity and Noisy Contexts.” In Fall 2022, Muralidhar joined the Computer Science Department at Stevens Institute of Technology in Hoboken, New Jersey, as an assistant professor and leads the Scientific Artificial Intelligence (ScAI) Lab to develop scientific machine learning solutions incorporating data and domain knowledge in physics, fluid dynamics, cyber-physical systems and disease modeling.
Xinyue Wang, advised by Edward Fox, has earned a Ph.D. in computer science. His research focuses on web archive processing and analysis infrastructure through distributed computation. The title of his dissertation is “Large Web Archive Collection Infrastructure and Services.” Wang is joining Yahoo in San Jose, California, as a research scientist.
Huiman Han, advised by Chris North, has earned a master’s degree in computer science. Her research focuses on visual analytics, interactive machine learning, and explainable artificial intelligence. The title of her thesis is “Explainable Interactive Projections for Image Data.” Huimin is joining LinkedIn in Mountain View, California, as a software engineer in Machine Learning.
Sarah Maxseiner, advised by Lynn Abbott, received a master’s degree in electrical and computer engineering. Her thesis is on assessing the quality level of hand-drawn sketches.