Daniel Hajialigol is a master’s degree student in the Department of Computer Science.  His advisor is Xuan Wang. His primary research focus is at the intersection of fine-grained entity typing and weak supervision.  

Feiyang Kang is a Ph.D. student in the Bradley Department of Electrical and Computer Engineering. He is advised by Ruoxi Jia. His research interests lie in trustworthy machine learning and data valuation. His current projects involve the detection and monitoring of distributional drifts and the use of optimal transport.

Wyatt Sweat is a Ph.D. student in the Department of Computer Science.  He is advised by Danfeng (Daphne) Yao. Sweat’s research is focused on improving the detection and the explainability of cybersecurity threats.    

Haohui Wang is a Ph.D. student in the Department of Computer Science.  She is advised by Dawei Zhou. Wang’s research interest is in machine learning on graphs and she is currently working on long-tail category characterization.    

Dawei Zhou is an assistant professor in the Virginia Tech Department of Computer Science; director of the VirginiaTech Learning on Graphs (VLOG) Lab; and core faculty at the Sanghani Center. Zhou’s prior research is on rare category detection, graph mining, curriculum learning, and algorithmic fairness, with applications in financial fraud detection, cyber security, financial forecasting, […]

Bilgehan Sel is a Ph.D. student in the Department of Electrical and Computer Engineering. His advisor is Ming Jin. His research focus lies in reinforcement learning and mathematical optimization from the perspective of multi-objective optimization.

Xuan Wang joined the Virginia Tech Department of Computer Science as an assistant professor in Spring 2023 and is core faculty at the Sanghani Center. Wang’s primary research interests are in the fields of natural language processing and data mining. She is specifically interested in developing principled data-driven approaches with light human effort for effective […]

Lanxiao Huang is a Ph.D. student in the Bradley Department of Electrical and Computer Engineering.  His advisor is Ming Jin. His research interests lie broadly in machine learning with a recent focus on reinforcement learning, multi-objective optimization, and reinforcement learning in application of cybersecurity.  

Zain ul Abdeen is a Ph.D. student in the Bradley Department of Electrical and Computer Engineering.  He is advised by Ming Jin. His research interests are generally focused on machine learning, specifically in the domain of kernel methods, deep learning, and cyber security in power systems.

Alexander Kedrowitsch is a Ph.D. student in the Department of Computer Science.  His advisor is Danfeng (Daphne) Yao. His research lies in investigating security topics related to the efficient detection of advanced persistent threats on computer systems.