Xiang Zhang

Xiang Zhang is an Associate Professor at the College of Information Sciences and Technology, The Pennsylvania State University, focusing on big data, data mining, machine learning, and biomedical informatics. His work develops algorithms for analyzing large-scale social, biological, and medical datasets using graph-based methods.

Education:

• Ph.D. in Computer Science (2011), University of North Carolina at Chapel Hill

Research Interests: Xiang Zhang's research spans graph neural networks, dynamic graph analysis, and biomedical data mining. He specializes in explainable AI, robust learning, and topology-aware models for imbalanced data. His group investigates security in graph models, synthetic data generation, and cross-domain adaptation.

Publications Trends: Recent work emphasizes explainable dynamic graph neural networks, adversarial attacks on LLMs, and robust contrastive learning. His team explores topology-level imbalances, prompt attacks, and causal relation modeling in temporal systems.

Scientific Awards:

• Best Research Paper Award at SIGKDD 2008
• Best Student Paper Award at ICDE 2008
• Best Paper Candidate at ICDM 2018 and ICDM 2012
• SIGKDD Dissertation Award Honorable Mention (2012)

Advising: He mentors a group of Ph.D. students including Zongyu Wu, Minghua Lin, and Junjie Xu, with alumni securing faculty positions at Florida International University and North Carolina State University.