Xiaofei Zhang

Xiaofei Zhang is an Associate Professor in the Department of Computer Science at the University of Memphis. His research focuses on developing efficient algorithms and toolkits for scalable data management, including graph databases and distributed computing systems. Dr. Zhang holds a PhD in Computer Science and Engineering from The Hong Kong University of Science and Technology (2013). Before joining the University of Memphis, he was a postdoctoral research fellow at the University of Waterloo's Cheriton School of Computer Science, and held postdoctoral positions at the Chinese University of Hong Kong and HKUST in 2014 and 2015.

His research interests span novel storage models, query optimization (both exact and approximate), and distributed/parallel computing theory. Key areas include graph data management, query acceleration, and scalable systems for large-scale datasets. He has contributed to tools like Hu-fu for secure spatial queries and frameworks for graph sparsification using deep reinforcement learning.

Recent work emphasizes machine learning integration in data management, such as reinforcement learning strategies for order fulfillment and quality-diversity optimization techniques. Dr. Zhang's publications address challenges in distributed systems, probabilistic data processing, and efficient query execution over large graphs.

No scientific awards have been explicitly listed. His advising and grant activities are not detailed in the provided text, though his research indicates active involvement in collaborative projects. His work contributes to both theoretical advancements and practical systems for modern data management challenges.