Yulai Xie

Yulai Xie is an Associate Professor at Huazhong University of Science and Technology (HUST), specializing in data storage, provenance systems, and cloud security. His research focuses on intrusion detection, container monitoring, and efficient big data storage architectures, with extensive collaborations with researchers such as Dan Feng and Darrell D. E. Long.

His research interests include data provenance, real-time intrusion detection, Docker container security, and hybrid modeling for resource prediction. These areas are evident in his work on systems like Pagoda and P-Gaussian, which leverage provenance graphs and statistical models for enhanced security and performance in cloud and big data environments.

The trend in his recent publications shows a consistent focus on secure, scalable, and real-time data systems. He combines machine learning (e.g., Isolation Forest), time series forecasting (ARIMA), and data compression techniques to improve the efficiency and responsiveness of storage and monitoring infrastructures in modern computing environments.

• Provenance-based intrusion detection
• Container and cloud security
• Efficient data storage and retrieval
• Real-time anomaly prediction
• Hybrid modeling for system performance

Yulai Xie has collaborated extensively with leading researchers and institutions, including the Storage Systems Research Center (SSRC) at UC Santa Cruz. His work has been supported by academic collaborations and institutional resources, though specific grants are not mentioned. He has advised or co-supervised several researchers, including Minpeng Jin, Yafeng Wu, and Zhuping Zou, as seen in co-authored publications.

He has been affiliated with the Storage Systems Research Center (SSRC) at UC Santa Cruz as a visiting scholar and has contributed to the Wuhan National Laboratory for Optoelectronics as a postdoctoral researcher. These labs focus on scalable storage, archival systems, and secure data management, aligning closely with his research themes.