معرفی
Xulong Tang is an Assistant Professor in the Department of Computer Science at the University of Pittsburgh. He holds a PhD in Computer Science from Penn State (2019), an MS from the University of Science and Technology of China (2013), and a BS from Harbin Institute of Technology (2010). His research focuses on high-performance computing, parallel architectures, and compiler optimization for heterogeneous systems.
Research interests include GPU optimization, compiler-assisted parallel computing, quantum computing systems, and efficient machine learning frameworks. He advises multiple PhD students and has published extensively in top conferences like ASPLOS, ISCA, and MICRO. His work addresses challenges in multi-GPU systems, quantum circuit simulation, and adversarial machine learning.
Tang has collaborated on projects involving quantum computing optimization, photonic quantum systems, and edge device acceleration. Notable contributions include frameworks for efficient training of temporal graph neural networks and compiler-driven hardware-software co-design. He serves as a program committee member for ASPLOS and IEEE Micro Top Picks.
