Dr. Ran Xu is an applied statistician and Assistant Professor in the Department of Allied Health Sciences. His methodological research interests include (1) general quantitative methods such as causal inference methods, econometrics, and applied machine learning; (2) systems science approaches such as social network analysis, agent-based ...

Articulated Motion and Deformable Objects: 7th International Conference …

‪Research Fellow, Dana Farber Cancer Institute, Harvard Medical School‬ - ‪‪Cited by 186‬‬ - ‪Cancer biology‬ - ‪DNA Damage Response‬

‪Assistant Professor, Department of Allied Health Sciences, University of Connecticut‬ - ‪‪Cited by 1,251‬‬ - ‪Quantitative Methods‬ - ‪Systems Science‬ - ‪Disease Prevention‬ - ‪Public Health Nutrition‬

I am a Senior Deep Learning Software Enginner at NVIDIA. Before joining in NVIDIA, I received my Ph.D. degree from Purdue University in 2021, advised by professor Saurabh Bagchi. My research interests lied in the joint discipline of Computer Vision and Systems, and particularly the approximation for streaming video analytics on mobile devices.

2024年2月2日 · Ran Xu (Ryan) received his Ph.D. from the Department of Statistics and Actuarial Science at University of Hong Kong. Afterward, He worked in the Department of MathematicsStatistics at Concordia...

“Weakly-supervised Scientific Document Classification via Retrieval-Augmented Multi-stage Training.” In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2023. Ran Xu, Yue Yu, Hejie Cui, Xuan Kan, Yanqiao Zhu, Joyce C Ho, Chao Zhang, and Carl Yang.

My research focuses on applied data science and systems science, with applications in substantive areas such as health behavior and disease prevention. Specifically, my research has two streams:...

Ran Xu is currently an assistant professor in the department of allied health sciences at the University of Connecticut. His research interests include general quantitative...

‪Emory University‬ - ‪‪Cited by 336‬‬ - ‪Graph Mining‬ - ‪Natural Language Processing‬ - ‪Large Language Models‬