The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Xinlei Chen sits on this spectrum.
This scientist: 61 publications — 1st percentile
1% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 991 publications or more.
The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Xinlei Chen sits on this spectrum.
This scientist: 45 D-Index — 51st percentile
51% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 131 D-Index or more.
Xinglei Chen is affiliated with Facebook in the United States and has an extensive background in computer science research. Their work spans multiple subfields, including computer vision and pattern recognition, artificial intelligence, electrical and electronic engineering, computer networks and communications, and cognitive neuroscience.
The scientist's research topics cover a diverse range, focusing on areas such as domain adaptation and few-shot learning, multimodal machine learning applications, advanced neural network applications, air quality monitoring and forecasting, EEG and brain-computer interfaces, quantum computing algorithms and architecture, and quantum information and cryptography.
Their publication record includes important papers that contribute to the field of computer vision and machine learning. Notable recent works include:
Xinglei Chen collaborates frequently with several researchers in the field. Co-authors include Ying Sun, Fan Dang, Dezhi Zheng, Yunhao Liu, and Saining Xie. These collaborators have contributed to a significant portion of their joint research output.
The scientist has published extensively in several venues, highlighting their active engagement with various academic communities. Frequent publication venues include:
Xinglei Chen's work focuses primarily on advancing computational models and applications in computer science, particularly in machine learning and vision. Their interdisciplinary research incorporates aspects from engineering and neuroscience, aiming to address complex problems through novel methodologies.
Xinlei Chen;Kaiming He
Xinlei Chen;Haoqi Fan;Ross B. Girshick;Kaiming He
Xinlei Chen;Hao Fang;Tsung-Yi Lin;Ramakrishna Vedantam
Xinlei Chen;Saining Xie;Kaiming He
Unknown
T. Mitchell;W. Cohen;E. Hruschka;P. Talukdar
T. Mitchell;W. Cohen;E. Hruschka;P. Talukdar
Jiwei Li;Xinlei Chen;Eduard H. Hovy;Dan Jurafsky
Xinlei Chen;C. Lawrence Zitnick
Xinlei Chen;Abhinav Shrivastava;Abhinav Gupta
Xinlei Chen;Deng Cai
Amanpreet Singh;Vivek Natarajan;Meet Shah;Yu Jiang
Xinlei Chen;Abhinav Gupta
Xinlei Chen;Ross Girshick;Kaiming He;Piotr Dollar
Huaizu Jiang;Ishan Misra;Marcus Rohrbach;Erik Learned-Miller
Deng Cai;Xinlei Chen
Charles R. Qi;Xinlei Chen;Or Litany;Leonidas J. Guibas
Xinlei Chen;C. Lawrence Zitnick
Harsh Agrawal;Peter Anderson;Karan Desai;Yufei Wang
Harsh Agrawal;Karan Desai;Yufei Wang;Xinlei Chen
Xinlei Chen;Li-Jia Li;Li Fei-Fei;Abhinav Gupta
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