Research direction：

Artificial intelligence, Computational imaging, Neuroscience

Education and Experience：

07/2025 – Present, Assistant Professor, College of AI, Tsinghua University

07/2023 – 06/2025, Postdoctoral Research Fellow, Department of Automation, Tsinghua University

09/2018 – 07/2023, Ph.D, Department of Automation, Tsinghua University

09/2014 – 07/2018, B.Eng, Department of Automation, Xi’an Jiaotong University

Representative Publications in past 5 years (# co-first author, *corresponding author)：

1、 Xinyang Li#, Yixin Li#, Yiliang Zhou, Jiamin Wu, Zhifeng Zhao, Jiaqi Fan, Fei Deng, Zhaofa Wu, Guihua Xiao, Jing He, Yuanlong Zhang, Guoxun Zhang, Xiaowan Hu, Xingye Chen, Yi Zhang, Hui Qiao, Hao Xie, Yulong Li, Haoqian Wang*, Lu Fang*, Qionghai Dai*. "Real-time denoising enables high-sensitivity fluorescence time-lapse imaging beyond the shot-noise limit." Nature Biotechnology (2023): 282-292.

2、 Xinyang Li#, Guoxun Zhang#, Jiamin Wu, Yuanlong Zhang, Zhifeng Zhao, Xing Lin, Hui Qiao, Hao Xie, Haoqian Wang*, Lu Fang*, and Qionghai Dai*. "Reinforcing neuron extraction and spike inference in calcium imaging using deep self-supervised denoising." Nature Methods (2021): 1395-1400.

3、 Xinyang Li#, Yuanlong Zhang#, Jiamin Wu*, Qionghai Dai*. "Challenges and opportunities in bioimage analysis." Nature Methods (2023): 958-961.

4、 Xinyang Li#, Xiaowan Hu#, Xingye Chen#, Jiaqi Fan, Zhifeng Zhao, Jiamin Wu*, Haoqian Wang*, Qionghai Dai*. "Spatial redundancy transformer for self-supervised fluorescence image denoising." Nature Computational Science (2023): 1067-1080.

5、 Xinyang Li#, Guoxun Zhang#, Hui Qiao#, Feng Bao, Yue Deng, Jiamin Wu, Yangfan He, Jingping Yun, Xing Lin, Hao Xie, Haoqian Wang*, Qionghai Dai*. (2021). Unsupervised content-preserving transformation for optical microscopy. Light: Science & Applications, (2021): 44-54.

Research Focus：

As the extension of human vision, imaging instruments have extended our observational capability to unprecedented scales and precision, leading to a series of scientific discoveries. To solve the fundamental challenges at the frontiers of optical imaging, my research focuses on the intersection of AI, optical imaging and neuroscience, aiming to empower scientific observation through AI and to advance scientific discovery. My work has been published in high-impact international journals, including Nature Methods, Nature Biotechnology, Nature Computational Science, and Light: Science & Applications. I have been invited to deliver talks at conferences such as the World Artificial Intelligence Conference 2025, International Conference on Artificial Intelligence 2023, and the Frontiers of Optical Engineering and Interdisciplinary Science Conference 2025. I currently serve as a Young Editorial Board Member of PhotoniX (Impact Factor = 19.1), and have received multiple honors and awards, including the PhotoniX Prize, the THU/McGovern Award for Outstanding Research Achievement, Tsinghua Shuimu Scholar, and the Tsinghua Outstanding Doctoral Dissertation Award. My current research directions include:

• Intelligent Imaging: Developing high-performance, interpretable, and self-supervised computational microscopy methods that integrate AI with optical imaging. These approaches aim to significantly enhance imaging performance and drive advances in life and biomedical sciences.

• Neuroimaging Robotics : Pioneering a novel neuroimaging robot architecture and exploring non-contact neural imaging technologies in freely behaving animals. This work seeks to reveal neural circuit mechanisms underlying complex behaviors and to provide technical foundations for brain science and AI.

• Quantum Imaging Theory and Methods: Building high-power entangled photon sources and exploring new paradigms that combine quantum effects with optical imaging. Designing and constructing quantum imaging systems to fundamentally surpass the photon shot noise and diffraction limits of classical imaging.

Honors & Awards：

2025 PhotoniX Prize

2023 Tsinghua Shuimu Scholar

2023 Beijing Outstanding Graduates

2023 Tsinghua Outstanding Doctoral Dissertation

2021 THU/McGovern Award for Outstanding Research Achievement