Education and Experience：

2025—present School of Life Sciences, Tsinghua University, China/ Assistant Professor

2025— present Center for Life Sciences & IDG/McGovern Institute for Brain Research, Tsinghua University / Principle Investigator

2022—2024 Tsinghua University, Postdoc Fellow

2018—2020 Rockefeller University, Visiting Scholar

2016—2022 Department of Automation, Tsinghua University, Ph. D

2012—2016 School of Aerospace, Tsinghua University, B.S.

2013—2016 Department of Mathematical Sciences, B.S.

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

1、 Yuanlong Zhang*, Mingrui Wang*, Qiyu Zhu*, Yuduo Guo, Bo Liu, Jiamin Li, Xiao Yao, Chui Kong, Yi Zhang, Yuchao Huang, Hai Qi, Jiamin Wu‡, Zengcai V. Guo‡, & Qionghai Dai‡. “Long-term mesoscale imaging of 3D intercellular dynamics across a mammalian organ”, Cell (2024).

2、 Yuanlong Zhang*, Lekang Yuan*, Qiyu Zhu*, Jiamin Wu,Tobias Nöbauer, Rujin Zhang, Guihua Xiao, Mingrui Wang, Hao Xie, Zengcai Guo, Qionghai Dai‡, and Alipasha Vaziri‡. “A miniaturized mesoscope for the large-scale single-neuron-resolved imaging of neuronal activity in freely behaving mice”, Nature Biomedical Engineering (2024)

3、 Guoxun Zhang*, Xiaopeng Li*, Yuanlong Zhang*, Xiaofei Han, Xinyang Li, Jinqiang Yu, Boqi Liu, Jiamin Wu‡, Li Yu‡, and Qionghai Dai‡. “Bio-friendly long-term subcellular dynamic recording by self-supervised image enhancement microscopy”, Nature Methods (2023)

4、 Xinyang Li*, Yuanlong Zhang*, Jiamin Wu*‡, and Qionghai Dai*‡. “Challenges and opportunities in bioimage analysis”. Nature Methods (2023)

5、 Yuanlong Zhang*, Guoxun Zhang*, Xiaofei Han, Jiamin Wu, Ziwei Li, Xinyang Li, Guihua Xiao, Hao Xie, Lu Fang‡, and Qionghai Dai‡. “Rapid detection of neurons in widefield calcium imaging datasets after training with synthetic data”, Nature Methods (2023)

Research Focus：

Many brain functions emerge from the intricate interplay of highly distributed local functional networks. However, the lack of tools capable of capturing whole-brain network activity with high spatiotemporal resolution has long hindered our understanding of these large-scale functional networks.

To address this challenge, we have pioneered a series of advanced optical and computational methodologies, continuously enhancing the spatiotemporal throughput, accuracy, and imaging depth limits of large-scale in vivo neural recordings while deepening our understanding of computational models of neural circuits. Leveraging these technologies, we are committed to exploring the following key questions:

• Information Theory and Computation: How is sensory information encoded, transformed, and represented across different processing hierarchies in the mammalian brain?

• Systems Neuroscience: How do neural representations interact with internal states—such as motivation, attention, and memory—to drive specific behavioral outputs?

• Brain-Inspired Intelligence: How can insights into brain function be harnessed to optimize the development of artificial neural networks?

Honors & Awards：

2025 Significant Scientific and Technological Results of the 2025 Zhongguancun Forum

2025 National Young Talent Award Program

2024 Outstanding Postdoctoral Fellowship (top 10/3500)

2024 Tsinghua's Top 10 Achievements (Faculty & Student Picks)

2024 Top 10 Science and Technology Advances in China and the World for 2024, Selected by CAS and CAE Academicians