Welcome to Neurolabware
About Our Lab
The Yuanlong Zhang Lab at Tsinghua University develops quantitative technology and computational frameworks to observe brain activity and explain how it gives rise to behavior and cognition. We work at the intersection of systems neuroscience, neuroengineering, and machine learning, with an emphasis on rigorous measurement, reproducible analysis, and interpretable models.
Our long-term goal is to make neural activity measurable at scale, make behavior describable in structured language, and connect brain computation with AI in ways that generate testable scientific hypotheses.
Research Focus
Our research centers on three connected directions:
- Pan-scale brain observation: We develop experimental and computational methods for scalable observation of large neuronal populations, aiming to expand both spatial coverage and analytical throughput in behaving animals.
- Language-describable behavior understanding: We build pipelines that map rich behavioral data to structured, language-compatible representations, enabling comparison across individuals, tasks, and experiments.
- NeuroAI: We develop tools to align brain data and artificial agents (and their internal representations), using each as a model system to better understand the other.
Across these projects, we integrate method development, data engineering, statistical inference, and machine learning to move from raw measurements to mechanistic, testable models.
Recent News
Recent Publications
- 2026 — The Optically Guided and Pre-assembled Implantation Cranial Window Reveals Cortical Spatial Representations during Navigation, Research
- 2026 — LensCopilot is all you need: leveraging a knowledge-grounded LLM for automated high-performance lens design, Fifth International Computational Imaging Conference (CITA 2025)
- 2025 — Slimming the Fat-Tail: Morphing-Flow for Adaptive Time Series Modeling, Proceedings of the 42nd International Conference on Machine Learning
- 2025 — Suction Leap-Hand: Suction Cups on a Multi-fingered Hand Enable Embodied Dexterity and In-Hand Teleoperation, IEEE International Conference on Robotics and Automation
- 2025 — Adaptive visible light integrated sensing and communication for cable-free virtual reality, Photonics Research
- 2025 — Prior-guided Hierarchical Harmonization Network for Efficient Image Dehazing, Proceedings of the AAAI Conference on Artificial Intelligence
- 2024 — Semi-supervised noise-resilient anomaly detection with feature autoencoder, Knowledge-Based Systems
- 2024 — Mesoscale neuronal granular trial variability in vivo illustrated by nonlinear recurrent network in silico, Nature Communications
- 2024 — Long-term mesoscale imaging of 3D intercellular dynamics across a mammalian organ, Cell
- 2024 — A miniaturized mesoscope for the large-scale single-neuron-resolved imaging of neuronal activity in freely behaving mice, Nature Biomedical Engineering
Lab Environment
We provide:
- Collaborative research: Shared projects, open discussion, and a culture of constructive feedback.
- Modern infrastructure: Access to advanced experimental facilities and computational resources.
- Mentorship and training: Regular mentoring, technical onboarding, and opportunities to lead projects and publish.
- Collaborations: Active partnerships across Tsinghua and with external research groups.
- Sustainable pace: Clear expectations and support for long-term, high-quality research.
Location
We are located in the Biomedicine Hall at Tsinghua University (Beijing, China). Our lab is part of the School of Life Sciences and is affiliated with the IDG/McGovern Institute for Brain Research at Tsinghua University.
Quick Links
- Research Projects — Current directions and ongoing work
- Team Members — Meet the lab
- Publications — Papers and preprints
- Join Us — Open positions and how to apply
- Contact — Get in touch
- Network — Limit research group at Tsinghua
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