Faculty
Dr. Quanying Liu, joined Southern University of Science and Technology (SUSTech) in September 2019, as an Associate Professor of the Department of Biomedical Engineering, Doctoral Supervisor, PI of Neural Computing and Control Laboratory (NCC lab). Before joining SUSTech, Quanying obtained her PhD degree from ETH Zurich and received postdoctoral training at Caltech.
Quanying's research focuses on interactions among neuroscience, AI and control theory, including multi-modal neural signal processing (EEG, sEEG, fMRI, DTI), AI for neuroscience (explainable AI to interpret the structure and function of the brain), optimization for neuromodulation (tES, TMS, electrical stimulation).
Dr. Quanying Liu has published over 80 research articles in top journals/conferences such as Nature Methods, The Innovation, PNAS, Neuroimage, and ICML, NeurIPS, ICLR. Her work has been cited more than 2800 times, with an H factor of 27. She is the associate editor of IEEE Journal of Translational Engineering in Health and Medicine (JTEHM).
For anyone who is interested in joining NCC lab, please feel free to email me.
Education
2013-2017 PhD in Biomedical Engineering, ETH Zurich, Switzerland (Doctoral thesis: “Brain Network Imaging based on High-density Electroencephalography”. Supervisors: Dr. Nicole Wenderoth and Dr. Dante Mantini)
2010-2013 Master in Computer Science, Lanzhou University, China
2006-2010 Undergraduate in Electrical Engineering, Lanzhou University, China
Academic Positions
2025-present Associate Professor in Department of Biomedical Engineering, Southern University of Science and Technology (PI of Neural Computing & Control lab)
2019-2025 Assistant Professor in Department of Biomedical Engineering, Southern University of Science and Technology (PI of Neural Computing & Control lab)
2017-2019 Postdoctoral Scholar in Department of Computing and Mathematical Sciences (CMS), California Institute of Technology (Principal Investigator: Dr. John Doyle)
2017-2019 Independent researcher in Neurosciences, Huntington Medical Research Institute, US
2016-2017 Visiting Scholar in Research Center for Motor Control and Neuroplasticity, KU Leuven, Belgium
2016.10 Late-Summer School on Non-Invasive Brain Stimulation, University Medical Center Freiburg, Germany
2014-2015 Visiting Scholar in Department of Experimental Psychology, University of Oxford, UK
Awards and Scholarships
The New Brain 30 (2023)
AAIC travel award (2019)
Estes Stars Award (2018)
Representative Work of NCC lab:
(Full list see Google Scholar: https://scholar.google.com/citations?user=UpP9hJ8AAAAJ&hl=en)
1.Luo, Z., et. al., Liu, Q.* (2025). Mapping effective connectivity by virtually perturbing a surrogate brain, Nature Methods
2.Qu, Y., et. al., Liu, Q.* (2024). Promoting interactions between cognitive science and large language models. The Innovation
3.Wang, M., et. al., Liu, Q.* & Wei, P.* (2025). Transcranial temporal interference stimulation precisely targets deep brain regions to regulate eye movements. Neuroscience Bulletin
4.Wang, M., et. al., Liu, Q.* (2023). Multi-objective optimization via evolutionary algorithm (MOVEA) for high-definition transcranial electrical stimulation of the human brain. NeuroImage
5.Mou, X., et. al., Liu, Q.* & Wu, H.* (2024). ChineseEEG: A Chinese linguistic corpora EEG dataset for semantic alignment and neural decoding. Scientific Data
6.Zhang, H., et. al., Liu, Q.* (2021). EEGdenoiseNET: A benchmark dataset for deep learning solutions of eeg denoising. Journal of Neural Engineering (1%高被引)
7.Wei, C., et. al., Liu, Q.* (2025). Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering and Manipulating Human Perceptual Variability. ICML
8.Zhang, M., Qian, F., Liu, Q.* (2025). Learning Task Belief Similarity with Latent Dynamics for Meta-Reinforcement Learning. ICLR
9.Li, D., et. al., Liu, Q.* (2024). Visual decoding and reconstruction via eeg embeddings with guided diffusion. NeurIPS
10.Li, D., et. al., Liu, Q.* (2025). BrainFLORA: Uncovering Brain Concept Representation via Multimodal Neural Embeddings. ACM MM (oral)