个人简介
张昕亚博士于2019年和2024年分别获得同济大学物理学学士和博士学位，博士期间在英国伦敦大学学院（University College London）进行为期一年的访问研究，2025年1月加入西湖大学交叉科学中心开展博士后研究。她的研究范围包括复杂系统、人工智能和计算神经科学，以第一作者身份在物理学顶尖期刊Physical Review Letters、Communications Physics、Physical Review Research等发表论文，并在NeurIPS（Spotlight）、AAAI（Oral）等人工智能领域顶级国际会议上发表合作论文。她的研究成果获得学界高度认可，入选PRL年度精选“PRL Collection of the Year 2024”（由国内单位完成的9篇入选论文之一）。目前，她的研究重点是物理学与人工智能交叉领域的前沿探索。
代表论文 (*通讯作者）
1. X.-Y. Zhang*, Y. Yao, Z. Han, G. Yan. Delayed threshold and spatial diffusion in k-core percolation induced by long-range connectivity. Communications Physics, 2025, 8(1): 1.
2. X.-Y. Zhang, J. M. Moore, X. Ru, G. Yan. Geometric scaling law in real neuronal networks. Physical Review Letters, 2024, 133 (13): 138401.(Editors' Suggestion & Featured in Physics)
3. X.-Y. Zhang, H. Lin, Z. Deng, M. Siegel, E. K. Miller, G. Yan. Decoding region-level visual functions from invasive EEG data. bioRxiv, 2024.04. 02.587853
4. Z. Liu, X. Ru, J. M. Moore, X.-Y. Zhang, G. Yan. Mixup in latent geometry for graph classification. IEEE Transactions on Network Science and Engineering, 2024.
5. X.-Y. Zhang, S. Bobadilla-Suarez, X. Luo, M. Lemonari, S. L. Brincat, M. Siegel, E. K. Miller, B. C. Love. Adaptive stretching of representations across brain regions and deep learning model layers. bioRxiv, 2023.12. 01.569615
6. X. Ru, X.-Y. Zhang, Z. Liu, J. M. Moore, G. Yan. Attentive transfer entropy to exploit transient emergence of coupling effect. Advances in Neural Information Processing Systems (NeurIPS 2023).
7. X. Ru, J. M. Moore, X.-Y. Zhang, Y. Zeng, G. Yan. Inferring patient zero on temporal networks via graph neural networks. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI 2023), 37 (8): 9632.
8. X.-Y. Zhang, J. Sun, G. Yan. Why temporal networks are more controllable: Link weight variation offers superiority. Physical Review Research, 2021, 3 (3): L032045.
