Zhichao Han
Ph.D. Student
supervised by Prof. David S. Kammer (ETHz) and Prof. Olga Fink (EPFL)
Dept. of Civil, Environmental and Geomatic Engineering
ETH Zürich, Switerland
Zhichao HanPh.D. Student
supervised by Prof. David S. Kammer (ETHz) and Prof. Olga Fink (EPFL)
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My research interests lie in the intersection between Machine Learning and Computational Science & Engineering.
Particularly, I am interested in the graph-represented systems where entities interact with each other and properties emerge at macroscopic scales.
My PhD research focuses on Machine Learning + Computational Mechanics. I develop machine learning models to 1) learn homogeneous or heterogeneous interactions between discrete particles, and 2) learn constitutive relations at continuum level, without accessing the ground-truth inter-particle force / stress labels.
| Collective Relational Inference for learning heterogeneous interactions Zhichao Han, Olga Fink, David S. Kammer Nature Communications, 2024. |
| Learning physics-consistent particle interactions Zhichao Han, David S. Kammer, Olga Fink PNAS Nexus, 2022. |
| Adversarial attack on community detection by hiding individuals Jia Li, Honglei Zhang, Zhichao Han, Yu Rong, Hong Cheng, Junzhou Huang Proceedings of The Web Conference (WWW), 2020. |
| Predicting path failure in time-evolving graphs Jia Li, Zhichao Han, Hong Cheng, Jiao Su, Pengyun Wang, Jianfeng Zhang, Lujia Pan Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (SIGKDD), 2019. |
| Deeper insights into graph convolutional networks for semi-supervised learning Qimai Li, Zhichao Han, Xiao-Ming Wu Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence (AAAI), 2018. |
| Community detection based on distance dynamics Junming Shao, Zhichao Han, Qinli Yang, Tao Zhou Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD), 2015. |