Shiyu is currently a PhD candidate in Biostatistics at the Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University. He is honored to be advised by Dr. Zhaohui (Steve) Qin and Dr. Liang Zhao, working on machine learning and its applications on complex structured data. In particular, he approaches his research in three aspects: (1) develop deep generative models for controllable data generation, (2) develop efficient and scalable deep graph models and (3) conduct statistical modeling on biomedical data. Shiyu was a Livingston Fellow at the Rollins School of Public Health, Emory University. He won the NeurIPS 2022 Scholar Award and has been serving as the independent reviewer and PC member for many top-tier conferences including NeurIPS, ICML, AISTATS, KDD and AAAI.
Prior to Emory, Shiyu earned his M.S. in Biostatistics from Yale University in 2019, B.S. in Pharmaceutical Sciences from Fudan University in 2017. Through intensive coursework and research projects at Yale and Emory University, he has gained solid foundation in both theory and applications of statistics and computer science.
Links: homepage, Google Scholar and LinkedIn.
Areas of Interest
- Bayesian Analysis
- Data Mining
- Machine Learning
- Network Science
- Statistical Modeling
Education
- B.S. 2017, Fudan University
- M.S. 2019, Yale University
Affiliations & Activities
Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University
Advisor: Zhaohui (Steve) Qin, Liang Zhao
Dissertation title: Graph Machine Learning and Its Applications to Genomic Data
Publications
- Hejie Cui, Jiaying Lu, Shiyu Wang, Ran Xu, Wenjing Ma, Shaojun Yu, Yue Yu, Xuan Kan, Chen Ling, Joyce Ho, Fei Wang, Carl Yang, 2023, A Survey on Knowledge Graphs for Healthcare: Resources, Applications, and Promises, arXiv e-prints, arXiv:2306.04802, ,
- Shiyu Wang*, Yuanqi Du*, et al., 2022, Controllable Data Generation by Deep Learning: A Review, arXiv preprint arXiv:2207.09542, ,
- Shiyu Wang, Xiaojie Guo, Liang Zhao, 2022, Deep Generative Model for Periodic Graphs, Conference on Neural Information Processing Systems (NeurIPS 2022), ,
- Xiaojie Guo*, Shiyu Wang*, Liang Zhao, 2022, Graph Neural Networks: Graph Transformation, Graph Neural Networks: Foundations, Frontiers, and Applications, ,
- Shiyu Wang, Xiaojie Guo, et al., 2022, Multi-objective Deep Data Generation with Correlated Property Control, Conference on Neural Information Processing Systems (NeurIPS 2022), ,
- Yuanqi Du*, Shiyu Wang*, et al., 2021, GraphGT: Machine Learning Datasets for Graph Generation and Transformation, Conference on Neural Information Processing Systems (NeurIPS 2021) Datasets and Benchmarks Track, ,
- Xingchao He*, Shiyu Wang*, et al., 2018, Genotypic and Environmental Effects on the Volatile Chemotype of Valeriana jatamansi Jones, Frontiers in plant science, ,