张超（zhangchao5@genomics.cn），硕士研究生，于2021年加入华大，现任华大生命科学研究院算法开发高级工程师。长期从事生物医学大数据挖掘，"医学+AI"算法的开发与研究，主要致力于细胞注释、批次效应去除，宏基因组与疾病关联等相关领域算法的研发工作，并在此领域积累了丰富的项目经验，以第一作者或共同通讯发表多篇相关学术论文。
研究方向：
1.宏基因组数据挖掘
2.NLP
现任岗位：华大研究院 智能所 算法开发高级工程师
教育背景：电子与通信工程 硕士
参与项目：
1.时空转录组数据批次效应去除（GigaScience, 2024; GigaByte, 2024）
2.细胞注释 （Nature communications， 2022）
3.宏基因组语言模型与疾病关联
论文：
1.Zhang C., Kang Q., Li M., et al. (2024).BatchEval Pipeline: batch effect evaluation workflow for multiple datasets joint analysis. GigaByte. https://doi.org/10.46471/gigabyte.108.
2.Zhang C., Liu L., Zhang Y., et al. (2024). spatiAlign: an unsupervised contrastive learning model for data integration of spatially resolved transcriptomics. GigaScience, 13, giae042. https://doi.org/10.1093/gigascience/giae042.
3.Meng, L., Jiang, M., Zhang, C., et al. (2023). Deep learning segmentation, classification, and risk prediction of complex vascular lesions on intravascular ultrasound images. Biomedical Signal Processing and Control, 82, 104584.
4.Qu, X., Zhang, C., Houser, S. H., et al. (2022). Prediction model for early childhood caries risk based on behavioral determinants using a machine learning algorithm. Computer Methods and Programs in Biomedicine, 227, 107221.
5.Shen, R., Liu, L., Wu, Z., Zhang, Y., Yuan, Z., Guo, J., ... & Yao, J. (2022). Spatial-ID: a cell typing method for spatially resolved transcriptomics via transfer learning and spatial embedding. Nature communications, 13(1), 7640.
