焦一平，博士，现为南京信息工程大学人工智能学院讲师，智慧医疗研究院成员。硕博毕业于东南大学自动化学院，期间获国家留学基金委资助，赴荷兰拉德堡德大学医学中心计算病理组联合培养一年。主要研究方向为计算病理学、机器学习，具有丰富的组织病理全扫描切片分析经验，以第一作者发表SCI论文六篇，授权发明专利一项。研究课题涉及肺癌、结直肠癌、乳腺癌、胰腺癌切片的癌灶检测与肿瘤微环境分析，以及配套的切片质量控制、主动学习，以及染色模式分析等技术。

更多信息欢迎请访问我的个人主页：http://faculty.nuist.edu.cn/jiaoyiping/zh_CN/index.htm

代表性论文

[1] Jiao Y, Li J, Qian C, et al. Deep learning-based tumor microenvironment analysis in colon adenocarcinoma histopathological whole-slide images[J]. Computer Methods and Programs in Biomedicine, 2021, 204: 106047.

[2] Jiao Y^#, Yuan J^#, Qiang Y, et al. Deep embeddings and logistic regression for rapid active learning in histopathological images[J]. Computer Methods and Programs in Biomedicine, 2021, 212: 106464.

[3] Jiao Y^#, Yuan J^#, Sodimu O M, et al. Deep Neural Network-Aided Histopathological Analysis of Myocardial Injury[J]. Frontiers in Cardiovascular Medicine, 2021, 8.

[4] Jiao Y, Li J, Fei S. Staining condition visualization in digital histopathological whole-slide images[J]. Multimedia Tools and Applications, 2022: 1-17.

[5] Jiao Y, Li Z, Chen X, et al. Preprocessing methods for near‐infrared spectrum calibration[J]. Journal of Chemometrics, 2020, 34(11): e3306.

[6] Jiao Y, Qian C, Fei S. Commentary: Overall Survival in Heart Disease–Related Death in Non-Small Cell Lung Cancer Patients: Nonimmunotherapy Versus Immunotherapy Era: Population-Based Study[J]. Frontiers in Oncology, 2021, 11.