报告题目：Privacy and Trustworthy Machine Learning for Healthcare

报告摘要

During the past decade, deep learning has achieved great success in healthcare. However, most existing methods aim at model performance in terms of higher accuracy, which lacks the information reflecting the reliability of the prediction. It cannot be trustworthy for diagnosis making and even is disastrous for safety-critical clinical applications. How to build a reliable and robust healthcare system has become a focal topic in both academia and industry. In the talk, I will introduce several our recent works for privacy and trusted AI in healthcare, including: privacy-preserving federated learning and multi-modality uncertainty learning. Moreover, I also discuss some open challenges for trustworthy learning.

1.Xiaoxiao Liang, Yiqun Lin, Huazhu Fu, Lei Zhu, and Xiaomeng Li, "RSCFed: Random Sampling Consensus Federated Semi-supervised Learning", CVPR, 2022.

2.Liang Gao, Huazhu Fu, Li Li, Yingwen Chen, Ming Xu, and Cheng-Zhong Xu, "FedDC: Federated Learning with Non-IID Data via Local Drift Decoupling and Correction", CVPR, 2022.

3.Chun-Mei Feng, Yunlu Yan, Huazhu Fu, Yong Xu, and Ling Shao, "Specificity-Preserving Federated Learning for MR Image Reconstruction", arXiv, 2021.

4.Zongbo Han, Changqing Zhang, Huazhu Fu, and Joey Tianyi Zhou, "Trusted Multi-View Classification", ICLR, 2021.

5.Huan Ma, Zongbo Han, Changqing Zhang, Huazhu Fu, Joey Tianyi Zhou, and Qinghua Hu, "Trustworthy Multimodal Regression with Mixture of Normal-inverse Gamma Distributions", NeurIPS, 2021.

嘉宾简介

付华柱，现任新加坡科技研究局 (A*STAR) 高性能计算研究所 (IHPC) 高级研究员 (Senior Scientist)。2013 年博士毕业于天津大学计算机科学学院，2013 年至 2015 年在新加坡南洋理工大学进行博士后研究，2015 年至 2018 年在新加坡科技研究局 (A*STAR) 资讯通讯研究院 (I2R) 担任研究员，2018 年至 2021 年在阿联酋起源人工智能研究院 (Inception Institute of Artificial Intelligence) 担任高级研究员。主要研究方向为计算机视觉，机器学习，以及人工智能医学图像分析等。至今已在 IEEE TPAMI, IEEE TIP, IEEE TMI 等期刊以及 CVPR, ICCV, NeurIPS, ICLR 等会议上发表论文 150 余篇，Google Scholar 引用超过 8800 次，曾获 2021 年 ICME 最佳论文奖、2021 年 MICCAI Young Scientist Publication Impact Award提名、2014 年计算机协会（CCF）优秀博士论文提名等。现担任 IEEE Transactions on Medical Imaging (TMI)，和IEEE Journal of Biomedical and Health Informatics (JBHI) 等期刊编委会成员 (Associate Editor)，国际会议 AAAI、IJCAI、和 MICCAI 等的区域主席， MICCAI OMIA workshop的联合主席，以及国际眼科图像系列比赛 i-Challenge 的发起人之一，同时也是IEEE Bio Imaging and Signal Processing Technical Committee (BISP TC) 技术委员。

个人主页: https://hzfu.github.io/

特别感谢本次Webinar主要组织者：

庄吓海（复旦大学）