报告人：王猛 博士 新加坡国立大学
主持人：陈阳
报告时间：2024年12月26日（周四）上午10:00
报告地点：东南大学九龙湖校区计算机楼513报告厅
报告摘要：Artificial intelligence (AI) has the potential to revolutionize healthcare, but concerns about reliability hinder its widespread adoption. In this talk, I will introduce several works that focus on enhancing the reliability of AI models in medical applications. These works explore methods to improve model reliability without compromising performance, and increase the transparency of AI decision-making processes. By discussing these advancements, I aim to shed light on the current challenges and potential solutions for making AI models trustworthy in healthcare settings.
报告人简介：王猛博士，新加坡国立大学Research Fellow，主要从事医学人工智能与多模态影像分析研究。担任IEEE Journal of Biomedical and Health Informatics和Frontiers in Medicine客座编辑。曾于新加坡科技研究局（A*STAR）高性能计算研究所及哈佛医学院担任Scientist和Postdoctoral Research Fellow。研究方向涵盖计算机视觉、医学图像分析、医学影像大模型及可信人工智能等领域。迄今已发表学术论文40余篇，包括Nature Communications、Cell Reports Medicine、IEEE Transactions on Pattern Analysis and Machine Intelligence、IEEE Transactions on Medical Imaging等国际顶级期刊，以及CVPR、MICCAI等国际顶级会议，并参与编写专著《Federated Learning for Medical Imaging》。
