8月24日上午，澳洲阿德莱德大学Tony Weitong Chen博士来我院作题为“Towards Fair and Robust Medical AI: Navigating Imbalanced and Under-annotated Health Data”的学术报告。本次报告由现代邮政学院院长孙知信教授主持，学院部分师生参与。

在报告中，Tony Weitong Chen博士首先表明人工智能、机器学习正在席卷医疗保健行业。其次他认为机器学习在医疗保健行业的成功在很大程度上取决于能否获得全面、多样化和注释良好的数据集。最后，他探讨了处理未充分注释的健康数据的解决方案，该方案不仅克服了数据限制，还增强了机器学习模型的公平性和鲁棒性。

报告结束后，Tony Weitong Chen博士与学院师生就机器学习相关领域方面的问题进行了热烈的学术交流和讨论，在场师生受益匪浅。

嘉宾简介：

Dr Tony Weitong Chen holds the position of a Lecturer (Assistance Professor) at the University of Adelaide and serves as the Co-director of the Data Transpose Lab. He is affiliated with the Australia Institute for Machine Learning and also represents early and mid-career researchers at Adelaide University. Dr. Chen completed both his PhD and Master's degrees at the University of Queensland, Australia, in 2020. Since then, his scholarship has been evidenced by over 40 peer-reviewed articles in esteemed journals and prominent international conferences such as IJCAI, AAAI, WWW, CIKM, IEEE ICDM, SIAM DM, WWWJ, and TKDD. Beyond academic publications, Dr. Chen has actively contributed to professional services. He's held pivotal roles like the PC Co-chair for ADMA 2022 and has served on conference steering committees, as well as being an SPC, PC member, and reviewer for notable journals including SIG KDD, ICML, TKDE, IJCAI, AAAI, CIKM, IJCNN, MobiSPC, AI, ACM Computing Survey, JCST, KAIS, among others.

His research primarily revolves around machine learning, particularly its applications to medical data. This interest has fostered robust collaborations spanning universities, industry, governmental bodies, and professional organizations. Testament to the significance and potential of his work, Dr. Chen's research endeavors have been backed by over $340,000 in grants and funding.

撰稿：宋秋月

图片：孙哲

审核：孙知信