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【09月16日周五】西电海外青年校友学术论坛-康奈尔大学王飞教授讲座


为隆重庆祝母校建校91周年,西电海外及港澳地区校友会联盟主办、西电美国校友会承办《西电海外青年校友学术论坛》,邀请海外优秀西电青年校友学者做学术演讲和交流。论坛为期8周,每周一期,美国普渡大学孙文海教授担任论坛主席。第一期讲座嘉宾为ACM杰出科学家美国康奈尔大学王飞教授。
讲座:      

Combating the COVID-19 Pandemic with Insights Generated from Real World Longitudinal Patient Electronic Health Records


主讲人:  

Dr. Fei Wang

Associate Professor of Health Informatics

Department of Population Health Sciences at Weill Cornell Medicine, Cornell University


时间:   9月17日周六早九点半(北京时间)

            9月16日周五晚九点半(美东时间)

Zoom Meeting ID:   852 9379 4606

Passcode:  1931


Abstract: 

Since its outbreak in early 2020, COVID-19 has impacted hundreds of millions of people worldwide. Numerous research has been conducted on COVID-19 in various disciplines, from basic science to clinical practice and public health policy making. During the pandemic, a huge amount of longitudinal electronic health records has been accumulated from patient care, which provides a rich resource containing invaluable insights for COVID-19. In this talk, I will introduce several research from my lab on this direction, and point out potential future directions.

Bio: Fei Wang is an Associate Professor at Department of Population Health Sciences, Weill Cornell Medicine, Cornell University. His major research interest is data mining, machine learning and their applications in health data science. He has published on the top venues of related areas such as ICML, KDD, NeurIPS, AAAI, JAMA Internal Medicine, Annals of Internal Medicine, etc. His papers have received over 21,000 citations so far with an H-index 70. His (or his students’) papers have won 8 best paper (or nomination) awards at international academic conferences. His team won the championship of the 2022 American Association of Clinical Chemistry (AACC) data challenge, 2017 NIPS/Kaggle Challenge on Classification of Clinically Actionable Genetic Mutations and 2016 Parkinson’s Progression Markers Initiative data challenge organized by Michael J. Fox Foundation. 


Dr. Wang is the recipient of the NSF CAREER Award in 2018, the inaugural research leadership award in IEEE International Conference on Health Informatics (ICHI) 2019, Amazon Machine Learning for Research Award in 2017 and 2019, Google Faculty Research Award in 2020, Sanofi iDEA Award in 2021. Dr. Wang was the chair of the Knowledge Discovery and Data Mining working group in American Medical Informatics Association (AMIA) in 2018-2019. Dr. Wang’s research has been supported by funding agencies including NSF, NIH, ONR, PCORI and MJFF. Dr. Wang is a Fellow of the American Medical Informatics Association (AMIA), a Fellow of the International Academy of Health Sciences and Informatics (IAHSI), and a Distinguished Member of the Association for Computing Machinery (ACM).


王飞教授目前为康奈尔大学威尔医学院群体健康科学系健康信息学副教授。他于2003年本科毕业于西安电子科技大学机电工程学院自动化系,2008年博士毕业于清华大学自动化系,是全国优秀博士论文奖(百篇)获得者。


王博士当前的主要研究方向为人工智能与智慧医学。他已在相关领域的顶级会议及期刊上发表了超过300篇文章,包括ICML, KDD, NIPS, CVPR, AAAI, IJCAI, JAMA Internal Medicine, Annals of Internal Medicine, Lancet Digital Health等等。他的文章已经收到了超过21,000次引用,他当前的H指数为70。王博士及其指导的学生的论文已经获得8次国际会议(包括数据挖掘及医学信息学)的最佳论文相关奖项。王博士带领的学生队伍曾获得2016年PPMI帕金森病亚型发现数据分析挑战赛冠军,2017年NIPS基因变异分类国际数据分析大赛冠军,以及2022年美国临床化学协会PTHrP检测数据分析挑战赛冠军。王博士是2018年美国自然科学基金委青年学者奖获得者,2019年国际健康信息学大会首届研究领导力奖获得者。王博士是美国医学信息学会数据挖掘与知识发现研究组上届主席,同时也是美国医学信息学会(AMIA)会士,国际健康科学以及信息学学会(IAHSI)会士,2021年入选国际计算机协会(ACM)杰出科学家。



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