{"title":"走向复杂结构和大数据下的个性化泛经济关联分析","authors":"E. Xing","doi":"10.1109/BIBM.2015.7359647","DOIUrl":null,"url":null,"abstract":"Dr. Eric Xing is a Professor of Machine Learning in the School of Computer Science at Carnegie Mellon University, and Director of the CMU/UPMC Center for Machine Learning and Health. His principal research interests lie in the development of machine learning and statistical methodology, and large-scale computational system and architecture; especially for solving problems involving automated learning, reasoning, and decision-making in high-dimensional, multimodal, and dynamic possible worlds in artificial, biological, and social systems. Professor Xing received a Ph.D. in Molecular Biology from Rutgers University, and another Ph.D. in Computer Science from UC Berkeley. He servers (or served) as an associate editor of the Annals of Applied Statistics (AOAS), the Journal of American Statistical Association (JASA), the IEEE Transaction of Pattern Analysis and Machine Intelligence (PAMI), the PLoS Journal of Computational Biology, and an Action Editor of the Machine Learning Journal (MLJ), the Journal of Machine Learning Research (JMLR). He was a member of the DARPA Information Science and Technology (ISAT) Advisory Group, a recipient of the NSF Career Award, the Sloan Fellowship, the United States Air Force Young Investigator Award, and the IBM Open Collaborative Research Award. He was the Program Chair of ICML 2014.","PeriodicalId":73283,"journal":{"name":"IEEE International Conference on Bioinformatics and Biomedicine workshops. IEEE International Conference on Bioinformatics and Biomedicine","volume":"24 1","pages":"4"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Toward personalized pan-omic association analysis under complex structures and big data\",\"authors\":\"E. Xing\",\"doi\":\"10.1109/BIBM.2015.7359647\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Dr. Eric Xing is a Professor of Machine Learning in the School of Computer Science at Carnegie Mellon University, and Director of the CMU/UPMC Center for Machine Learning and Health. His principal research interests lie in the development of machine learning and statistical methodology, and large-scale computational system and architecture; especially for solving problems involving automated learning, reasoning, and decision-making in high-dimensional, multimodal, and dynamic possible worlds in artificial, biological, and social systems. Professor Xing received a Ph.D. in Molecular Biology from Rutgers University, and another Ph.D. in Computer Science from UC Berkeley. He servers (or served) as an associate editor of the Annals of Applied Statistics (AOAS), the Journal of American Statistical Association (JASA), the IEEE Transaction of Pattern Analysis and Machine Intelligence (PAMI), the PLoS Journal of Computational Biology, and an Action Editor of the Machine Learning Journal (MLJ), the Journal of Machine Learning Research (JMLR). He was a member of the DARPA Information Science and Technology (ISAT) Advisory Group, a recipient of the NSF Career Award, the Sloan Fellowship, the United States Air Force Young Investigator Award, and the IBM Open Collaborative Research Award. He was the Program Chair of ICML 2014.\",\"PeriodicalId\":73283,\"journal\":{\"name\":\"IEEE International Conference on Bioinformatics and Biomedicine workshops. IEEE International Conference on Bioinformatics and Biomedicine\",\"volume\":\"24 1\",\"pages\":\"4\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-11-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE International Conference on Bioinformatics and Biomedicine workshops. IEEE International Conference on Bioinformatics and Biomedicine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BIBM.2015.7359647\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE International Conference on Bioinformatics and Biomedicine workshops. IEEE International Conference on Bioinformatics and Biomedicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIBM.2015.7359647","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
Eric Xing博士是卡内基梅隆大学计算机科学学院机器学习教授,也是CMU/UPMC机器学习与健康中心主任。他的主要研究兴趣是机器学习和统计方法的发展,以及大规模计算系统和架构;特别是在人工、生物和社会系统的高维、多模态和动态可能世界中解决涉及自动学习、推理和决策的问题。邢教授获得罗格斯大学分子生物学博士学位,以及加州大学伯克利分校计算机科学博士学位。他是《应用统计年鉴》(AOAS)、《美国统计协会杂志》(JASA)、《IEEE模式分析与机器智能学报》(PAMI)、《公共科学图书馆计算生物学杂志》(PLoS Journal of Computational Biology)的副主编,也是《机器学习杂志》(MLJ)、《机器学习研究杂志》(JMLR)的行动编辑。他是DARPA信息科学与技术(ISAT)咨询小组的成员,是NSF职业奖、斯隆奖学金、美国空军青年研究员奖和IBM开放合作研究奖的获得者。他是ICML 2014的项目主席。
Toward personalized pan-omic association analysis under complex structures and big data
Dr. Eric Xing is a Professor of Machine Learning in the School of Computer Science at Carnegie Mellon University, and Director of the CMU/UPMC Center for Machine Learning and Health. His principal research interests lie in the development of machine learning and statistical methodology, and large-scale computational system and architecture; especially for solving problems involving automated learning, reasoning, and decision-making in high-dimensional, multimodal, and dynamic possible worlds in artificial, biological, and social systems. Professor Xing received a Ph.D. in Molecular Biology from Rutgers University, and another Ph.D. in Computer Science from UC Berkeley. He servers (or served) as an associate editor of the Annals of Applied Statistics (AOAS), the Journal of American Statistical Association (JASA), the IEEE Transaction of Pattern Analysis and Machine Intelligence (PAMI), the PLoS Journal of Computational Biology, and an Action Editor of the Machine Learning Journal (MLJ), the Journal of Machine Learning Research (JMLR). He was a member of the DARPA Information Science and Technology (ISAT) Advisory Group, a recipient of the NSF Career Award, the Sloan Fellowship, the United States Air Force Young Investigator Award, and the IBM Open Collaborative Research Award. He was the Program Chair of ICML 2014.