征文 | 第五届BigDIA2019国际会议

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“2019年度图像图形领域会议”

第五届International Conference on Big Data and Information Analytics会议将于2019年7月8-10日在云南昆明召开。

BigDIA 2019 will bring together research scientists from academia, industries, and government agencies to report progress and exchange ideas to address challenges in fundamental research and rapid knowledge translation in collecting, processing, analyzing, integrating, annotating and visualizing Big Data for scientific exploration, business and public policy decision-making. The meeting aims to promote interdisciplinary collaborations among participants to further develop big data science, algorithms, technologies and domain-specific applications.

Conference organizer

Founding Institutes

Xi'an Jiaotong University, China

National University of Defense Technology, China

York University, Canada

Hosting and Organizing Institute

Yunnan University

Supporting Institutes

Big Data Algorithm and Analysis National Engineering Laboratory;

National Engineering Laboratory for Big Data Analysis and Applied Technology; 

National Engineering Laboratory for Big Data Analysis Systems;

Laboratory for Industrial and Applied Mathematics，Yunnan Provincial Applied Statistics Association

昆明滇池（来源于网络）

Scope

Topics of interest include, but are not limited to:

Fundamental theories for Big Data analytics

• Statistical theories for Big Data

• Computer science theories for Big Data

• Mathematical theories for Big Data

• Big Data computing: Architecture, database, algorithm, platform, visualization

• Artificial Intelligence (AI) for Big Data

Application areas

• EHR and health care Big Data

• Bioinformatics

• Imaging data

• Precision medicine

• Big Data prediction and decision-support systems

• Finance and economics

• Wearable or mobile device data

• Internet of Things

• Big Data management  in cloud

Paper Submission

This conference is technical sponsored by IEEE SMC Society and all accepted full papers will be submitted for inclusion into the IEEE Xplore^TM. Paper submissions should be formatted according to the IEEE Manuscript Template and a maximum of 8 pages. Please visit  http://2019bigdata.medmeeting.org for more information.

Important Dates

Paper Submission Deadline：May 30th, 2019
Notification of Acceptance：June 10th, 2019

Final Manuscript Due：June 20th, 2019

Contacts

Deyu Meng  Tel: [phone],

       [e-mail] 

Weidong Bao  Tel: [phone], 

       [e-mail]

Xiaomin Zhu  Tel: [phone]

       [e-mail]

Keynote Speakers

Professor Zongben Xu is an academician of Chinese Academy of Sciences, mathematician, signal and information processing expert Xi'an Jiaotong University. He was a Vice President of Xi'an Jiaotong University, and is currently the Deputy Director of the Information Technology Science Department of the Chinese Academy of Sciences; Dean of Xi'an Institute of Mathematics and Mathematics Technology, Xi'an Jiaotong University; Director of the National Engineering Laboratory of Big Data Algorithms and Analysis Technology.

Dr. Wei Xu is an Associate Professor of Biostatistics at Dalla Lana School of Public Health, University of Toronto. He leads the Biostatistics Department at the Princess Margaret Cancer Centre. Dr. Xu’s research interests focus on cancer big data, statistical methodology, clinical trial design and analysis, statistical genetics, biomarker research, predictive model construction, and personalized medicine development. 

Title: Dig data in cancer clinical and genomic research

Songxi Chen is a Professor of Statistics, Iowa State University, USA, and  a Professor at Peking University, China. He is a national specialist, a co-director of the Statistical Science Center, and a co-director of the Department of Business Statistics and Economics, Peking University. He is a fellow of the Institute of Mathematical Statistics (IMS); a fellow of the American Statistical Society; and an elected member of the International Statistical Society. 

Title: Distributed Statistical Inference for Massive Data

Weidong Liu, is a winner of the National Outstanding Youth Science Foundation, and a Professor, the School of Mathematical Sciences, Shanghai Jiaotong University. His expertise includes statistical inference of high-dimensional data and distributed statistical inference of large data. He has authored major research papers published in Ann. Statist., JASA, JRSSB, Biometrika and Ann. Probab.

Title: Distributed Robust Estimation on Sparse  Linear Regression

Ming Yuan is Professor of Statistics at Columbia University. He was previously a Senior Investigator at Morgridge Institute for Research and Professor at University of Wisconsin at Madison and a Coca-Cola Junior Professor at Georgia Institute of Technology. His research interests lie broadly in statistics and its interface with other quantitative and computational fields such as optimization, machine learning and computational biology.

Dr. Jun (Luke) Huan directs the Baidu Big Data Lab. Before that he was the Charles and Mary Jane Spahr Professor in the Department of Electrical Engineering and Computer Science at the University of Kansas.   Dr. Huan works on Data Science, AI, Machine Learning and Data Mining. His research is recognized globally. He has published more than 130 peer-reviewed papers in leading conferences and journals and has graduated ten Ph.D. students. 

Title: AutoDL: Automated Deep Learning for Open & Inclusive AI

For more information about BigDIA 2019, please click here.

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