Guizhou Provincial Big Data Analysis Engineering Laboratory was established in 2017 through funding from the Special Subsidy Funds for High and New Technology of Guizhou Province (Development and Reform Committee of Guizhou Province for High-tech Industry Program), By achieving innovation and breakthrough in big data mining and analysis as well as comprehensive application of algorithms, it aims to improve innovation capability and application in big data analysis technology, and to promote the development of big data industry.
The Laboratory exists to foster a research environment and create a core team through the resources of Guizhou University. It complies with the top-level design of Guizhou Province “to improve government governance capacity, economic transformation and upgrading transformation and people’s livelihood with big data”. Targeted at big data analysis technology, the Laboratory has cooperated with companies inside and outside the province to build five labs for data description, data preprocessing, data analysis algorithms and models, block data analysis technologies, and data analysis platforms and tools. The Laboratory will establish three major public service platforms for big data analysis and mining, big data processing, and big data visualization, according to the needs of key industrial applications and data industry development. It is expected to lead the development of the big data analysis industry inside and outside the province, and provide basic support for the development of the big data analysis industry in Guizhou, government decisions based on big data, and corporate innovations.
Since the founding of the Laboratory, it has focused on the development and implementation of the big data field and achieved an innovative and systematic approach for 'Government-Business-University-Research' cooperation. It has established Bijiang District Agricultural Big Data Center in Tongren City, Guizhou Agricultural Big Data Platform in Longli County, Grid Based Accurate Service Management Platform for Social Governance in Pearl Community of Huaxi District, and Guizhou Statistics and Publication Platform. It has cooperated with Guiyang Grid Service Management Command and Dispatch Center to jointly build Block Data and Regional Governance Research Center; has worked with Guiyang Traffic Management Bureau to obtain traffic data for big data analysis by establishing “Guiyang Traffic Big Data Incubator”; and jointly built both “Guizhou Intelligent Information Big Data Lab” with Prince Techs and China Telecom, and “Chinese Liquor Big Data Research Institute” with Kweichow Moutai Group and Beijing Big Data Research Institute, to conduct industry research and application demonstration in the Chinese beverage industry. In addition, the Laboratory cooperated with AUDAQUE to jointly publish the 'Block Data GLDM: Model and Specification for Regional Data Resourceization' and it co-published 'China Digital Economy Index' with Caixin Media and BBD Co., Ltd. It also published a book titled, 'The Future with Big Data: Graphical Interpretation of Big Data and Industry Fusion'.
The Laboratory follows the guidelines of the big data industry planning and policies at national, provincial and municipal levels to promote the development of Guizhou Big Data industry. To promote the economic development model, it established big data analysis and mining technology innovation and application platform, and gathered and integrated innovation resources through key common technologies and industrialization. It strengthened the combination of production, education, and research to promote the big data industry and provide dynamic support for cultivating and developing strategic emerging industries.
Wei Qin, Director
Female, Ph.D., Associate Professor of Guizhou University, Vice Dean of Guizhou Big Data Academy (Executive Dean). She obtained a Bachelor of Science in Management from Peking University Information Management Department, Doctor of Informatics from University of Illinois at Urbana-Champaign. She is a member of the Artificial Intelligence and Pattern Recognition Committee of China Computer Federation, Machine Learning Committee of the Chinese Association for Artificial Intelligence, and CSIAM Activity Group on Big Data and Artificial Intelligence. She is mainly engaged in the research of data analysis and mining and has participated in programs such as National Program on Key Basic Research Project (973 Program), the National Social Science Fund Project of United States, the National Research Center for Supercomputing Applications (NCSA) project and the project of Science and Technology Department of Guizhou Province. She has published more than 20 papers and one English monograph.
He Qing, Deputy Director
Male, Ph.D., Associate Professor, Supervisor for Master’s Degree Candidates. He is a council member of the Information and Big Data branch of China Medical Association of Minorities. His main research directions include big data, intelligent optimization, and artificial intelligence. He has presided over a number of big data application projects, such as big data accurate anti-poverty projects. These projects have achieved good social benefits in terms of poverty alleviation and other strategic development work in Guiyang.
Huang Ruizhang, Deputy Director
Female, Ph.D., Associate Professor, Supervisor for Master’s Degree Candidates. Her main research areas and directions include text mining, machine learning, network mining, and knowledge learning. She organized and developed a government website evaluation system based on Internet big data technology. Through the Internet technology, the system automatically collects data from the government website, and evaluates the website’s quality in terms of usability, description accuracy, and update timelines. This system has currently been applied in the e-government system of Guizhou Province.
Ouyang Zhi, Deputy Director
Male, Ph.D., Associate Professor of Guizhou Big Data Academy. He has presided over two horizontal projects of the Big Data Development Administration of Guizhou Province. His research interests include big data applications and governance, and knowledge management.
