Professor Franco Gandolfi
Georgetown University, USA
Brief Introduction: Senior university leader, executive board member, published author, serial entrepreneur, public speaker, and international consultant, Prof. Dr. Franco Gandolfi is currently the Distinguished Professor in Management at the California Institute of Advanced Management (CIAM) in Los Angeles, California. Dr. Gandolfi previously served as the Inaugural Campus Director and Pro-Vice-Chancellor (PVC) of Iqra University’s Bahria Town Campus in Karachi, Pakistan, as CEO of Lancaster University in Ghana, and as a Member of the Executive Board of the Nguyen Hoang Group (NHG), a conglomerate of business units in the education space in Vietnam. Prior to his roles in Pakistan, Ghana, and Vietnam, he served as the Vice-Chancellor (VC) and Chief Executive Officer (CEO) of Manipal International University (MIU) in Kuala Lumpur, Malaysia. Previously, he had held deanships and senior professorial appointments at the Canadian University of Dubai, UAE, the University of the South Pacific, Fiji, California Baptist University in Riverside, California, and Central Queensland University in Sydney, Australia. Furthermore, Prof. Dr. Franco Gandolfi holds a full professorship in leadership with Georgetown University in Washington DC, one of the world’s most renowned research universities.
Speech Title：The pandemic and unprecedented disruption: The road towards a new normal
Professor Yang Guangfei
Dalian University of Technology, China
Brief Introduction: PhD from Waseda University (artificial intelligence), professor and doctoral supervisor at Dalian University of Technology, and director of the Big Data and Intelligent Decision Research Center of Dalian University of Technology.Engaged in interdisciplinary research on big data, artificial intelligence, management decision-making, and sustainable development. Hosted 5 national-level projects including key projects of the National Social Science Foundation, general projects of the National Natural Science Foundation of China, general projects of the China Postdoctoral Fund, special funding projects of the China Postdoctoral Fund, Social Science Fund of the Ministry of Education, and key social science planning projects of Liaoning Province More than 20 provincial and ministerial level projects. Participate in national innovation groups, innovation teams of the Ministry of Education, major national science and technology projects, major national soft science projects, national science and technology support plans, and key projects of the National Natural Science Foundation. The post-evaluations of the National Natural Science Foundation of China Youth Fund and general projects were all evaluated as "excellent".
Speech Title：Data-Driven Modeling for Environment Management: Method and Application
Associate Professor Wu Haocun
South China University of Technology, China
Brief Introduction: Associate Professor Wu Haocun received his PhD in financial statistics from the University of Hong Kong in 2007 and graduated from the Department of Mathematics at South China University of Technology in 2002. Currently, he is an associate professor at the School of Economics and Finance of South China University of Technology and a master's tutor in the Department of Quantitative Economics. Lectures on statistics, advanced econometrics and other undergraduate and postgraduate courses. He also serves as a course instructor in innovative programs such as the Economics Innovation Class, the All-English Finance Class, and the Financial Technology Elite Class offered by the School of Economics and Finance. It has many years of experience in higher education and scientific research consulting in the Guangdong-Hong Kong-Macao Greater Bay Area. He has taught and conducted academic research at Sun Yat-sen University, Hong Kong Polytechnic University, University of Macau, Macau University of Science and Technology, Macau Institute for Tourism Studies and other universities. He has presided over a number of scientific research consulting projects, including projects funded by the National Social Science Fund and the Ministry of Education. He has been published in international academic magazines He has published more than 30 papers at conferences and conferences, including nearly 10 SSCI/SCI papers, and has served as an academic reviewer for several international academic magazines. In recent years, his main research directions have been financial technology and digital economy, economic big data analysis and statistical modeling, economic analysis and countermeasures of the service industry under the epidemic crisis, and quantitative research on the economy and society of the Guangdong-Hong Kong-Macao Greater Bay Area. It is hoped that through the innovative use of quantitative economic models, practical problems arising in the national economy and regional development will be solved, and management inspiration and policy suggestions will be provided by combining the subject knowledge of economics and finance.
Speech Title：Impacts of Digital Inclusive Finance on Urban Economic Resilience of China
Professor Wei Wei
Xi'an University of Technology, China
Brief Introduction: Wei Wei, Master's Supervisor, Senior Member of CCF, Senior Member of IEEE&ACM, Scholar from Hanjiang, Shaanxi, CCF Internet of Things Committee, Network Data Committee, etc., with an H-index coefficient of 65+and Google citations exceeding 14316+. He obtained a Ph.D. in Computer Engineering from Xi'an Jiaotong University in 2011, completed a visiting study at UNL University in the United States in 2009, and completed a postdoctoral research in Electrical Engineering at Xi'an University of Technology in 2015. In 2017, he visited and completed postdoctoral research at UTD University in the United States. From 2022 to 2023, he has been continuously selected as one of the top 2% scientists in the world by Stanford. (Selected for both lifelong influence and annual influence), selected as a highly cited scholar in China by Elsevier in 2022&2023.
Speech Title：Parking Navigation with Information Field Based on WSNs Big-data Frame