讲座人： James M. Tien教授
讲座题目：Fourth Industrial Revolution: Internet of Things, Real-Time Decision Making, Artificial Intelligence
讲座摘要：The post-COVID world economy continues to underscore the prominence of the disruptive and interrelated Big Data technologies of Internet of Things (IoT), Real-Time Decision-Making (RTDM), and Artificial Intelligence (AI), which, together, underpin the Fourth Industrial Revolution. IoT is generally considered to be a range of devices or systems, each with an Internet Protocol address. In earlier papers, the author defined such devices and systems as servgoods, or items that can be thought of as physical products enveloped by services-oriented layers that can render each product or good to be smarter, adaptable and/or customizable for a specific purpose. Indeed, the transmission of both information and power with greater bandwidth (i.e., data transfer capacity) and minimal latency (i.e., data delay) are critical to RTDM; it is based on an integrated system of computers that must perform critical decision-oriented functions in near real-time or within a time frame of as short as 67 nanoseconds, each encompassing the steps of sensing or data fusion, processing or data analysis, reacting or decision-making, and learning or feedback processing. Clearly, an IoT servgood – or, say, an autonomous vehicle – must be constantly sensing, processing, reacting, and learning. At present, the most critical Big Data component is AI, an evolving set of technologies that enable computers to simulate elements of human thinking, understanding, learning and decision-making. Central to AI is machine learning, an approach that is loosely modeled on the way layers of neurons and synapses in the brain change as they assimilate new input; sometimes, such deep learning may even result in a trained machine that can outperform their human counterparts. AI-based servgoods include virtual assistants that can understand natural language and appropriately respond; robots that can automatically carry out a complex series of tasks; medical devices that can assist with diagnostic and/or therapeutic decisions; and platforms that can allow users to employ pre-built decision-making algorithms. Finally, in a connected IoT, RTDM and AI world, there are ample opportunities for breaches of privacy and security; not only are the resultant servgoods vulnerable to being hacked but so are their various connected devices. Clearly, such breaches of security must be appropriately addressed by technical standards and government regulations.
专家简介：James M. Tien教授，美国国家工程院院士、迈阿密大学杰出教授，曾担任迈阿密大学工程学院院长、国际电气与电子工程师协会（IEEE）总会副主席、执行委员会主席、产品委员会主席、期刊委员会主席等职务，长期从事智能制造及其管理决策方面的研究，并发表了大量文章，获得了一系列教学和研究奖项，包括被选为IEEE Fellow、INFORMS Fellow、AAAS Fellow，且获得了IEEE Joseph G. Wohl杰出职业奖，IEEE主要教育创新奖，IEEE Norbert Wiener和IBM教师奖等，享有崇高学术声誉和巨大国际影响力。
讲座题目：Chinese Digital Economy: Development and Future Trends
讲座摘要：The digital economy has become a significant force in reorganizing global resources, reshaping the structure of worldwide economy, and changing global competitive landscape. In this talk, it starts with the basic concepts of digital economy. Second, the history of development regarding major international digital economies and the current status of China's digital economy are reviewed. Then, the talk especially illustrates the recent new advances that emerged in the evolution of digital economy. Finally, several suggestions of policies to promote, optimize, and strengthen China's digital economy are proposed, which are data openness and protection, key technologies, training programs for talents, livelihood services for citizens, social credit system establishment, and international collaborations.
Yong Shi serves as the Director of the Research Center on Fictitious Economy & Data Science (FEDS) and the Director of the Key Lab of Big Data Mining and Knowledge Management (BDK), both at Chinese Academy of Sciences. He has been the Isaacson Professor, Union Pacific Chair and Charles W. and Margre H. Durham Distinguished Professor of University of Nebraska at Omaha, USA. He is the Elected Fellow of the World Academy of Sciences for the Advancement of Science in Developing Countries (TWAS, 2015), the Counselor of the State Council of the People’s Republic of China (2016), the Elected Member of the International Eurasian Academy of Sciences (IEAS, 2017), the Elected Fellow, the Asia-Pacific Artificial Intelligence Association (AAIA, 2022), the Elected Fellow, the International Academy of Information Technology and Quantitative Management (IAITQM, 2022) and the Elected Fellow, Web Intelligence Academy (WIA, 2023). His research interests include Business Intelligence and Analytics (BI&A), Big Data Mining and Knowledge Management, Data-driven Decision Making, Digital Economy, Artificial Intelligence, and Multiple Criteria Decision Making (MCDM). He has authored and co-authored over 36 books and more than 400 papers published in various peer-reviewed journals and conference proceedings. He has received a number of honors and awards, including the Georg Cantor Award by International Society on Multiple Criteria Decision Making (2009), the Fudan Prize of Distinguished Contribution in Management by Fudan Premium Fund of Management, China (2009), Science Fellow by the Commonwealth Scientific and Industrial Research Organization (CSIRO), Australia (2012), Doctor Honoris Causa of Agora University, Romania (2014), the WIC Outstanding Research Contribution Award, Chile (2018), and the Cheng Siwei Global Prize, China (2021). He has been the Founding Editor and the Editor-in-Chief of two academic journals, including International Journal of Information Technology & Decision Making (IJITDM, SCI) and Annals of Data Science (AODS, Springer).