A Q&A with Prof. John Wang

The Encyclopedia of Data Science and Machine Learning (ISBN: 9781799892205) delves into state-of-the-art research on big data and machine learning, highlighting their pivotal roles in the Fourth Industrial Revolution. Aimed at professionals and researchers, it serves as a dynamic resource, covering diverse topics and fostering innovative findings in the evolving landscape of data science. With Prof. John Wang's insights, we delve further into the importance and timeliness of his recent publication.

Prof. Wang: The Fourth Industrial Revolution, known as Industry 4.0 or 4IR, brought a revolutionary change to how companies, organizations, and institutions function and evolve. It involves the integration of advanced technologies like AI, IoT, and automation, creating smart and interconnected systems. This transformation optimizes productivity, efficiency, and decision-making processes, enabling entities to stay competitive in an increasingly digitized and interconnected world.

Prof. Wang: The Encyclopedia of Data Science and Machine Learning (ISBN: 9781799892205) (EDSML) explores the latest, state-of-the-art research in the fields of data science, machine learning (ML), data mining (DM), optimization, artificial intelligence (AI), statistics, and the connections, linkages, and applications of knowledge-based business with information systems.

Prof. Wang: EDSML serves as an international platform for practitioners, educators, and researchers to advance the knowledge and practice of Big Data and Machine Learning (BDML). It emphasizes emerging theories, principles, models, processes, and applications, aiming to inspire and disseminate cutting-edge findings into research, business, and communities.

Prof. Wang: BDML deals with descriptive and predictive analytics, emphasizing prescriptive analytics through digital technology and interconnectivity. It continuously explores its "depth" and expands its "breadth." BDML will continue to maximize citizens' "wealth" while promoting society's "health."

Prof. Wang: There are 207 qualified full chapters among the 271 accepted proposals. Ultimately, the encyclopedia comprises 187 high-quality chapters, authored by an international team of over 370 experts from more than 46 countries and regions. These experts represent leading scientists and talented young scholars from various nations, including Algeria, Argentina, Austria, Bangladesh, Brazil, Canada, Chile, China, Colombia, Cuba, Denmark, Egypt, El Salvador, Finland, France, Germany, Ghana, Greece, Hong Kong, Hungary, Indonesia, Iran, Iraq, Japan, Lebanon, Macau, Malaysia, Mexico, Netherlands, New Zealand, Poland, Portugal, Saudi Arabia, Serbia, Singapore, South Africa, Sweden, Switzerland, Syria, Taiwan, Tunisia, Turkey, UK, USA, Venezuela, Vietnam, etc.

Prof. Wang: With my role as the Editor of prominent publications, including the Encyclopedia of Business Analytics and Optimization and Data Warehousing and Mining, coupled with my extensive editorial experience, I am well-equipped to be an authority on this book's coverage, drawing upon a wealth of knowledge in the field.

Prof. Wang: I possess extensive experience in the areas covered by this book through my involvement in special organizations and professional affiliations. I served as the Editor for several journals indexed in Scopus or EI, including the International Journal of Data Science, International Journal of Business Analytics, International Journal of Data Mining, Modelling and Management, and more. Additionally, I have been recognized for academic excellence, receiving the InfoSci-Journals Distinguished Fellowship Award from IGI Global in 2016 and serving as a Keynote Speaker at the International Conference on Data Analytics and Computing in 2022. I have received two special range adjustments for his extraordinary contributions beyond a tenured full professor. Furthermore, my noteworthy affiliation includes teaching the graduate course on Business Analytics four times at Harvard University, showcasing my commitment to education and expertise in the field.

John Wang is a professor in the Department of Information Management and Business Analytics at Montclair State University, USA. Having received a scholarship award, he came to the USA and completed his PhD in operations research from Temple University. Due to his extraordinary contributions beyond a tenured full professor, Dr. Wang has been honored with two special range adjustments in 2006 and 2009, respectively. He has published over 100 refereed papers and seventeen books. He has also developed several computer software programs based on his research findings. He serves as Editor-in-Chief for ten Scopus-indexed journals, such as Int. J. of Business Analytics, Int. J. of Information Systems and Supply Chain Management, Int. J. of Information Systems in the Service Sector, Int. J. of Applied Management, Int. J. of Information and Decision Sciences, Int. J. of Data Mining, Modelling and Management, etc. He is the Editor of Encyclopedia of Business Analytics and Optimization (five-volume), Data Warehousing and Mining: Concepts, Methodologies, Tools, and Applications (six-volume) and the Editor of the Encyclopedia of Data Warehousing and Mining, 1st (two-volume) and 2nd (four-volume). His long-term research goal is on the synergy of operations research, data mining and cybernetics.

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Casey Long
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