Academic Talk of Professor Hui Xiong of Rutgers New Jersey State University and Dr. Hengshu Zhu, Chief Scientist of Baidu

 

Dr. Hengshu Zhu, a professor of Rutgers New Jersey State University, and Hui Xiong, a chief scientist of Baidu gave excellent talks online to the faculties and students of the school on October 19, 2020, receiving the invitation of Professor Ming Yang in the School.

Dr. Hengshu Zhu, currently the chief scientist of Baidu and the head of Baidu Talent Intelligence Center (TIC), is now mainly responsible for the research and development of AI data science products in Baidu's internal business intelligence and enterprise talent management. He is devoted to key technologies in machine learning and data mining, business intelligence, human resources big data, social welfare and other fields. He has published more than 80 papers in several international top-tier conferences and journals in the field of artificial intelligence, such as KDD, SIGIR, WWW, IJCAI, AAAI, TKDE, TOIS, PIEEE and so on. He has won the best paper award or nomination Award for four times. His related achievements have been widely talked by MIT Technology Review、Nikkei Asian Review、Fast Company and other authoritative media. He has served as a member of the (Senior) procedures Committee of several top academic conferences and a reviewer of more than 10 IEEE / ACM transactions. As a co-chair, he has successively founded the "International Symposium on organizational behavior and talent analysis" (OBTA-2018) and "International Symposium on talent management computing" (TMC-2019) on KDD. When in charge of the organizing committee, he successfully bid for the top international data mining event KDD Cup 2019 Regular ML Track on behalf of Baidu.  Some of his honors include: special award of president of Chinese Academy of Sciences (2014), Excellent Doctoral Dissertation Award of Chinese Academy of artificial intelligence (2016), Excellent Doctoral Dissertation Award of Chinese Academy of Sciences (2016), Microsoft academic "KDD global 20 university new star" (2016), and Baidu top prize seed project (2016), Harvard Business Review "Lam Chalan Management Practice Award" (2018), "China Human Resource Management School Award" (2018) of Business School of Renmin University of China, and first prize of Natural Science Award of Ministry of education of China (2018). He is also a senior member of CCF, ACM and IEEE.

Dr. Hengshu Zhu’s talk is "Baidu intelligent recruitment technology and application practice". With the rapid development of big data and machine learning technology, intelligent system has more and more ability to deal with various practical problems, and has been widely used in various application scenarios such as production and life. At the same time, recruitment websites and enterprises have accumulated rich recruitment big data. The use of artificial intelligence technology to build an intelligent recruitment system can effectively grasp the market recruitment trend and improve recruitment efficiency. Dr. Zhu's talks take Baidu think tank as an example. This paper introduces the opportunities and challenges in the field of talent recruitment, the AI technology and innovative product practice accumulated by Baidu in the field of intelligent recruitment: intelligent talent evaluation, personnel post matching based on deep learning and personalized interview question recommendation, etc.

Professor Hui Xiong is currently a full-time professor of Rutgers New Jersey State University and Chair Professor of RBS president. He is mainly devoted to data mining, business intelligence, and human resource big data. He currently serves as the IEEE fellow, ACM distinguished scientist, Professor of Yangtze River chair of the Ministry Education of China, category B of overseas distinguished young scholars of China National Fund Commission (NSFC) (Overseas, Hong Kong and Macao Scholars Cooperative Research Fund), Harvard Business Review 2018 "Lam Charan Management Practice Award" - grand prize, 2017 IEEE ICDM outstanding service award, and ICDM-2011 best research paper award. Professor Hui Xiong is the co editor of Encyclopedia of GIS (Springer) and the editorial board of IEEE Transactions on Big Data (TBD), ACM transactions on knowledge discovery from data (TKDD) and ACM transactions on Management Information Systems (TMIS). He has served as chairman of the common procedure Committee for ACM KDD 2012 corporate and government topics, chairman of the common procedure Committee of IEEE ICDM 2013, chairman of the common conference of IEEE ICDM 2015, and chairman of the research topic procedure Committee of ACM kdd-2018. In terms of personnel training, most of the doctoral graduates under the guidance of Professor Hui Xiong have become tenure track professors of famous American universities, including the University of Tennessee Knoxville, the University of Arizona, Stony Brook University of New York State University and the University of Central Florida Florida, George Mason University, City University of Hong Kong, and ESCP Business School - Paris.

Professor Hui Xiong's talk is "talent analysis: from economic law to data science". It introduces the application of big data in talent management. Through a simple introduction, Professor Xiong explained the different definitions of personnel, talents and characters. Taking the construction of his own team as an example, he proposed to have an innovative thinking ability and put forward the method of talent selection from a strategic position. Professor Xiong's team has developed a set of powerful innovative big data technologies for intelligent human resource management, such as recruitment, performance evaluation, talent retention, talent development, job matching, team management, leadership development and organizational culture analysis. It can help enterprise leaders understand talent behavior and generate useful talent knowledge, and then provide intelligence for real-time decision-making and effective personnel management.

After the talk, faculties and students discussed with the two experts respectively, which benefited the majority of teachers and students in the specific academic aspects and practical industrial application.