Dr. Xiao-Ping Zhang
Dr. Xiao-Ping Zhang
Fellow of IEEE, EIC, CAE
Professor
Department of Electrical, Computer and Biomedical Engineering
Ryerson University Signal Processing Path to Nobel Prize in Economics – Risk, Correlation, Causality and Predictive Analytics in Big Data
Monday 2/21, 8:00-9:00pm
Dr. Xiao-Ping Zhang
Fellow of IEEE, EIC, CAE
Professor
Department of Electrical, Computer and Biomedical Engineering
Ryerson University Signal Processing Path to Nobel Prize in Economics – Risk, Correlation, Causality and Predictive Analytics in Big Data
Monday 2/21, 8:00-9:00pm
Economic data and financial markets are intriguing to researchers working on big data and quantitative models. With rapid growth and increasing access to data in digital form, finance, economics, and marketing data are poised to become one of the most important and tangible big data applications, owing not only to the relative clean organization and structure of the data but also to clear application objectives and market demands. However, data related economic and social science studies often have different viewpoints from signal processing (SP) and artificial intelligence (AI).
This talk intends to introduce some foundational concepts in finance/economics/marketing research, from signal and data processing point of view. Some of these ideas led to Nobel Prize in Economics. We explain the different focuses between economic and social science data analysis and physical signal processing, such as co-integration and causality analysis. For example, in most physical systems using signal processing and machine learning, the causality (input/output) relationship is often known and taken for granted, but it is generally not obvious/unknown in social and economic sciences. It is critical to discriminate causalities from spurious correlations in data. We illustrate a marketing dynamic response model that uses signal processing tools to identify and catch fleeting business opportunities. We also introduce the concept of predictive analytics from probabilistic point of view. We hope to inspire signal processing researchers to broaden their knowledge beyond their current areas of expertise and grasp some basics concepts and evaluation criteria in economics and social science fields.
This talk intends to introduce some foundational concepts in finance/economics/marketing research, from signal and data processing point of view. Some of these ideas led to Nobel Prize in Economics. We explain the different focuses between economic and social science data analysis and physical signal processing, such as co-integration and causality analysis. For example, in most physical systems using signal processing and machine learning, the causality (input/output) relationship is often known and taken for granted, but it is generally not obvious/unknown in social and economic sciences. It is critical to discriminate causalities from spurious correlations in data. We illustrate a marketing dynamic response model that uses signal processing tools to identify and catch fleeting business opportunities. We also introduce the concept of predictive analytics from probabilistic point of view. We hope to inspire signal processing researchers to broaden their knowledge beyond their current areas of expertise and grasp some basics concepts and evaluation criteria in economics and social science fields.
Biography
Xiao-Ping (Steven) Zhang received the B.S. and Ph.D. degrees from Tsinghua University, in 1992 and 1996, respectively, all in electronic engineering. He holds an MBA in Finance and Economics with Honors from the University of Chicago Booth School of Business. He is now Professor and Director of Communication and Signal Processing Applications Laboratory (CASPAL), with the Department of Electrical and Computer Engineering, Ryerson University. He has served as Program Director of Graduate Studies. He is cross-appointed to the Finance Department at the Ted Rogers School of Management at Ryerson University. He has been a Visiting Scientist at Research Laboratory of Electronics (RLE), Massachusetts Institute of Technology. He is a frequent consultant for biotech companies and investment firms. His research interests include statistical signal processing and big data analytics, multimedia analysis, sensor networks and IoT, machine learning/AI, and applications in finance, economics, and marketing.
Dr. Zhang is Fellow of the Canadian Academy of Engineering, Fellow of the Engineering Institute of Canada, Fellow of the IEEE, a registered Professional Engineer in Ontario, Canada, and a member of Beta Gamma Sigma Honor Society. He is the general Co-Chair for the IEEE International Conference on Acoustics, Speech, and Signal Processing, 2021. He is the general co-chair for 2017 GlobalSIP Symposium on Signal and Information Processing for Finance and Business, and the general co-chair for 2019 GlobalSIP Symposium on Signal, Information Processing and AI for Finance and Business. He was an elected Member of the ICME steering committee. He is the General Chair for the IEEE International Workshop on Multimedia Signal Processing, 2015. He is a Senior Area Editor for the IEEE TRANSACTIONS ON IMAGE PROCESSING. He was a Senior Area Editor the IEEE TRANSACTIONS ON SIGNAL PROCESSING and an Associate Editor for the IEEE TRANSACTIONS ON IMAGE PROCESSING, the IEEE TRANSACTIONS ON MULTIMEDIA, the IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, the IEEE TRANSACTIONS ON SIGNAL PROCESSING, and the IEEE SIGNAL PROCESSING LETTERS. He is Editor-in-Chief for the IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING. He is Chair for Image, Video, and Multidimensional Signal Processing Technical Committee (IVMSP TC) of IEEE Signal Processing Society. He received 2020 Sarwan Sahota Ryerson Distinguished Scholar Award – the Ryerson University highest honor for scholarly, research and creative achievements. He is selected as an IEEE Signal Processing Society Distinguished Lecturer for the term from January 2020 to December 2021, and an IEEE Circuits and Systems Society Distinguished Lecturer for the term 2021 to 2022.
Dr. Zhang is Fellow of the Canadian Academy of Engineering, Fellow of the Engineering Institute of Canada, Fellow of the IEEE, a registered Professional Engineer in Ontario, Canada, and a member of Beta Gamma Sigma Honor Society. He is the general Co-Chair for the IEEE International Conference on Acoustics, Speech, and Signal Processing, 2021. He is the general co-chair for 2017 GlobalSIP Symposium on Signal and Information Processing for Finance and Business, and the general co-chair for 2019 GlobalSIP Symposium on Signal, Information Processing and AI for Finance and Business. He was an elected Member of the ICME steering committee. He is the General Chair for the IEEE International Workshop on Multimedia Signal Processing, 2015. He is a Senior Area Editor for the IEEE TRANSACTIONS ON IMAGE PROCESSING. He was a Senior Area Editor the IEEE TRANSACTIONS ON SIGNAL PROCESSING and an Associate Editor for the IEEE TRANSACTIONS ON IMAGE PROCESSING, the IEEE TRANSACTIONS ON MULTIMEDIA, the IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, the IEEE TRANSACTIONS ON SIGNAL PROCESSING, and the IEEE SIGNAL PROCESSING LETTERS. He is Editor-in-Chief for the IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING. He is Chair for Image, Video, and Multidimensional Signal Processing Technical Committee (IVMSP TC) of IEEE Signal Processing Society. He received 2020 Sarwan Sahota Ryerson Distinguished Scholar Award – the Ryerson University highest honor for scholarly, research and creative achievements. He is selected as an IEEE Signal Processing Society Distinguished Lecturer for the term from January 2020 to December 2021, and an IEEE Circuits and Systems Society Distinguished Lecturer for the term 2021 to 2022.
