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Vasant Dhar, New York University
Title: Machine Learning in the Era of "Big Data"
Abstract: "What information consumes is rather obvious: it consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention, and a need to allocate that attention efficiently among the overabundance of information sources that might consume it." Herbert Simon.
Machine learning, a branch of artificial intelligence, is about algorithms that allow computers to evolve behaviors or discover models/theories based on empirical data. In this talk, I argue that in the rapidly emerging age of “big data,” machine learning is playing an increasingly important role in uncovering interesting patterns hidden in troves of data through its ability to formulate and test novel hypotheses intelligently and thus is potentially transformative to both how business decisions are made and how business research will be conducted. Entities that collect and learn from the vast data trails we leave behind are in a very advantageous position toform useful theories and models about human behavior. Estimates suggest that there were be a need for over a million “data savvy” managers in the next decade, and roughly quarter of a million positions that require “deepanalytical talent.” How should universities position themselves for this future?
Bio: Vasant Dhar is Professor of Information Systems at New York University’s Stern School of Business. He teaches courses in data mining and knowledge systems, and financial information systems. He has been with NYU Stern for more than 20 years. His primary research focus is on data mining in the financial industry, specifically, the use of artificial intelligence and statistical methods for systematic investment decision-making. Several of his automated trading strategies are in use on Wall Street. He has been published in numerous journals including Information Systems Research, Data Mining and Knowledge Discovery, and IEEE Transactions on Neural Networks. Outside of academia, he has worked at Morgan Stanley and Company in the mid 1990s and at the Artificial Intelligence Laboratory of the Microelectronics Computer Corporation in Austin, Texas in the late 1980s. He received his Bachelor of Technology in chemical engineering from the Indian Institute of Technology in Delhi, and his M.A. and Ph.D. in artificial intelligence from the University of Pittsburgh.
Jamshid Vayghan, IBM
Bio: Dr. Jamshid Vayghan is an IBM Distinguished Engineer, Director and Chief Technology Officer (CTO) for IBM's internal CIO organization. He is responsible for technical and information strategy for IBM's global sales transformation and its alignment with the business strategy. He is a well respected expert in business transformation, enterprise information management, enterprise architecture, and data mining. He has a diverse career as executive, engineer, researcher, IT practitioner, member of board of directors, and teacher working in 3 continents. He holds a Bachelor of Engineering degree in Chemical Engineering, Master of Science and Ph.D. degrees in Computer Science specialized in data mining and Artificial Intelligence.
Michael Zhang, Hong Kong University of Science and Technology
Bio: Michael Zhang is an Assistant Professor of Information Systems at Hong Kong University of Science and Technology. He teaches courses in e-commerce and entrepreneurship. His research interests are on issues related to creation, dissemination and processing of information in business and management contexts. His works study pricing of information goods, online word-of-mouth, online advertising, incentives of creation in open content projects, and use of information in financial markets. His research has appeared in the American Economic Review, Management Science, Journal of Marketing, and other academic journals. Before joining the academia, he worked as a consultant for an investment bank, and as an international marketing manager for a high-tech company. He holds a US patent, and started a social networking company. He currently serves as an Associate Editor for Information Systems Research and is also on the editorial boards of Production and Operations Management and Electronic Commerce Research and Applications. He holds a PhD in Management from MIT Sloan School of Management, an MSc in Management, a BE in Computer Science and a BA in English from Tsinghua University.
