Keran Zhao
Assistant Professor
Department Supply Chain & Information Systems
Office Address 465 Business Building
Email Address
krzhao@psu.edu
Keran Zhao
Assistant Professor
Department Supply Chain & Information Systems
Office Address 465 Business Building
Email Address
krzhao@psu.edu
Keran Zhao is an Assistant Professor in the Department of Supply Chain and Information Systems at the Smeal College of Business, Pennsylvania State University. Prior to joining the Smeal College of Business, he was an Assistant Professor at the Bauer College of Business, University of Houston. Dr. Zhao's research interests lie in the area of digital platform design and artificial intelligence. His research investigates the design and user behavior of online live streaming and healthcare communities, using machine/deep learning and econometrics approaches.
Expertise
Live Streaming, Artificial Intelligence, Design of Digital Platforms, Blockchain and NFT, Healthcare Informatics
Education
Ph.D., Management of Information Systems, University of Illinois at Chicago, 2021
M.S., Information Science, University of Pittsburgh, 2016
Courses Taught
MIS 441 – Bus Intelligence (3)
Application of Information Technology based methods and tools to analyze business data and support decision making. MIS 441 Business Intelligence for Decision Making (3) Business intelligence encompasses the IT tools for exploring, analyzing, integrating, and reporting business data for fact-based, intelligent decision making. This course primarily investigates methods and tools for exploring and analyzing large amounts of business data also called "Big Data." Learning methods emphasize active learning in the application of methods and tools to real data and the presentation of the results. Students will be exposed to a variety of methods for analyzing both structured and unstructured data and they will work with business data sets to understand the value that can be extracted from large data sets. They will also learn how to classify and associate data to discover business rules that can be used to support decision making. The course will also cover methods to analyze social media information and about tools that can facilitate such analysis and discovery. Again they will get a chance to work with data from real social networks to gain an appreciation of how value can be obtained from such networks. Finally, they will learn about techniques for visualizing, presenting and communicating information in a useful way, e.g. through dashboards and with other technologies on various platforms.