J. Alberto Espinosa, Ph.D.

Bio

Prof. Espinosa is a Full Professor of Information Technology and Analytics (IT&A) at the Kogod School of Business at American University. He holds Ph.D. and Master of Science degrees in Information Systems from the Tepper School of Business at Carnegie Mellon University, a Masters degree in Business Administration from Texas Tech University; and a Mechanical Engineering degree from Pontificia Universidad Catolica del Peru. He has won numerous teaching, resarch and service awards, including the 2025 American University Outstanding Teaching in Full-Time Appointment Award, 2022 Kogod Graduate Professor of the Year Award, and 2021 American University Grean Teacher Award. He is the architect of Kogod's MS Analytics programs, both campus and online, and of the undergraduate specializations in Information Technology and Systems and in Business Analytics. He is also the curriculum architect for the IT&A programs and specializations. He has writen a teaching book on Predictive Analytics and Machine Learning for Managers and co-authored two other books, one on work coordination across time zones and a 2-volume book on big data and analytics for service delivery. He has published over 70 peer-reviewed articles, including refereed journal articles, conference proceedings, books and book chapters, and has over 7,765 Google Scholar citations. His research focuses on coordination and performance in technical projects across global boundaries, particularly distance and time separation (e.g. time zones, shiftwork, telework). More recently, he has been developing methods to represent and study team knowledge quantitatively and visually using social network analytics to depict and measure knowledge relationships. Prof. Espinosa employs a multiple method approach in his research, but his primary focus is on field studies with technical organizations and organizations collaborating through collaboration technologies. His work has been published in leading scholarly journals, including: Management Science; Organization Science; Information Systems Research; the Journal of Management Information Systems; IEEE Transactions on Software Engineering, IEEE Transactions on Engineering Management; Communications of the ACM; Human Factors, Information, Technology and People; and Software Process: Improvement and Practice. His work has also been featured in leading academic conference proceedings. He teaches predictive analytics, social and organizational network analytics, R programming for analytics, information technology foundations, business process analysis, and programming for online business applications. He also has several years of working experience, first as a design engineer and later as a senior manager and VP and CFO with international organizations directly supporting, supervising and formulating policy for finance and global IT and data management and analysis functions, where he designed and developed a number of software applications to support geographically distributed work.