- Prof. Espinosa is a Full Professor of Information Technology and Analytics at Kogod School of Business, 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, Peru. He is the architect of Kogod's MS Analytics degree, both campus and online. He is also the curriculum architect for all information systems and technology undergraduate specializations. He has co-authored two books, one on work coordination across time zones and another on big data and analytics for service delivery. His research focusses on coordination and performance in global technical projects across global boundaries, particularly distance and time separation (e.g. time zones). More recently, he has been developing methods to represent team knowledge quantitatively and visually using social network analytics. Prof. Espinosa employs a multiple method approach in his research, but his primary focus is on field studies with technical organizations. 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, information technology foundations, business process analysis, and programming for business applications and analytics. He also has several years of working experience, first as a design engineer and later as a senior manager and VP with international organizations directly supporting, supervising and formulating policy for finance and global IT functions, where he designed and developed a number of software applications to support geographically distributed work.
- See Also
- Web Site
- I'm Working While They're Sleeping: Time Zone Separation Challenges and Solutions
- Obtaining Value from Big Data for Service Systems Vol.1
- Obtaining Value from Big Data for Service Systems Vol.2
- For the Media
- To request an interview for a news story, call AU Communications at 202-885-5950 or submit a request.
ITEC-621 Predictive Analytics
ITEC-621 Predictive Analytics
Area of Expertise
Global and geographically distributed teams; coordination and collaboration across global boundaries; work across time zones; coordination in large-scale technical collaboration, business analysis, and databases
J. Alberto Espinosa researches coordination and performance in technical collaborative projects. His work studies the challenges, best practices, and most effective processes to coordinate technical work in complex work environments, such as across global boundaries; geographic distance and time zones; and large-scale, multifunctional collaboration. He employs multiple methods in his research, including theory, lab experiments, qualitative studies, and survey methods, but his primary focus is on field studies in technical organizations. His research has been published in leading scholarly journals, including Management Science; Organization Science; Information Systems Research; Journal of Management Information Systems; IEEE Transactions of Engineering Management; Communications of the ACM; Information, Technology, and People; and Software Process Improvement and Practice. His work has also been published in book chapters and leading academic conference proceedings. A frequent presenter at academic conferences, Espinosa has several years of working experience as a design engineer and senior manager with international organizations.