Alberto Espinosa Professor Information Technology & Analytics
- Bio
- 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. Explore all AU Faculty Experts in our media guide.
Teaching
Spring 2025
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ITEC-621 Predictive Analytics
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ITEC-621 Predictive Analytics