Eduardo Miranda

Eduardo Miranda is a Teaching Professor in the Department of Software and Societal Systems at Carnegie Mellon University, bringing extensive industry experience from roles at Ericsson (1996–2005) and Lockheed Martin (1991–1996) as a software developer, project leader, and manager. Prior to CMU, he taught as an adjunct professor in Argentina and Canada for nearly two decades.

His academic credentials include:

• Bachelor of Science in Systems Analysis from the University of Buenos Aires, Argentina
• Master of Engineering from the University of Ottawa, Canada
• Master of Science in Project Management from the University of Linköping, Sweden
• PhD in Software Engineering from the École de Technologie Supérieure – Université du Québec

Miranda's research centers on bridging agile practices with disciplined project management, specializing in visual milestone planning, paired comparisons for estimation, and contingency modeling. He has pioneered techniques like the Paired Comparisons Estimation Tool and developed frameworks for MoSCoW prioritization with quantitative validation through Monte Carlo simulations. His work integrates Petri Nets for requirements analysis and combinatorial testing for verification.

His 15 most recent publications (2010–2023) reveal a clear trajectory toward hybrid methodologies, emphasizing visual, participatory approaches to agile execution while maintaining rigorous planning foundations. Key themes include buffer management for timeboxing, recovery models for estimation failures, and lightweight process assessments using nominal group techniques.

Notable recognitions include:

• Master of Software Engineering Coach Award for Outstanding Teaching and Mentorship (2014)
• Best Industrial Paper award at IEEE System and Software Reliability Engineering Conference (1998)

As an educator, Miranda created simulation-based agile teaching tools used in CMU's MSE program, though specific student mentorship details and grant funding are not documented in available sources. His industry collaborations include the MSE/NIST seminar series on combinatorial testing, but no dedicated research lab is associated with his current work.