Doctor of Science (D.Sc.) in Engineering Management, George Washington University, Washington DC, USA.
Master of Science (M.Sc.) in Mechanical Engineering, Johns Hopkins University, Baltimore, MD, USA.
Bachelor of Science (B.Sc.) in Mechanical Engineering, University of Puerto Rico, Mayaguez, Puerto Rico.
Martin Negrón has a doctoral degree in engineering management from George Washington University. His research explored the development of a mathematical model describing a global socio-economic conflict with the objective of defining potential outcomes of the conflict and facilitating the process of identifying possible solutions.
Martin Negrón has over twenty years of professional experience in a variety of positions including weapons acquisition, public policy, and international programs. He has publications related to the development and protection of virtual and physical infrastructure. He co-authored book chapters related to the risks of implementing e-government programs with a focus on developing countries.
Martin Negrón also co-authored a book chapter discussing the use of public-private partnerships for the protection of critical infrastructure. He currently works as an optimization engineer for the Naval Air Warfare Systems supporting the F-35 program in Washington DC.
Teaching and Research Interests:
Martin Negrón is interested in continuing research in areas of predictive models for technology implementation taking into consideration elements related to budgets, technical skills, technology cycles and the fast evolution of new missions in addition to other established conditions such as government laws and regulations.
His interest also spans in areas related to international defense agreements and collaboration and their effects on technology life cycle planning. In addition, he is interested in modeling economic, social and political conditions to understand their impact on technology implementation and the development of new technologies.
Courses Taught at HU:
Machine Learning I
Quantitative Decision Making (Current)
Risk Modeling (Current)