After completing his MS in astronomy and space science at Cornell, where he did field work at the Arecibo Ionosphere Observatory, he moved to the University of California at Berkeley where he began a graduate program in Latin American history.

[1] Concluding that he wanted a career in the area of technology and policy, and to continue his technical education, he became one of the first two PhD students to join Henry Booker's newly established Department of Applied Electrophysics (now Electrical and Computer Engineering) at the University of California, San Diego.

[2] While completing the experimental work for his PhD, he arranged a course on computers and programming for a group of underserved high school students who the neighborhood youth corps placed on campus for the summer.

[4] Educated in applied physics, a field in which no result is published without a characterization of associated uncertainty, Morgan was dismayed to find that in the early 1970s this was not the norm in quantitative policy analysis.

Through his work, initially on the health effects of coal-fired power plants[5] and then on a variety of other topics in risk assessment,[6] Morgan developed and demonstrated methods for characterizing and incorporating uncertainty in quantitative policy analysis.

Working with economist Lester B. Lave and psychologist Baruch Fischhoff and a group of PhD students, they developed and demonstrated the mental model approach to risk communication.

[16][17] Throughout his tenure at Carnegie Mellon, Morgan has built on these and other research experiences to evolve a graduate core course in EPP, which is now supported by his book Theory and Practice in Policy Analysis: Including Applications in Science and Technology (Cambridge, 2017).