Department of Physics
Office: Science & Research 1, 629D
Contact: firstname.lastname@example.org - (713) 743-9344
Education: Ph.D., University of Maryland at College Park, Physics
B.S., University of Texas at Austin, Physics and Mathematics
Google Scholar Profile
Dr. Greg Morrison holds a Ph.D. in Physics from the University of Maryland with a focus on biophysics and statistical mechanics, did postdoctoral work at Harvard University focused on information theory and biological networks. He was previously an assistant professor at the IMT School for Advanced Studies in Lucca, Italy, studying complex systems applied to a variety of problems.
Morrison's research has spanned two broad, but fairly distinct, fields:
- The investigation of problems in single molecule biophysics, using the theoretical approaches of statistical physics, and
- The study of interconnected meso- or macroscopic systems using the methods of network theory.
His research as a graduate student focused primarily on the theoretical modeling of biophysical systems, including confinement effects for homopolymers, the behavior of self-avoiding chains under tension, and analytically tractable models for two-state systems. This modeling is essential for understanding the underlying physics of many biologically relevant processes, as well as the design of novel experimental systems.
Working at Harvard greatly expanded his research interests as well as the approaches in problem solving, with a primary focus evolving into the study of complex networks with applications for biological and sociological systems, and information-theoretic problems applied to chemical systems. His research on complex networks expanded further at IMT Lucca to work on the dynamics of global innovation networks using patent data, corporate ownership networks, and national input-output systems.
His broad experiences in solving diverse problems will be combined at UH to describe biologically relevant systems on multiple scales and in many different contexts, with particular interests in confined biomolecular systems with applications for sequencing technologies, analytical models for the structure and dynamics of molecules with numerous specific interactions, and identifying meaningful structural elements of and differences between designed and emergent complex systems.
American Physical Society
Network Science Society