Andrei Ruckenstein
Professor of Physics (CAS)
Research Interests:
Classical Computation, Correlated Systems, and Higher Education
My research primarily focuses on three key areas, statistical mechanics models of classical computation, strongly correlated systems, and new models for higher education. In the context of computational problems, I have worked together with my colleagues Claudio Chamon and Eduardo Mucciolo to develop a new approach to reversible classical computation by mapping a universal reversible classical logic circuit into a quantum planar vertex model that encodes the result of the computation in its ground state. In addition, I am exploring the connection between the problem of single gene transcription and classical computation. In terms of correlated systems, I am exploring models of marginal Fermi liquid behavior at Lifshitz transitions in models of correlated systems, which support the evolution from hole to electron Fermi surfaces. Finally, during my work as an University administrator I explored new models of Higher Education that address an indisputable structural issue with the current model of research-intensive universities.