12/05/2017
We are back!!!! Today’s Faculty Friday, is someone special to our department, he has contributed a lot to the department and is stepping down as Department Chair, Neil Murray, Ph.D.
A Little about Prof Murrary:
Prof. Murray is the Chair of the Department of Computer Science at SUNY Albany. He received his PhD from Syracuse University. He is a noted scholar and dedicated teacher, Neil epitomizes the notion of service leadership. He lead the computer Science department for more than a dozen years as chair, guiding us through challenging times along the way, and setting the stage for our continued success, he had been a mentor and a great source of support for many.
Fun Fact:
Prof. Murray has been a faculty in the department of Computer Science for 35 years, served as the Department Chair totaling 12 years. This includes his service for the past 5 years.
Research:
My main research interest is in automated deduction; this includes both theoretical and experimental studies. The development of inference techniques for negation normal form (NNF) formulas and related tableau-based techniques is central. These techniques could lead to tangible progress not only for automatic theorem provers, but for other systems; examples are deductive databases, systems based on logic programming, and other AI systems with an inferencing component such as deduction-based program synthesis and non-monotonic reasoning systems.
NNF-based techniques are also promising for producing a representation of the models of a (propositional) formula. This capability is important for many more practical applications than was previously thought to be the case. Planning is one example, and fault-diagnosis is another. These issues are closely related to recent developments in “Decomposable Negation Normal Form (DNNF)” (Darwiche, J.ACM (48, 4), July 2001), and to our paper “Efficient Query Processing with Reduced Implicate Tries.” To appear, Journal of Automated Reasoning.
Recently, longtime co-author Erik Rosenthal and I have partnered with Sandeep Shulka of Virginia Tech. In the development of tools for synthesis of provably correct deter- ministic multi-threaded code for safety-critical applications. These tools will be based on a modeling formalism called polychronous data flow, which captures specifications for multi-rate reactive concurrent embedded systems. Prime implicates, often used in, for example, abductive reasoning and data base query optimization, are also useful in the analysis of polychronous specifications. An important component of the plan is a new algorithm (developed by Ph.D. student Matusiewicz, myself, and Rosenthal) that produces the prime implicate trie — a tree whose branches are labeled with the prime implicates — of a logical formula. The algorithm is being extended to take advantage of several properties that are especially well-suited for this application.
Personal Page: Personal Page: http://www.cs.albany.edu/~nvm/