For DOE-Nevada, Paul Black is managing efforts related to long term stewardship for the low-level waste disposal sites. Neptune is building a decision-based system for exploring and understanding the long term consequences of disposal at the Nevada Test Site low-level waste facilities. These decision models include management options ranging from closure and disposal to institutional control, to probabilistic environmental and risk modeling, to building cost models that allows optimization across the management options. It is anticipated that this work will lead to these disposal sites being identified as effective national disposal facilities for low-level radioactive waste.
Notable advances that he has been instrumental in developing include
insertion of Bayesian decision analytic methods for sample design to
support screening assessment and risk assessment site characterization
decisions, and elicitation training applied to problems at the Nevada Test
Site for which Dr. Black uses facets of Bayesian statistical decision theory.
Dr. Black has worked at a number of environmentally sensitive sites during his
tenure at Neptune and Company, and worked on several national environmental
studies while working for ICF International. He has extensive experience in
the environmental arena that covers a broad range of decision analysis,
statistics, quality assurance, and public involvement applications. Dr. Black's
previous work has included basic research into the foundations of probability
theory and decision analysis, in conjunction with the development of a number
of computer-based decision aids and expert systems that he developed while
working at Decision Science Consortium and in the U.K. His academic training
at Carnegie Mellon University involved research into foundations of probability
theory and competing theories of uncertainty which has resulted in new developments
in random set theory that have potentially broad implications for decision theoretic
extensions to standard Bayesian analysis. Dr. Black developed computer algorithms
that significantly increase the chance of success for decision theories based on
random sets and sets of utility functions. While at Carnegie Mellon, Dr. Black also
participated in development of computer programs to facilitate elicitation of expert
opinion to support Bayesian normal linear models. Dr. Black has continued this line
of research through his professional career. At Neptune and Company Dr. Black has
adapted these models to support environmental decision making. Dr. Black continues
to work on basic research issues in probability theory and decision theory, while
maintaining a focus on application of new developments, and he continues to promote
decision theoretic methods for solving environmental problems.
Last modified: 28 May 2002