Roman Krzysztofowicz headshot
RK

Roman Krzysztofowicz

Professor
Unit: School of Engineering and Applied Science
Department: Department of Systems and Information Engineering
Office location and address
Olsson Hall, Room 113C
151 Engineer's Way
Charlottesville, Virginia 22903
Biography

Dr. Krzysztofowicz joined the faculty of the University of Virginia in 1982, after he had held faculty posts at the University of Arizona and the Massachusetts Institute of Technology. He directed the Systems Engineering graduate programs, and was a founding associate director of the Center for Risk Management. An author/coauthor of over 115 archival articles published in some 25 journals, 15 books, and 4 encyclopedias, he served as editor-in-chief of the Journal of Hydrology (1996–2007), and as associate editor of Stochastic Hydrology and Hydraulics, Stochastic Environmental Research and Risk Assessment, and Journal of Applied Meteorology.

EN-Improved statistical post-processing with Bayesian processor of ensemble (BPE)
Source: U.S. DOC - Nat. Oceanic & Atmospheric Admin. (Noaa
May 01, 2016 – April 30, 2017
EN-SE Improved Statistical Post-Processing with Bayesian Processor of Ensemble (BPE)
Source: U.S. DOC - Nat. Oceanic & Atmospheric Admin. (Noaa
February 16, 2015 – February 15, 2016
EN-SE New Statistical Techniques for Probabilistic Weather Forecasting
Source: U.S. NSF - Directorate For Geosciences
May 01, 2007 – April 30, 2013
SYS 3060: Stochastic Decision Models
Credits: 3
Introduction to mathematical modeling of forecasts and decisions under uncertainty using principles of statistical decision theory; judgmental and Bayesian techniques for probabilistic forecasting; forecast verification methods; static and sequential decision models for quality control, inventory control, queue management, hazard warnings; and economic, investment, and weather-sensitive decisions. Prerequisite: APMA 3100 and 3120, or instructor permission.
APMA 3100: Probability
Credits: 3
A calculus-based introduction to probability theory and its applications in engineering and applied science. Includes counting techniques, conditional probability, independence, discrete and continuous random variables, probability distribution functions, expected value and variance, joint distributions, covariance, correlation, the Central Limit theorem, the Poisson process, an introduction to statistical inference. Prerequisite: APMA 2120 or equivalent.
APMA 3110: Applied Statistics and Probability
Credits: 3
Examines variability and its impact on decision-making. Introduces students to basic concepts of probability, such as random variables, probability distribution functions, and the central limit theorem. Based on this foundation, the course then emphasizes applied statistics covering topics such as descriptive statistics, statistical inference, confidence intervals, hypothesis testing, correlation, regression modeling, statistical quality control. Students cannot receive credit for both this course and APMA 3120. Prerequisite: APMA 2120 or equivalent.
SYS 4581: Selected Topics in Systems Engineering
Credits: 1–3
Detailed study of a selected topic determined by the current interest of faculty and students. Offered as required. Prerequisite: As specified for each offering.
SYS 6097: Graduate Teaching Instruction
Credits: 1–12
For master's students.
SYS 6581: Selected Topics in Systems Engineering
Credits: 1–3
Detailed study of a selected topic, determined by the current interest of faculty and students. Offered as required.
SYS 7001: System and Decision Sciences
Credits: 3
Introduction to system and decision science with focus on theoretical foundations and mathematical modeling in four areas: systems (mathematical structures, coupling, decomposition, simulation, control), human inputs (principles from measurement theory and cognitive psychology, subjective probability theory, utility theory), decisions under uncertainty (Bayesian processing of information, Bayes decision procedures, value of information), and decisions with multiple objectives (wholistic ranking, dominance analysis, multiattribute utility theory). Prerequisite: Mathematical analysis and probability theory at an undergraduate level; admission to the graduate program.
SYS 7005: Stochastic Systems II
Credits: 3
Provides a non-measure theoretic treatment of advanced topics in the theory of stochastic processes, focusing particularly on denumerable Markov processes in continuous time and renewal processes. The principal objective is to convey a deep understanding of the main results and their proofs, sufficient to allow students to make theoretical contributions to engineering research. Prerequisite: SYS 6005 or equivalent.
SYS 7075: Bayesian Forecast-Decision Theory
Credits: 3
Presents the Bayesian theory of forecasting and decision making; judgmental and statistical forecasting, deterministic and probabilistic forecasting, post-processors of forecasts; sufficient comparisons of forecasters, verification of forecasts, combining forecasts; optimal and suboptimal decision procedures using forecasts including static decision models, sequential decision models, stopping-control models; economic value of forecasts; communication of forecasts; and the design and evaluation of a total forecast-decision system. Prerequisite: SYS 6005, 6014, or equivalent.
SYS 8995: Supervised Project Research
Credits: 1–12
Formal record of student commitment to project research for Master of Engineering degree under the guidance of a faculty advisor. Registration may be repeated as necessary.
SYS 8999: Non-Topical Research, Masters
Credits: 1–12
Formal record of student commitment to master's research under the guidance of a faculty advisor. Registration may be repeated as necessary.
SYS 9997: Graduate Teaching Instruction
Credits: 1–12
For doctoral students.
SYS 9999: Dissertation
Credits: 1–12
For doctoral students.