Teaching at Northeastern University
IE 7215 Simulation Analysis (Fall 2018-present)
Elementary queueing models, simulation model design, simulation languages
Input data analysis and distribution fitting, model verification and validation, output
analysis and transient/steady-state response
Terminating/nonterminating systems, model experimentation and optimization
Random number/random variate generation, and variance reduction techniques
IE4510 Simulation Modeling Analysis (Fall 2018-present)
Process model design and development, validation, and experimentation for discrete-event simulation models
Topics include problem formulation, data collection and analysis, random-variable generation, model development,
scenario experimentation, statistical analysis of output, and resultant decision management.
Utilizes a major industry-standard simulation software application with animation capabilities.
Teaching at RPI
ISYE 4290/6620 Discrete-Event Simulation Modeling (Fall 2017)
Introduction to discrete-event simulation modeling and analysis techniques including; graphical simulation
modeling approaches, animation techniques, modeling large-scale and complex systems, pseudo-random number
and random variate generation, stochastic processes,
Input modeling (data collection, analysis, and
fitting distribution), output analysis (initial bias and termination bias, variance reduction techniques),
sensitivity analysis, design of experiments, interactive simulation-based decision-support systems.
ISYE 4210/6600 Design of Manufacturing Systems and Supply Chains (Spring 2016, 2017)
Dynamics of manufacturing systems and supply chains, lean manufacturing, lead time reduction in
manufacturing and service operations, advanced pull systems, concurrent design of products
and supply chains, and integration of information technology in supply chain operations.
Analysis of models and
their application to design and planning problems in manufacturing as well as service systems is emphasized.
ISYE 4140 Statistical Analysis (Fall 2014, 2015)
Review of simple and multiple regression, selection procedures, regression diagnostics, residual analysis,
stepwise regression, analysis of variance, design of experiments including factorial experiments,
analysis of ordinal data and nonparametric inference, basic time series models.
Extensive use of
statistical software. Emphasis on statistical applications to industrial engineering.
Co-teaching at Northwestern University
IMC 451 Statistics and Marketing Research (Fall 2013)
