“After developing a stochastic and relatively complex model of a real world phenomenon,” explains Samim, “We try to analyze it using different simulation approaches.” Stochastic modeling attempts to capture uncertainty inherent in all events, which renders the practice of modeling more practical and meaningful.
Within this research framework, Samim is focused on developing new and/or more efficient simulation approaches that provide benefits from mathematically intractable stochastic models.
“What usually makes stochastic models mathematically intractable is interdependency among systems’ components,” states Samim. “Innovative and efficient simulation methods permit the incorporation of interdependency into the model.”
Stochastic Analysis has applications in economics, public policy analysis, transportation and operations management.
Samim's advisor is Professor Sheldon Ross. Samim is working on his PhD and his major is Operations Research at Department of Industrial and Systems Engineering at USC. He looks to graduate in 2008.
