Applied Probability

Applied Probability

Faculty Research Interests

applied probability, computational finance, MCMC, queueing theory, rare-event analysis, simulation methodology, and risk theory

quantitative finance, asset pricing, derivatives, risk measures, real estate, applied probability, empirical finance

applied probability, stochastic systems, and heavy-tailed phenomena, including applications to the analysis of ranking algorithms, random graphs and queueing theory

applied probability, queueing systems, stochastic networks, stochastic-process limits, performance approximations and numerical transform inversion with applications to communications, computer, production and service systems

stochastic systems and applied probability, resource control in stochastic networks, financial systemic risk, risk hedging in production systems, healthcare operations, hospital resource planning, supply chain optimization

discrete Optimization, market design, scheduling, applied probability

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