Sidney Ira Resnick, Cornell University

Professor Ithaca, New York sir1@cornell.edu Office: (607) 255-1210

Expert In

Data networks Data storage facilities Risk estimation Tail estimation

Bio/Research

Professor Resnick's professional interests center in applied probability and cross the boundary into statistics. Past foci include modeling questions for queues, storage facilities, extremes, data networks, risk estimation and estimation problems for tails and non-standard time series models. A recurrent theme is influence of tails, especially heavy tails where large values shock the system. Heavy tailed modeling has become increasingly important in data network modeling and finance. In network modeling, heavy tailed file sizes are the explanation for observed long range dependence in network traffic and in finance, extreme value and heavy tailed methods offer methods for calculating value at risk and probabilities of rare events in multivariate settings. The analytic basis for heavy tailed modeling is the theory of regularly varying functions; the probabilistic basis for modeling turns out to rest on stochastic point processes.

Tail estimation problems generally require estimating beyond the range of the data and require a good understanding of probability, stochastic processes and statistics. Likewise, good data network research utilizes applied probability, statistics, simulation and optimization.

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