Research intrests

Stochastic processes, Fractional calculus, Time series, Statistics, Stochastic calculus.

    (8) F. Sabzikar, D. Surgailis: Invariance principles for tempered fractionally integrated processes, Stochastic Processes and their Applications (2017).
    (7) F. Sabzikar, D. Surgailis: Tempered fractional Brownian and stable motions of second kind, Statistics and Probability Letters, Vol. 132 (2018) pp. 17–27.
    (6) F. Sabzikar: Tempered Hermite process, Modern Stochastics: Theory and Applications, Vol. 2 (2015) pp. 327–341.
    (5) M. M. Meerschaert and F. Sabzikar: Tempered Fractional Stable Motion, Journal of Theoretical Probability, Vol. 29 (2016) pp. 681-706.
    (4) M. M. Meerschaert, F. Sabzikar, M. S. Phanikumar, and A. Zeleke: Tempered Fractional Time Series Model for Turbulence in Geophysical Flows, Journal of Statistical Mechanics: Theory and Experiment, Vol. 2014 p. P09023 (13 pp.)
    (3) F. Sabzikar, M.M. Meerschaert, and J. Chen: Tempered Fractional Calculus, Journal of Computational Physics, Vol. 293 (2015) pp. 14–28, Special Issue on Fractional Partial Differential Equations.
    (2) M.M. Meerschaert and F. Sabzikar: Stochastic integration for tempered fractional Brownian motion, Stochastic Processes and their Applications, Vol. 124 (2014), No. 7, pp. 2363–2387.
    (1) M.M. Meerschaert and Farzad Sabzikar, Tempered Fractional Brownian Motion, Statistics and Probability Letters, Vol. 83 (2013), No. 10, pp. 2269–2275.
  • STAT 432, Fall 2015
  • STAT 447, Spring 2016
  • I am an Assistant Professor in the Department of Statistics at Iowa State University. I joined Iowa State University in August, 2015 after finishing my position as a visiting assistant professor in the Department of Statistics and Probability at Michigan State University. I received my PhD in statistics under the supervision of Mark Meerschaert in May 2014. My main research is in the area of probability, fractional calculus and time series. More specifically, I am interested in the application fiof fractional calculus to stochastic analysis of continuous stochastic process (Gaussian, stable), random fields and time series.
  • CV