Abolfazl Saghafi PhD

Abolfazl Saghafi, PhD

Abolfazl Saghafi PhD

Program Director for the Data Science Program

Assistant Professor of Statistics


PhD, Statistics, University of South Florida

PhD Applied Mathematics, Iran University of Science & Technology

MSc, Mathematical Statistics, Shahid Beheshti University

BSc, Statistics, Azad University

Research Interests

  • Machine Learning
  • Time Series Classification
  • Parametric/Non-Parametric/Bayesian Analysis and Modeling
  • Extreme Value Probability Distributions


Dr. Saghafi earned his PhD in Applied Mathematics from Iran University of Science and Technology where he specialized on Divergence Measures, Entropy, Weibull and Order k Poisson Models. Further, he earned his 2nd PhD in Statistics from University of South Florida, specializing on machine learning, Time Series Classification and BIG data analytics. In 2011, he expounded upon a decades-old limitation by finding a closed form solution for an open problem since 1983 on the Poisson distributions of order k. Dr. Saghafi’s endeavor in applied mathematics and statistics is incredibly useful for solving practical, real-world problems, reflected by the diversity of journals that have accepted his work for publication and by the collaboration with researchers from many disciplines.  For more information, see abolfazlsaghafi.info.

Selected Scholarly Activity

A. Saghafi, S. Jazayeri, S. Esmaeili, C.P. Tsokos, Systems and Methods for Detecting Buried Objects, Patent issued with USPTO on Jan 8, 2019 with number US 10175350 B1.

A. Saghafi, S. Jazayeri, S. Esmaeili, C.P. Tsokos, Real-time object detection using Power Spectral Density of Ground Penetrating Radar Data, Structural Control and Health Monitoring, 26(6) (2019).

S. Jazayeri, A. Saghafi, S. Esmaeili, C.P. Tsokos, Automatic object detection using Dynamic Time Warping on Ground Penetrating Radar signals, Expert Systems with Applications. 122(15) (2019) 102-107.

X. Wang, C.P. Tsokos, A. Saghafi, Improved Parameter Estimation of Time Dependent Kernel Density by using Artificial Neural Networks, Journal of Finance and Data Science. 4(3) (2018) 172-182.

Contact Information

Office location: McNeil Science and Technology Center, Room 209
Mailing address: Box #64
University of Sciences
600 South 43rd Street
Philadelphia, PA 19104-4495
Office Phone: 215-596-7240

a [dot] saghafi [at] usciences [dot] edu