dst 20191210 amelsawah

Dr. Ahmed Abdelnabi Mohamed Elsawah
Assistant Professor of Statistics
Division of Science and Technology
office: T3-502-R24

Google Scholars

ResearchGate

Curriculum Vitae

Education

Postdoctoral Follow in Design of Experiments, BNU-HKBU United International College, China
PhD in Design of Experiments, Central China Normal University, China
MPhil in Order Statistics, Zagazig University, Egypt
BSc (Hons) in Mathematics and Statistics, Zagazig University, Egypt

Research Interests

Design of Experiments
Computer Experiments
Statistical Simulation
Multivariate Analysis
Order Statistics

Current Teaching

Advanced Statistics
Experimental Design
Statistics: The Art of Data

Selected Publications
  • Elsawah, A. M., 2020. Building some bridges among various experimental designs. J. Korean Statistical Society [Link]
  • Elsawah, A. M., 2019. Constructing optimal router bit life sequential experimental designs: new results with a case study. Commun Stat Simul Comput. 48 (3), 723-752.
  • Elsawah, A. M., 2019.  Designing Uniform Computer Sequential Experiments with Mixture Levels Using Lee Discrepancy. J. Systems Science and Complexity 32 (2), 681–708.
  • Elsawah, A.M., 2019. Constructing optimal projection designs. Statistics [Link]
  • Elsawah, A.M., Fang, K.T. and Deng, Y.H., 2019.  Some interesting behaviors of good lattice point sets. Commun Stat Simul Comput. [Link]
  • Elsawah, A.M., Fang, K.T. and Ke, X., 2019. New recommended designs for screening either qualitative or quantitative factors. Stat. Papers. [Link]
  • Elsawah, A.M. and Fang, K.T., 2019. A catalog of optimal foldover plans for constructing U-uniform minimum aberration four-level combined designs.  J. Applied Statistics 46 (7), 1288-1322.
  • Elsawah, A.M., Fang, K.T., He, P. and Qin, H., 2019.  Optimum Addition of Information to Computer Experiments in View of Uniformity and Orthogonality. Bulletin of the Malaysian Mathematical Sciences Society 42 (2), 803–826
  • Elsawah, A.M., Fang, K.T., He, P. and Qin, H., 2019.  Sharp lower bounds of various uniformity criteria for constructing uniform designs. Stat. Papers. [Link]
  • Elsawah, A.M., 2018. Choice of optimal second stage designs in two-stage experiments. Comput. Stat. 33(2), 933-965.
Grants and Projects
  • “Representative Points of Statistical Distributions in Statistical Inference” UIC Research Grant (CoI, 2020-2022)
  • "Answers to Some Significant Open Questions in Experimental Designs” UIC Research Grant R201912 (PI, 2019-2021)
  • “Solving Some Fundamental Problems Concerning the Construction of Designs for Experiments” UIC Research Grant R201810 (CoI, 2018-2020)
Academic and Social Service

  • Referee for various journals, including, Statistics, Statistical Papers, Engineering Reports, Statistics in Medicine, Statistics and Probability Letters, Statistical Planning and Inference, Journal of the Korean Statistical Society, Communications in Statistics - Theory and Methods, Communications in Statistics - Simulation and Computation.
  • Reviewer for Mathematical Reviews, 2016-present.
  • External Examiner for MPhil and PhD theses.
Postgraduate Opportunities

Design of experiments is becoming ubiquitous in engineering, science, industry and many real-world problems for studying complex phenomena and investigating the relationship between inputs affecting an experiment and its outputs. This technique involves two basic aspects, designing the experiment (data collection) and analyzing the experiment (data analysis). Designing the experiment is arguably the corner stone of this approach. The significant problem experimenters may face is the selection of optimal designs for their experiments, which reduce the experimental cost and provide more efficient information about the behavior of the phenomena under the experimentation.  Through theoretical justification, our team tries to provide efficient ways from different perspectives for constructing optimal designs for real-world experiments.

MPhil and PhD students are warmly welcome to join our research team and enjoy the work with us. We believe that your abilities will help our team to success more.