Taysseer Sharaf, PhD.

Assistant Professor of Statistics

TAYSSEER SHARAF
 

I earned PhD in Statistics from University of South Florida, Tampa, FL in 2015; a master's degree from University of South Florida in 2012; a BSc. in Computer Science and Statistics from Alexandria University, Alexandria, EGYPT in 2005.


In Fall 2015 I joined the Department of Mathematics and Statistics at Slippery Rock University, PA as an assistant Professor for one academic year till I joined the department of Mathematics and Statistics at University of Michigan-Dearborn in Fall 2016.

My research interest spans the area of statistical learning, mainly developing statisticals methods using artificial intelligence such as the use of Bayesian statistics in improving the learning algorithms of artificial neural networks

Teaching.

UNIVERSITY OF MICHIGAN DEARBORN

Fall 2019

STAT 325-001: Applied Statistics I
STAT 305-001: Introduction to Data Science

Winter 2019

STAT 325-001: Applied Statistics I
STAT 440-001: Design and Analysis of Experiments

Fall 2018

STAT 263-001: Introduction to Statistics
STAT 325-001: Applied Statistics I
STAT 305-001: Introduction to Data Science

Summer 2018

STAT 301-002: Bio-Statistics

Winter 2018

STAT 325-001: Applied Statistics I
STAT 440-001: Design and Analysis of Experiments

Fall 2017

STAT 263-001: Introduction to Statistics
STAT 305-001: Introduction to Data Science
STAT 490-001: Nonparametric Statistics

Winter 2017

STAT 325-001: Applied Statistics I
STAT 305-001: Introduction to Data Science
STAT 440-001: Design and Analysis of Experiments

Fall 2016

STAT 325-001: Applied Statistics I
STAT 263-001: Introduction to Statistics

SLIPPERY ROCK UNIVERSITY

Summer 2016

STAT 152: Elementary Statistics I

Spring 2016

STAT 152: Elementary Statistics I
STAT 254: Nonparametric Statistics
MATH 113: Math as Liberal Arts

Fall 2015

STAT 152: Elementary Statistics I
MATH 122: Finite Mathematics
MATH 113: Math as Liberal Arts

Research.

RESEARCH INTERESTS:

My research interests span the areas of Statistical Learning, BIG DATA, data mining. My current research is focused on artificial neural networks ANN, Time series, Bayesian analysis and Survival analysis. During my senior year as an undergraduate, I visually perceived the merging of statistical methods and computer sciences would be a potent implement for analyzing and interpreting data. Now a days, with the rapid development of data storage and computing technology, high dimensional data are frequently collected in a diversity of fields, such as cancer research, global warming, bio-medical engineering and finance, among others. The demand of an adjacent method to the conventional statistical methodology is of great importance, to be able to mine, interpret and discover patterns within the high dimensional data sets.
My primary research focuses on adapting artificial neural networks ANN and amending it to be capable to perform statistical modeling. ANN is one of the best semi-parametric tools in modeling nonlinear functions.

PUBLICATIONS:

  1. Sharaf, T., Williams, T., Chehade, A., and Pokhrel, K., "BLNN: An R Package for Training Neural Networks Using Bayesian Inference". SoftwareX, Elsevier, 2020, Accepted, In press

  2. Pokhrel, K. ,Sharaf, T., Bhandari, P., Ghimire, D., "Farm Exit among Smallholder Farmers of Nepal: A Bayesian Logistic Regression Models Approach",Agricultural Research, Springer, 2020,Accepted, In press

  3. Alghamdi, T., Elgazzar, K., and Sharaf, T., "Spatiotemporal Prediction Using Hierarchical Bayesian Modeling". 2020 International Conference on Communications, Signal Processing and their Applications. Accepted

  4. Eldowa, D., Elgazzar, K., Hassanein, H., Sharaf, T., and Shah, S., "Assessing the Integrity of Traffic Data Through Short Term State Prediction",2019 IEEE Global Communications Conference (GLOBECOM), Waikoloa, HI, USA, 2019, pp. 1-5, IEEE, DOI: 10.1109/GLOBECOM38437.2019.9013491

  5. Williams, T. , Zachary, S. ,Seewald, D., Pokhrel, K., and Sharaf, T., "Survival Analysis of Childhood Leukemia Patients", SIAM Undergraduate Research Online (SIURO), June 2019, DOI: 10.1137/19S019085

  6. Taghreed Alghamdi, Khalid Elgazzar, Magdi Bayoumi, Taysseer Sharaf, Sumit Shah, “Forecasting Traffic Congestion Using ARIMA Modeling”, 15th International Wireless Communications & Mobile Computing, 2019,IEEE.

  7. Hansapani Rodrigo, Chris P. Tsokos, Taysseer Sharaf, Regularized Neural Network to Identify Potential Breast Cancer: A Bayesian Approach, Journal of Modern Applied Statistical Methods, 15(2), pp. 563-579, 2016.

  8. Taysseer Sharaf, Chris P. Tsokos, “Two Artificial Neural Network Approaches For Modeling Discrete Survival Time of Censored Data”, Advances in Artificial Intelligence, vol. 2015, Article ID 270165, 7 pages, 2015.

  9. Taysseer Sharaf, Chris P. Tsokos, “Predicting Survival Time of Localized Melanoma Patients Using Discrete Survival Time Method”, Journal of Modern Applied Statistical Methods 13(1), 140-156, 2014.

Contact.

Get in touch:

taysseer_sharaf
taysseersharaf
@taysseer_sharaf
LinkedIn
 (313) 593-5162
tsharaf@umich.edu
 Department of Mathematics and Statistics 2014 CASL Building 4901 Evergreen Road Dearborn, Michigan 48128, Office number 2080