Dr. Sameh Hassanien Basha received Ph.D. and master's degrees in computational science from the Department of Mathematics- Faculty of Science- Cairo University, Egypt, in 2001, and 2018 respectively. He received a Bachelor's degree with a specialization in Mathematics and Computer Science from the Department of Mathematics- Faculty of Science- Cairo University, Egypt, in 2005. His research interests include Machine Learning and statistical methods applied to the analysis of many types of data for basic science purposes, Optimization techniques, Soft computing to deal with imprecise, incomplete, inconsistent data, Rough sets to reduce the amount of data and obtain the same accuracy, Neutrosophic set and neutrosophic logic which generalize the fuzzy set and fuzzy logic, and Data Mining which aims to extract the useful hidden information from the data.
Dr. Basha’s research in both Master's and Ph.D. degrees is focused on using soft computing techniques to deal with imprecise, incomplete, inconsistent, and vague data. In the master thesis, we used the wavelet method as a reduction technique to refine the input rules for the hybrid genetic-fuzzy data mining model.
In his Ph.D. thesis, defined a Neutrosophic Rule-Based System(NRBS) which is a rule-based system where neutrosophic logic(NL) is used as a tool for representing different forms of knowledge about the problem at hand, as well as for modeling the interactions and relationships that exist between its variables. One of the major drawbacks of NRBSs is that they are not able to learn but require the KB to be derived from expert knowledge. The key point is to employ an evolutionary learning process to automate the NRBS design.
The second step is building a hybrid system between a Genetic Algorithm and a Neutrosophic rule-based system that aims to the genetic learning process at designing or optimizing the KB.
Dr. Basha’s research activity focuses on developing, analyzing, and using soft computing methods and Machine Learning (ML) algorithms.
