My current research line is developing Machine Learning Algorithm for Bioinformatics problems. Most of my machine learning experience is in Artificial Neural Networks which I have successfully used to develop algorithms for solving problems in various domains like: Data Mining, NP-Hard problems , and constraint satisfaction problems (See Publication Section). I am also so much interested in Algorithm Design and Complexity theory.
· Masters Thesis: “Connectionist Approaches to Cost-Based Abduction”. Using High Order Recurrent Neural Networks (HORNs) to find the optimal solution, the least cost explanation, for a given Cost-Based Abduction (CBA) Instance. CBA is an important AI formalism for representing knowledge under uncertainty. Evidence to be explained is treated as a goal to be proven through a set of observed hypotheses each is associated with an assumability cost. Finding the least cost proof for a given CBA instance is an NP-Hard problem.
Thesis Supervisor: Dr. Ashraf M. Abdelbar (Associate Professor of Computer Science, AUC).
Thesis Committee Members: Dr. Amr El-Kadi, Dr. Ahmed Rafea, Dr. Amr Goneid
Thesis External Examiner: Dr. Donald C. Wunsch II (Mary Finley Missouri Distinguished Professor of Computer Engineering, University of Missouri-Rolla, USA).