Faculty Profile

Wael Korani

Title
Assistant Professor
Department
Information Science
College
College of Information

    

    

      


                          

            
Curriculum Vitae

            

              Click Here to View Faculty CV
            

          

        
                          

            
Education

            



  

  


  
PhD, University of Regina, 2021. 
Major: Computer Science
Degree Specialization: Artificial intelligence
Dissertation Title: Mother Tree Optimization for solving continues and discrete optimization problems
MSc, Tuskegee university, 2015. 
Major: Bioinformatics
Degree Specialization: Master of science
Certificate, Oracle university, 2008. 
Major: database
Degree Specialization: DBA and DBD
MSc, Cairo University, 2008. 
Major: Electrical Power and Machines Engineering
Degree Specialization: Control Systems
BS, Ain Shams University, 2002. 
Major: Electrical Engineering
Degree Specialization: Electrical Engineering





          

        
                

          
Current Scheduled Teaching*


          
DTSC 5505.001, Applied Machine Learning for Data Scientists, Summer 2024 
INFO 5709.002, Data Visualization and Communication, Summer 2024 
INFO 5505.020, Applied Machine Learning for Data Scientists, Spring 2024 
INFO 6900.727, Special Problems, Spring 2024 


          
*
  Texas Education Code 51.974 (HB 2504) requires each institution of
  higher education to make available to the public, a syllabus for
  undergraduate lecture courses offered for credit by the institution.
  

        

      

    

  


    

    

      


        


          


            
Previous Scheduled Teaching*


            
                    

                    INFO 5505.020, Applied Machine Learning for Data Scientists, Fall 2023  SPOT
                    

                    INFO 6900.042, Special Problems, Fall 2023 
                    

                    INFO 5505.001, Applied Machine Learning for Data Scientists, Summer 5W2 2023  SPOT
                    

                    INFO 5709.002, Data Visualization and Communication, Summer 5W1 2023  SPOT
                    

                    INFO 5505.020, Applied Machine Learning for Data Scientists, Spring 2023  SPOT
                    

                    INFO 5505.001, Applied Machine Learning for Data Scientists, Fall 2022  SPOT
                    

                    INFO 5505.020, Applied Machine Learning for Data Scientists, Fall 2022  SPOT
                    

                    INFO 5505.001, Applied Machine Learning for Data Scientists, Summer 5W2 2022 
                    

                    INFO 5709.002, Data Visualization and Communication, Summer 5W1 2022 

          


          
*
  Texas Education Code 51.974 (HB 2504) requires each institution of
  higher education to make available to the public, a syllabus for
  undergraduate lecture courses offered for credit by the institution.
  

        

      

    

  

  
  	

	

	  

		

		   
Published Publications



  

  
Published Intellectual Contributions


  
Conference Proceeding
Korani, W.  (2023). Binary Mother Tree Optimization Algorithm for 0/1 Knapsack Problem. Springer nature. 
Korani, W., Akbari, H.  (2023). Early Detection of Depression and Alcoholism Disorders by EEG Signal. 
Korani, W., Malek, M.  (2022). Discrete Mother Tree Optimization and Swarm Intelligence for Constraint Satisfaction Problems. ICAART. 
Korani, W., Mouhoub, M.  Mother Tree Optimization for Conditional Constraints and Qualitative Preferences. 8. IEEE SSCI 2022. 



	
		
		
	  

	

	

  
    
	

	

	  

		

		   
Awarded Grants



  
  
  	  
          
Contracts, Grants and Sponsored Research  

 	 
	 	 
  
Grant - Research   
Malarvizhi Kumar, P. (Principal), Xiao, T. (Co-Principal), Korani, W. (Co-Principal), "Cohort II of the Capacity Building for Research at Minority-Serving Institutions: Infrastructure Research Readiness," Sponsored by NSF, Federal, $3000 Funded. (November 2023 – August 2024).



	
		
		
	  

	

	

	
	

  
  
  

  	

		

		,  
			
				

					
					Overall
Summative Rating		
					Challenge and
Engagement Index		
					Response Rate
					
				

			
			
				

					
					
out of 5		
					
out of 7		
					%
 of 
students responded		
					
					
				

			
		


		
    
			
  • Overall Summative Rating (median):
    
			This rating represents the combined responses of students to the four global summative items and is presented to provide an overall index of the class’s quality. Overall summative statements include the following (response options include a Likert scale ranging from 5 = Excellent, 3 = Good, and 1= Very poor):
				
      
					
    • The course as a whole was
      • 
					
    • The course content was
      • 
					
    • The instructor’s contribution to the course was
      • 
					
    • The instructor’s effectiveness in teaching the subject matter was
      • 
				
    
			
    • 
			
  • Challenge and Engagement Index:
    
			This rating combines student responses to several SPOT items relating to how academically challenging students found the course to be and how engaged they were. Challenge and Engagement Index items include the following (response options include a Likert scale ranging from 7 = Much higher, 4 = Average, and 1 = Much lower):
				
      
					
    • Do you expect your grade in this course to be
      • 
					
    • The intellectual challenge presented was
      • 
					
    • The amount of effort you put into this course was
      • 
					
    • The amount of effort to succeed in this course was
      • 
					
    • Your involvement in course (doing assignments, attending classes, etc.) was
      • 
				
    
			
    • 
		

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