Mohammed ALi Alshahrani, PhD

Applied college

Assistant proffessor
Applied College
Computer department

Computer science - artificial intelligence

0175427660
moaalshahrANI@nu.edu.sa

Qualifications

Doctor of Philosophy degree    2020
I have graduated with a Doctor of Philosophy degree in computer science from the University of Essex – United Kingdom
Masters degree    2013
I have graduated with a masters degree in computer science from the University of Waikato - New Zealand
Post graduate diploma    2011
I have graduate with a post graduate diploma in Software and Information Technology from Lincoln University – New Zealand
Graduate diploma    2010
I have graduate with a graduate diploma in Software and Information Technology from Lincoln University – New Zealand
English language     2008-2009
achieved an advanced level equivalent to IELTS 6.5. From 28/4/2008 to 24/7/2009.
Bachelor degree    2007
Bachelor degree in education: major computer science

Experiences

Currently I am working at Najran University as Assistant Professor    Since Dec, 2020
I was assigned as the vice-dean of the Supporting Services at the Applied College          Jan, 2022- Oct 2022
I was assigned as assiatent of the CEO at the Applied College for the Supporting Services           Jan, 2022- Oct 2022

I am assigned as the head of computer department at the Applied College     Since Jan, 2021    until june, 2022
I worked at Najran University as a lecturer    May, 2014-Dec 2020
I worked with MKCL Arabia as IT trainer at (King Saud University)    Sep, 2013-May, 2014
 

Specialties and Skills

 Assistant Professor at compurer department    
 

Training Courses

الدورات التدربية

الأبحاث العلمية

Alshahrani, M. (2020). Exploring embedding vectors for emotion detection (Doctoral dissertation, University of Essex). 
Alshahrani, M., Samothrakis, S., Fasli, M. (2019, July). Identifying idealised vectors for emotion detection using CMA-ES. In Proceedings of the Genetic and Evolutionary Computation Conference Companion (pp. 157-158).
Alshahrani, M., Samothrakis, S., Fasli, M. (2017, October). Word mover’s distance for affect detection. In 2017 International Conference on the Frontiers and Advances in Data Science (FADS) (pp. 18-23). IEEE.
Alshahrani, M. A. A. (2013). Real Time Vehicle License Plate Recognition on Mobile Devices (Doctoral dissertation, University of Waikato).
Ahmed, I. A., Senan, E. M., Rassem, T. H., Ali, M. A., Shatnawi, H. S. A., Alwazer, S. M., & Alshahrani, M. (2022). Eye Tracking-Based Diagnosis and Early Detection of Autism Spectrum Disorder Using Machine Learning and Deep Learning Techniques. Electronics, 11(4), 530.
Al-Jabbar, M., Alshahrani, M., Senan, E. M., & Ahmed, I. A. (2023). Analyzing Histological Images Using Hybrid Techniques for Early Detection of Multi-Class Breast Cancer Based on Fusion Features of CNN and Handcrafted. Diagnostics, 13(10), 1753.‏

Al-Jabbar, M., Alshahrani, M., Senan, E. M., & Ahmed, I. A. (2023). Histopathological Analysis for Detecting Lung and Colon Cancer Malignancies Using Hybrid Systems with Fused Features. Bioengineering, 10(3), 383.‏

Al-Jabbar, M., Alshahrani, M., Senan, E. M., & Ahmed, I. A. (2023). Multi-Method Diagnosis of Histopathological Images for Early Detection of Breast Cancer Based on Hybrid and Deep Learning. Mathematics, 11(6), 1429.

Alshahrani, M., Al-Jabbar, M., Senan, E. M., Ahmed, I. A., & Saif, J. A. M. (2023). Hybrid Methods for Fundus Image Analysis for Diagnosis of Diabetic Retinopathy Development Stages Based on Fusion Features. Diagnostics, 13(17), 2783.
 

courses:

field traning
data structure
Introduction to databases
fundamental Programming
applied project

الساعات المكتبية

الوصف

  8-9 9-10 10-11 11-12 12-1 1-2
الأحد
Sunday		     c-35 c-35 c-35 c-35
الاثنين
Monday		         c-35 c-35
الثلاثاء
Tuesday		     c-35 c-35 c-35 c-35
الأربعاء
Wednesday		   c-35     c-35 c-35
الخميس
Thursday		       c-35