Ziad Doughan

Research Interests:

• Artificial Intelligence, Machine learning and Deep learning 
• Discrete and Logic-based Artificial Intelligence
• Biomimetic systems, Artificial General Intelligence (AGI) and Artificial Super Intelligence (ASI)
• Graphics, Games and Robotics
   

Education: Degrees, Discipline, Institution and Date

• Ph.D., Electrical and Computer Engineering, BAU, 2022 
• M.Sc., Electrical and Computer Engineering, BAU, 2016
• B.Sc., Electrical and Computer Engineering, BAU, 2006

Computer Engineering Program:

• Artificial Intelligence
• Machine Learning
• Deep Learning
• Computer Graphics
• Discrete Structures
• Programming
• Object Oriented Programming
• Algorithms
• Compiler

• Skills: Project Management, Leadership, Interpersonal Communication, Artificial Intelligence, Data Analysis
• Concepts: OOP, UML, PMP, Agile, SCRUM
• Programming: VS.Net, JAVA, C++, HTML, Python
• Databases: SQL Server, MS Access, Java DB
• Systems: Windows, DOS, Cisco
• Software: MS Office, MS Visio, MS Project, Primavera, SAP

• Deep Learning: a Hands-on Introduction, MaLGa, Università di Genova, 2022
• Computer Vision Crash Course, MaLGa, Università di Genova, 2022
• Fundamentals of Deep Learning, NVIDIA DLI, 2022
• R Programming, Course, The Johns Hopkins University, 2022.
• Python for Data Science, Specialization, Datacamp, 2021 (4 Cources):
  • Python Data Science Toolbox Part 2.
  • Python Data Science Toolbox Part 1.
  • Intermediate Python.
  • Introduction to Python.
• Deep Learning, Specialization, Deeplearning.ai, 2020 (5 Courses):
  • Sequence Models.
  • Structuring Machine Learning Projects.
  • Convolutional Neural Networks.
  • Improving Deep Neural Networks.
  • Neural Networks and Deep Learning.
• Machine Learning, Course, Stanford Online, 2020.
• Cisco CCNA 4.1, Cisco, 2008 (4 Cources).

Principal publications and presentations:
I.  Journal Publications

1.    Z. Doughan, H. Al Mubasher, M. Bizri, and A. M. Haidar “The Metaverse: A Virtual World in the Palm of Your Hand”, BAU Journal - Science and Technology, 2022.

2.    Z. Doughan, R. Kassem, A. M. El Hajj, A. M. Haidar “Artificial Neural Network Vision: Between Myth and Reality”, Theme Issue: Science Fiction or Fact? IEEE Potentials, 2022.

3.    Z. Doughan, R. Kassem, A. M. El Hajj, A. M. Haidar “Novel Preprocessors for Convolution Neural Networks”, IEEE Access, April 2022, DOI: 10.1109/ACCESS.2022.3163405

II.  Conference Proceedings
1.    Z. Doughan, R. Kassem, A. M. El Hajj, A. M. Haidar “Logic-Based Neural Network for Pattern Correction”, IEEE International Conference on Smart Systems and Power Management (IC2SPM), Beirut, Lebanon, November 2022.
2.    Z. Doughan, R. Kassem, A. M. El Hajj, A. M. Haidar “Logic-Based Neural Network for Image Compression Applications”, 3rd IEEE Middle East & North Africa COMMunications Conference (MENACOMM), Agadir, Morocco, December 2021, DOI: 10.1109/MENACOMM50742.2021.9678278
3.    Z. Doughan, W. Itani, A. M. Haidar "Advanced Biomimetic Cells Architecture for Parallel Operations in Artificial Intelligence", 4th International Conference on Advances in Computational Tools for Engineering Applications (ACTEA), Zouk Mosbeh, Lebanon, July 2019, DOI: 10.1109/ACTEA.2019.8851116
4.    H. Koleilat, Z. Doughan, Y. Attallah "Automatic Radial Routing Protocol for Public Transport System", 4th International Conference on Advances in Computational Tools for Engineering Applications (ACTEA), Zouk Mosbeh, Lebanon, July 2019, DOI: 10.1109/ACTEA.2019.8851091
5.    Z. Doughan, W. Itani, A. M. Haidar "Biomimetic Cells: A New Frontier in Brain Informatics", IEEE International Multidisciplinary Conference on Engineering Technology (IMCET), Le Commodore Hotel, Hamra, Beirut, Lebanon, November 2018, DOI: 10.1109/IMCET.2018.8603044
6.    Z. Doughan, W. Itani, A. M. Haidar "Bio-mimetic Approach in Digital Artificial Neuro-science", 3rd International Conference on Advances in Computational Tools for Engineering Applications (ACTEA), Zouk Mosbeh, Lebanon, July 2016, DOI: 10.1109/ACTEA.2016.7560120