Dr. Moamed Wahby.jpeg

Dr. Mohamed A. Wahby Shalaby

Associate Professor

Faculty Office Ext.

1763

Faculty Building

UB2

Office Number

S25

Biography

Dr. Mohamed. A. Wahby Shalaby is an associate professor in the Mechanical Engineering program at the School of Engineering and Applied Sciences (EAS), Nile university. He is an associate professor in the fields of artificial intelligence, information technology and robotics. He received the BSc. and MSc. degrees in computer engineering from Cairo University, Egypt, and the Ph.D. degree in electrical and computer engineering from Concordia University, Canada in 2012. Recently, He is assigned to be the EAS Quality assurance unit Manager. Dr. Shalaby has been an associate editor of the Egyptian Informatics Journal, Elsevier, since 2015. He is also an IEEE member of the computational intelligence society and IEEE SA (Standards Association). In addition, Dr. Shalaby has been a founding member of the multi-disciplinary Smart Engineering Systems Research Center (SESC) at Nile University, Giza, Egypt.
 

Recent Publications

Modeling and control of 3-omni wheel Robot using PSO optimization and Neural Network

Omni mobile robots are one of the mobile robots that interact with humans in many areas where it is needed to be collaborative and accurate. Committing robotics with artificial intelligence-based controllers became nowadays mandatory for more association of these robots with distinct environments. This paper proposes the distinction of the 3WD Omni Vision feedback model between Simscape and actual

Mechanical Design
Research Tracks
  • Artificial Intelligence
  • Deep Learning
  • Robotics and Computer Vision
  • Biometrics
  • Image Encryption
  • Image and Video Processing
     
Projects
Research Project

Optimization of Fuzzy Electric Vehicle Routing Problem

Objective/Contributions: The issue of sustainable development is a global one. As a result, green innovation has emerged as a critical avenue to resolving environmental issues, gaining a competitive edge, achieving carbon neutrality, and further promoting sustainable development. One of the biggest sustainable development initiatives is the United Nations’ Sustainable Development Goals (SDG). The
1
Research Project

Sate flow modelling and Control of Home Appliance

Abstract Modern home appliances are designed to be intelligent, performing complex activities to make our lives easier. However, unexpected failures, such as error codes in automatic washing machines, can be confusing for users. Discrete event models can be used to improve the prediction of appliance behavior and avoid this scenario. These models can help identify the root cause of the error
1
Research Project

Optimization of Fuzzy Electric Vehicle Routing Problem

Abstract This research project addresses the electric vehicle routing problem with fuzzy demands, soft time windows, and fuzzy real-time traffic conditions. A mixed-integer programming model was developed, and a two-phase solution approach was proposed. The first phase examined the effect of recharging, while the second phase studied the impact of real-time traffic conditions. To overcome the
Electric Vehicles Utilization for Freight Transportation in Egypt: Opportunities and Challenges
Research Project

Electric Vehicles Utilization for Freight Transportation in Egypt: Opportunities and Challenges

Abstract This paper aimed at addressing and examining the major opportunities and challenging facing relevant stakeholders to utilize electric vehicles (EVs) for freight transportation. Through PESTEL analysis and stakeholders’ questionnaire, we were able to understand the governmental effort done so far and understand the stakeholders’ needs and potential to shift towards EV trucks for freight
Novel Concept-based Image Captioning Models using LSTM and Multi-Encoder Transformer Architecture
Research Project

Novel Concept-based Image Captioning Models using LSTM and Multi-Encoder Transformer Architecture

Abstract Captioning images involves using vision and language models to describe images concisely. Successful captioning requires extracting key information, including the image's topic. While state-of-the-art methods use topic modeling on caption text, this lacks consideration of the image's semantic information. Concept modeling, which extracts concepts directly from images and caption text, can