Dr Omar Aldhaibani

Senior Lecturer
Dr. Omar A. Aldhaibani is a distinguished Senior Lecturer at Liverpool John Moores University (LJMU), specializing in robotics, artificial intelligence (AI), and sensor technologies. His academic expertise bridges theoretical innovation and practical application, with a proven track record in cutting-edge research, impactful teaching, and interdisciplinary collaboration. Dr. Aldhaibani holds a PhD in Software Defined Wireless Network (SDWN) engineering, where he developed advanced methods for intelligent handover systems in Wi-Fi environments, leveraging Quality of Experience (QoE) metrics and machine learning.

Dr. Aldhaibani is actively engaged in the advancement of autonomous robotic platforms, working with state-of-the-art systems such as Unitree’s Go2 and H1 robots and AgileX’s LIMO. His research spans autonomous navigation, robotic perception systems, and human-robot interaction, integrating machine learning for real-time decision-making. In addition, his expertise in simulation environments such as Webots and Gazebo has enabled the creation of digital twins for optimizing robotic system design and deployment.

At LJMU's Built Environment and Sustainable Technologies Research Institute, Dr. Aldhaibani was spearheads pioneering research aimed at developing sensor platforms. This involves creating non-destructive measurement solutions for healthcare monitoring and innovative sensing technologies to detect insecticide residue on walls, crucial for combating diseases like Malaria. His expertise in design, construction of electronic and RF systems and developing software for microwave systems using AI for decision-making, implementing deep learning techniques to analyse data.

Prior to joining LJMU, Dr. Aldhaibani served as an Industrial Systems Specialist at Sensor City, where he applied his robotics and IoT expertise to real-world projects. Notable achievements include designing a low-power ePaper healthcare monitoring device and developing a smart energy monitoring system for Knowsley Safari Park. These solutions highlight his ability to merge robotics, IoT, and sensor technologies into practical and scalable systems.

Dr. Aldhaibani’s technical expertise encompasses hardware and software integration, robotics system prototyping, and intelligent system development. Proficient in programming languages such as Python, C/C++, and VHDL, he utilizes platforms like Raspberry Pi, Arduino, and Pycom to develop innovative robotics and IoT applications.

An accomplished educator, Dr. Aldhaibani is deeply committed to teaching and mentoring. At LJMU, he delivers modules on robotics systems design, engineering mathematics, and Internet of Things (IoT), providing students with comprehensive, hands-on learning experiences. His teaching approach combines cutting-edge research with real-world applications, preparing students to excel in the rapidly evolving fields of robotics and AI.

Current Research Interests
Robotics
Dr. Aldhaibani’s research focuses on advancing the field of robotics through innovation in design, control, and AI integration. Key areas of interest include:

Autonomous Navigation: Developing algorithms for real-time robotic navigation in complex environments, leveraging AI and sensor fusion for decision-making.
Human-Robot Interaction: Enhancing intuitive interaction methods to improve safety, collaboration, and user experience.
Machine Learning for Robotics: Applying advanced machine learning techniques to improve robotic perception, adaptability, and task performance.
Robotic Manipulation: Creating precise control systems for robotic arms to perform tasks such as object detection, grasping, and manipulation.
Simulation and Digital Twins: Employing platforms like Webots and Gazebo to create digital twins for testing and optimizing robotic systems.
Notable Robotics Projects
Integration of Unitree Go2 and H1 Robots for mobility, object recognition, and advanced autonomous behaviors.
Development of AI-driven robotic systems for pipeline inspection and repair, utilizing image processing and real-time decision-making.
Exploration of robotic platforms for healthcare and industrial automation, combining IoT and robotics technologies to enhance efficiency and scalability.

Languages

Arabic
English
Russian

Degrees

2019, Liverpool John Moores University, United Kingdom, PhD entitled “Developing an SDWN Architecture for Wireless Network Engineering to Support a Quality of Experience Aware Handover
2012, Kharkiv National University of Radio Electronics, Ukraine, M.Sc. degree with in Computer Systems and Networks Engineering.
2009, University of Technology- Iraq, Iraq, B.Sc. Control and Systems Engineering/Computer Engineering

Certifications

2023, LJMU, United Kingdom, Postgraduate Certificate in Higher Education