Bio

Degree

PhD in Electrical Engineering and Computer Sciences

Colorado School of Mines

MS in Electrical Engineering / Computational and Applied Mathematics

Colorado School of Mines

MS in Electrical Engineering / Telecommunication

University of Sirte

BS in Electrical Engineering / Electronics

Academy of Science and Technology

Research Interests

My research interests focus on the design, development, and integration of intelligent electrical and computer engineering systems that address real-world challenges in smart infrastructure, sustainable energy, autonomous platforms, and embedded technologies. I am particularly interested in interdisciplinary research that combines hardware design, software intelligence, data analytics, and system-level optimization to create scalable, energy-efficient, and reliable engineering solutions.
During my PhD studies at the Colorado School of Mines, I developed a strong research foundation while gaining extensive teaching and mentoring experience. I supported undergraduate and graduate-level courses including Information Systems Science, Feedback Control Systems, Multidimensional Signal Processing, Image Processing, and Multidisciplinary Engineering and Data Acquisition Laboratories. As a teaching assistant, I prepared and delivered discussion sessions, developed homework assignments and programming projects, assisted with laboratory instruction, and held regular office hours. From 2012 to 2015, I also mentored master’s students at the Central Automation, Robotics, and Distributed Intelligence (CARDI) Laboratory, where I advised graduate researchers and supported interdisciplinary projects. These experiences strengthened my ability to supervise student research and integrate scholarly work into teaching environments.
At MSU Denver, since Fall 2025, a major focus of my research has been smart infrastructure monitoring and sensing systems. Building on my previous work on the Pole Integrity Monitoring System (PIMS), I am developing embedded sensor platforms for real-time structural health monitoring of utility and power distribution infrastructure. This research integrates low-power sensing hardware, wireless communication protocols, edge computing, and data analytics to enable early fault detection, predictive maintenance, and improved infrastructure reliability. Current efforts include the application of machine learning–based anomaly detection techniques, scalable deployment architectures, and cloud-enabled data management systems. I actively involve undergraduate students in hardware prototyping, data acquisition, and algorithm development to promote experiential learning and workforce readiness.
Another key research direction is energy harvesting and sustainable power systems. My work on the Energy Harvesting Transformer explores methods of capturing ambient electromagnetic energy and converting it into usable electrical power for self-powered sensing platforms and Internet of Things (IoT) applications. Future research will focus on improving power conversion efficiency, developing adaptive energy management strategies, and designing hybrid energy harvesting systems that integrate electromagnetic, thermal, and vibration-based sources. This research supports the growing demand for low-maintenance, energy-efficient smart devices in industrial and infrastructure applications.
I also maintain strong interests in autonomous systems and unmanned aerial platforms. Through the Design and Implementation of a Long-Range Quadcopter Drone project, I have investigated embedded control architectures, wireless communication optimization, navigation systems, and energy-aware flight control. Ongoing and future research will explore autonomous navigation, sensor fusion, swarm coordination, and AI-based path planning, with applications in infrastructure inspection, environmental monitoring, and emergency response.
In addition to technical research, I pursue scholarship in engineering education and curriculum pathways, particularly related to the transition between Electrical Engineering Technology (EET) and Electrical Engineering (EE) programs. My work on Transitioning from EET to EE: A Case Study examines curriculum alignment, student preparedness, and academic success factors. This research aims to develop data-driven instructional models that improve student retention, academic mobility, and workforce readiness.
My broader research interests include embedded systems, digital electronics, wireless communication, control systems, signal processing, power electronics, data acquisition systems, and IoT-enabled cyber-physical systems. I am especially interested in collaborative research that integrates artificial intelligence, machine learning, and data-driven optimization techniques with hardware–software co-design.
Looking forward, I aim to pursue externally funded research initiatives that actively engage undergraduate and graduate students in hands-on research activities. I am committed to translating research outcomes into laboratory modules, senior design projects, and industry collaborations. Through the integration of research, teaching, and mentorship, I seek to contribute to academic excellence, technological innovation, and sustainable workforce development.

Teaching Interests

My teaching philosophy is grounded in the belief that engineering education must balance strong theoretical foundations with experiential learning and real-world application. I view teaching as an active and collaborative process in which students are encouraged to construct knowledge through inquiry, experimentation, and reflection. My primary goal as an educator is to cultivate technically competent, ethically responsible, and innovative engineers who are prepared to contribute meaningfully to academia, industry, and society.
My first experience teaching at the college level began in 2005 during my graduate studies at Sirte University in Libya. During this time, I taught undergraduate engineering courses and served as a teaching assistant in multiple core and advanced engineering classes. These early experiences allowed me to engage closely with students from diverse academic backgrounds and provided valuable insight into curriculum design, assessment strategies, and instructional planning. I developed an appreciation for the importance of structured course organization, clear learning objectives, and outcome-based education, which continue to guide my teaching practice today.
In parallel with classroom teaching, I served as a laboratory assistant in the Wireless Communication, Microwave, and Antenna Systems laboratories within the Electrical Engineering and Telecommunication Department. This role strengthened my conviction that laboratory instruction is not supplementary but central to engineering education. I emphasize hands-on experimentation, calibration procedures, instrumentation accuracy, data acquisition, and error analysis as core competencies. Students are encouraged to design experiments, collect and interpret data, and validate theoretical models using real measurements. This approach not only reinforces technical concepts but also develops critical thinking, analytical reasoning, and professional laboratory practices.

In my classroom instruction, I adopt an active and inquiry-based pedagogical framework. I typically introduce new topics using real-world examples, engineering case studies, and guided problem-solving exercises before presenting formal theoretical definitions and mathematical models. This method allows students to develop intuitive understanding and conceptual reasoning prior to formal abstraction. I integrate formative assessments, collaborative group work, and reflective exercises to promote continuous feedback and student engagement.
In laboratory sessions and project-based courses, I emphasize experiential learning by requiring students to collect their own experimental data, implement design solutions, and evaluate system performance using statistical tools and mathematical modeling. Students are encouraged to troubleshoot hardware and software systems, document their work using professional technical reports, and present results in formal oral presentations. These activities mirror industry practices and help students develop essential professional skills such as technical communication, teamwork, and project management.
I am also committed to inclusive teaching practices that recognize diverse learning styles, cultural backgrounds, and academic preparation levels. I employ multiple instructional modalities including visual demonstrations, hands-on activities, simulation-based learning, and interactive discussions. This flexible approach allows students with varying learning preferences to engage meaningfully with course content and achieve academic success.

My teaching interests span a broad range of electrical and computer engineering disciplines, including embedded systems, digital electronics, computer architecture, power systems, renewable energy technologies, control systems, wireless communications, programming, and data analysis. I am particularly interested in developing interdisciplinary courses that integrate hardware design, software development, and system-level engineering concepts.
I actively support curriculum innovation that aligns academic instruction with emerging technological trends. I advocate for the integration of modern development platforms, simulation tools, and industry-standard software into coursework. Additionally, I promote project-based learning modules that expose students to real engineering challenges such as smart infrastructure monitoring, sustainable energy systems, autonomous systems, and Internet of Things (IoT) applications.

My scholarly activities play a central role in shaping my teaching philosophy and instructional design. My work on “Transitioning from EET to EE: A Case Study” has provided important insights into the academic and professional pathways of students moving between applied technology and traditional engineering programs. This research informs my approach to curriculum scaffolding, prerequisite alignment, and bridge course development. I incorporate targeted instructional modules that strengthen students’ mathematical foundations, theoretical understanding, and problem-solving capabilities while preserving the applied skills developed in technology-focused programs.
The Pole Integrity Monitoring System (PIMS) project has significantly influenced my teaching in embedded systems, sensor networks, and power infrastructure courses. I integrate this research into classroom instruction through case studies and laboratory projects in which students design sensor-based monitoring platforms, implement data acquisition systems, and develop fault detection algorithms. These activities help students understand the societal importance of infrastructure reliability and the role of engineering solutions in public safety and smart grid applications.
My work on the Energy Harvesting Transformer has informed my instruction in power electronics, renewable energy systems, and sustainable engineering. Through this project, I emphasize energy efficiency, power conversion techniques, and the design of self-powered electronic systems. I encourage students to investigate alternative energy harvesting methods, evaluate system-level tradeoffs, and explore emerging applications in low-power electronics and IoT-based sensing platforms. This research-driven approach promotes sustainability awareness and innovation in energy-conscious design.
Furthermore, the Design and Implementation of a Long-Range Quadcopter Drone project provides a rich interdisciplinary platform for teaching embedded control systems, wireless communication, power management, and autonomous system design. I integrate concepts from this work into senior design projects and advanced laboratory courses, allowing students to engage in system integration tasks such as flight controller programming, sensor fusion, communication optimization, and battery performance modeling. These experiences prepare students for complex real-world engineering challenges and foster systems-level thinking.

Office Hours

Tuesday and Thursday from 12:00PM–1:00 PM and 2:00PM–3:00 PM