Raymond Edibo

Area of Study / Keywords

Spintronics Chirality-Induced Spin Selectivity (CISS) Artificial Intelligence Carbon Nanotubes Spin-Polarized Charge Transport Machine Learning 6G Networks Spin-Orbit Coupling Quantum Computing Low-Dimensional Materials

About

Raymond Edibo is a Master of Science student in Electrical and Computer Engineering at the University of Alberta, working in the Nano Spintronics Research Group. His research spans spin-polarized charge transport in nanostructured devices and the application of machine learning and AI to next-generation engineering problems, from nanoscale device modelling to sustainable telecommunications systems. He holds a Bachelor of Engineering in Electrical and Electronic Engineering from Baze University, Nigeria, where he graduated with First Class Honors (CGPA: 3.94/4.00), earning Best Student awards in both his department and faculty in 2024.

Beyond research, Raymond is committed to student leadership and community impact. He has served as Engineering Faculty Representative for 500+ students, led entrepreneurship and biotech innovation initiatives, and volunteered as a tutor for preschoolers and internally displaced children in Abuja, Nigeria. He was named Baze Engineering Leader of the Year (2024) and is a McCall MacBain Scholarship Finalist (2025).

Research

My research sits at the intersection of spintronics, nanotechnology, and artificial intelligence. Within the Nano Spintronics Research Group at the University of Alberta, I investigate Chirality-Induced Spin Selectivity (CISS) and the behavior of spin-polarized carriers in carbon nanotubes functionalized with chiral molecules, targeting applications in sensing, information processing, and data storage. I am also interested in how machine learning techniques can be applied to model, predict, and optimize the behavior of nanoscale spintronic systems, bridging fundamental device physics with intelligent, data-driven engineering.

My engagement with AI and ML as core engineering frameworks was shaped through my work with the WINEST Research Group, where I developed practical AI use cases, authored research proposals, and contributed to internationally recognized publications. This includes "Using AI to Reduce the 6G Standards Barrier for African Contributors" (ITU AI for Good Final Report, 2024) and "Principles of Green AI: A Framework for Energy Optimization in Future Networks" (ITU ML Comms Workshop, 2024). I am drawn to building AI and ML systems that are technically robust, globally inclusive, and energy-efficient, with applications spanning nanoscale device modelling, network optimization, and intelligent embedded systems. My technical toolkit includes Python, C, C++, MATLAB, TensorFlow, PyTorch, scikit-learn, CUDA-accelerated computing, LTspice, STM32, Arduino IDE, SCADA systems, embedded signal chain design, and low-power circuit architectures. I am also a Certified Blockchain Professional (NITDA/Domineum Academy), reflecting my interest in decentralized and next-generation computing systems

Teaching

I serve as a Teaching Assistant in the Department of Electrical and Computer Engineering at the University of Alberta, with hands-on experience delivering instruction in programming. I will be continuing as a Teaching Assistant in the upcoming Fall term, further deepening my contribution to undergraduate education.

My commitment to teaching and mentorship extends well beyond the university. As a Music Tutor at Jubilee Creche, Abuja (2023 - 2025), I designed individualized lesson plans for young children, organized musical performances, and nurtured early confidence and creativity. As an English Tutor at an Internally Displaced Persons Primary School in Abuja (2024 - 2025), I developed interactive literacy materials and mentored children from displaced communities, supporting their educational development under challenging circumstances. Through these experiences, spanning engineering classrooms, early childhood education, and underserved communities, I have developed a versatile and human-centered approach to teaching that I bring into every learning environment I am part of