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Assist Prof Dr. Stephen Ojo | Radiofrequency Award | Best Researcher Award

Assistant Professor at Radiofrequency Award, Anderson University, United States.

Dr. Stephen Ojo is an Assistant Professor of Electrical and Computer Engineering at Anderson University, USA. He holds a Ph.D. in Information Systems from Girne American University, Cyprus, and has extensive experience in wireless communication and signal processing. Dr. Ojo has a strong background in teaching and has taught a variety of courses in computer programming, engineering design, electric circuits, and digital systems. He has also worked as a Research Associate at Vodafone Telecommunication Company in Cyprus, where he was involved in developing a multiplicative-based path loss model for wireless channels. Dr. Ojo has received several scholarships and awards, including the ExxonMobil Scholarship Award and a fully funded Ph.D. fellowship. He is proficient in engineering packages, programming languages, and operating systems, making him a versatile and skilled professional in his field.

Professional Profiles:

Education:

Ph.D. in Information Systems from Girne American University, Cyprus, awarded in 2021. The dissertation focused on Experimental and Analytical Studies of Signal Loss in Wireless Local Area Networks using Supervised Machine Learning Algorithms. Master of Science in Electrical and Electronics Engineering from Girne American University, Cyprus, with a minor in Communication Systems, completed in 2018. The thesis explored a Multiplicative Based Model for Wireless Channels. Bachelor of Science in Electrical and Electronics Engineering from the Federal University of Technology, Akure, Ondo State, Nigeria, obtained in 2014. The senior design project involved the design of a 1 kilobyte Static Random Access Memory using CMOS technology.

Work Experience:

Assist Prof Dr Stephen Ojo is an Assistant Professor of Electrical and Computer Engineering at the College of Engineering, Anderson University, Anderson, South Carolina, USA, since September 2021. He serves as the Chairman of the Computer Engineering Faculty Search Committee for the academic years 2023-2024. Dr. Ojo is also a Research Mentor for the NIH (National Institute of Health) R25 Grant Research Program, a position he has held since 2023 and will continue through 2025. Additionally, he is a Subject Matter Expert (SME) and Committee Member on the PhD Dissertation Committee at the University of Charleston, West Virginia, USA, for the year 2024.

Teaching:

Dr. Stephen Ojo has been an integral part of the teaching faculty at Anderson University, bringing his expertise in electrical and computer engineering to the classroom. He has taught a range of courses, including ENGR 130 – Foundations of Computer Programming, ENGR 120 – Foundations of Engineering Designs II, ENGR 299 ā€“ Electric Circuits II, ENEE 230 – Electric Circuits I, ENEE 210 – Digital System and Logic Circuits, CYB 220 – Programming for Security, ENEE 199 – Embedded Systems, and ENEE 299 – Macroelectronics. Dr. Ojo is known for his engaging teaching style and his ability to explain complex concepts in a clear and accessible manner. He is dedicated to providing his students with a high-quality education and is committed to helping them succeed in their academic pursuits. Through his teaching, Dr. Ojo inspires and motivates his students to excel in their studies and pursue careers in the field of electrical and computer engineering.

Research:

Dr. Stephen Ojo’s research interests are centered around the intersection of electrical and computer engineering, with a focus on innovative technologies and applications. His research encompasses various areas, including wireless communication, signal processing, machine learning, and artificial intelligence. Dr. Ojo’s work involves both experimental and analytical studies, often utilizing supervised machine learning algorithms to analyze and optimize wireless local area networks (WLANs). His research aims to enhance the performance and efficiency of wireless communication systems, contributing to advancements in the field. Dr. Ojo’s research also extends to areas such as digital system design, embedded systems, and robotics, where he explores novel approaches and techniques to address complex engineering challenges. Overall, Dr. Ojo’s research is characterized by its interdisciplinary nature and its potential impact on advancing technology and engineering practices.

Research Associate:

As a Research Associate at Vodafone Telecommunication Company in Cyprus from September 2016 to November 2017, Dr. Stephen Ojo was involved in the development of a multiplicative-based path loss model for wireless channels in Cyprus. This project, conducted in collaboration with Vodafone, focused on improving wireless communication systems’ performance and efficiency. Dr. Ojo’s responsibilities included data analysis for wireless systems, conducting field measurements at 2100 MHz across rural, suburban, and urban areas of Cyprus using the Tems 16 Ericsson tool, and computing path loss across the entire country. Additionally, Dr. Ojo compared the measured path loss with theoretical and empirical propagation loss, gaining practical experience with Base station Transceivers and signal measurements. The project aimed to select the best model for Cyprus using RMSE and R2 metrics and estimate traffic density in the country using Erlang B and Erlang C. Ultimately, the project resulted in the development of a new multiplicative-based path loss model for wireless channels, contributing to advancements in wireless communication technology.

Scholarships and Awards:

Dr. Stephen Ojo received the ExxonMobil Scholarship Award from 2009 to 2013, covering his undergraduate program at the Federal University of Technology, Akure, Ondo State, Nigeria. He was also awarded a fully funded Ph.D. fellowship at Girne American University, Cyprus. šŸ†

Technology tools:

Stephen Ojo is proficient in a variety of engineering packages, including MATLAB, NI LABVIEW 2012, PROTEUS 8.0 Professional, AWR, Python, Design Environment 10, Java, and C# programming languages. He also has experience in VLSI design and circuit design, as well as using Multisim 11, SPSS, and SolidWorks. Additionally, Stephen is skilled in Windows and Linux operating systems and is proficient in MS Office Suite, Libre Office Suite, and Open Office Suite. He is also experienced in using Power Word Simulator and VHDL design with Autera.

Publications:

  1. Radial basis function neural network path loss prediction model for LTE networks in multitransmitter signal propagation environments
    • Authors: S Ojo, A Imoize, D Alienyi
    • Citations: 51
    • Year: 2021
  2. A review of artificial intelligence and machine learning for incident detectors in road transport systems
    • Authors: S Olugbade, S Ojo, AL Imoize, J Isabona, MO Alaba
    • Citations: 39
    • Year: 2022
  3. Automating the modular construction process: A review of digital technologies and future directions with blockchain technology
    • Authors: TO Olawumi, DWM Chan, S Ojo, MCH Yam
    • Citations: 39
    • Year: 2022
  4. Development of a multilayer perceptron neural network for optimal predictive modeling in urban microcellular radio environments
    • Authors: J Isabona, AL Imoize, S Ojo, O Karunwi, Y Kim, CC Lee, CT Li
    • Citations: 34
    • Year: 2022
  5. Atmospheric Propagation Modelling for Terrestrial Radio Frequency Communication Links in a Tropical Wet and Dry Savanna Climate
    • Authors: J Isabona, AL Imoize, S Ojo, CC Lee, CT Li
    • Citations: 26
    • Year: 2022
  6. On the Use of Wavelet Domain and Machine Learning for the Analysis of Epileptic Seizure Detection from EEG Signals
    • Authors: KVN Kavitha, S Ashok, LA Imoize, S Ojo, KS Selvan, TA Ahanger, …
    • Citations: 24
    • Year: 2022
  7. Multiplicative based path loss model
    • Authors: B Bilgehan, S Ojo
    • Citations: 16
    • Year: 2018
  8. Path loss modeling: A machine learning based approach using support vector regression and radial basis function models
    • Authors: S Ojo, A Sari, TP Ojo
    • Citations: 15
    • Year: 2022
  9. An ensemble machine learning approach for enhanced path loss predictions for 4G LTE wireless networks
    • Authors: S Ojo, M Akkaya, JC Sopuru
    • Citations: 15
    • Year: 2022
  10. Factors influencing the adoption of blockchain technology in the construction industry: a system dynamics approach
    • Authors: TO Olawumi, S Ojo, DWM Chan, MCH Yam
    • Citations: 13
    • Year: 2021
Stephen Ojo | Radiofrequency Award | Best Researcher Award

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