Researcher | University of Vermont | United States
Mr. Christian Idogho is a Ph.D. Candidate in Materials Science at the University of Vermont, where he focuses on semiconductor thin-film growth, materials characterization, and renewable energy systems. He earned a Bachelor of Engineering in Mechanical Engineering from the University of Agriculture, Makurdi (2020) and a Diploma in Chemical Engineering from Auchi Polytechnic. His professional and research experience spans multiple institutions and international collaborations, including advanced thin-film deposition projects using CVD, sputtering, and pulsed-laser deposition, as well as in-situ X-ray scattering studies at Brookhaven National Laboratory. He has also contributed to renewable energy forecasting research using machine learning at the University of Nigeria, Nsukka, and held teaching assistantships at both the University of Vermont and Auchi Polytechnic, mentoring students in physics and core engineering subjects. His research interests include semiconductor thin-film growth, thermoelectric materials, machine learning for clean energy forecasting, renewable energy systems, and advanced materials characterization techniques such as XRD, SEM, AFM, and ellipsometry. Mr. Idogho’s research skills cover a wide spectrum, including COMSOL Multiphysics, MATLAB, Python, CAD tools (SolidWorks, Autodesk Inventor), and simulation of photovoltaic and thermoelectric systems. His awards and honors include the Best Researcher Award in Machine Learning (2025), Best Undergraduate Thesis Award (2020), and the Olive Real Estate Science and Engineering Scholarship. He is also an active reviewer for journals such as Energy Research and Clean Energy and maintains memberships in Sigma Xi, the Association for Iron & Steel Technology (AIST), Material Advantage, NSBE, and Black in AI. Mr. Idogho’s contributions through publications in Energy Science & Engineering, Energies, and Unconventional Resources underscore his growing reputation in clean energy and advanced materials. With his vision, technical expertise, and commitment to international collaboration, he is positioned to become a global leader in sustainable energy materials and semiconductor research. Mr. Idogho’s growing academic impact is reflected in 21 citations, 4 documents, and an h-index of 1, demonstrating his emerging influence in materials science and renewable energy research.
Profiles: Google Scholar | Scopus | ORCID | LinkedIn
Featured Publications
1. Maduabuchi, C., Nsude, C., Eneh, C., Eke, E., Okoli, K., Okpara, E., & Idogho, C. (2023). Renewable energy potential estimation using climatic-weather-forecasting machine learning algorithms. Energies, 16(4), 1603. Cited by: 25
2. Onuh, P., Ejiga, J. O., Abah, E. O., Onuh, J. O., Idogho, C., & Omale, J. (2024). Challenges and opportunities in Nigeria’s renewable energy policy and legislation. World Journal of Advanced Research and Reviews, 23(2), 2354–2372. Cited by: 15
3. Idoko, P. I., Ezeamii, G. C., Idogho, C., Peter, E., Obot, U. S., & Iguoba, V. A. (2024). Mathematical modeling and simulations using software like MATLAB, COMSOL and Python. Magna Scientia Advanced Research and Reviews, 12(2), 62–95. Cited by: 6
4. Maduabuchi, C., Nsude, C., Eneh, C., Eke, E., Okoli, K., Okpara, E., & Idogho, C. (2023). Renewable energy potential estimation using climatic-weather-forecasting machine learning algorithms. Energies, 16(4), 1603. Cited by: 3
5. Idogho, C., Abah, E. O., Onuh, J. O., Harsito, C., Omenka, K., Samuel, A., Ejila, A., & Idoko, I. P. (2025). Machine learning-based solar photovoltaic power forecasting for Nigerian regions. Energy Science & Engineering, 13(4), 1922–1934. Cited by: 1