Aristide Tolok Nelem | Multicriteria optimization | Research Excellence Award

Dr. Aristide Tolok Nelem | Multicriteria optimization | Research Excellence Award

University of Ebolowa | Cameroon

Dr. Aristide Tolok Nelem is a dedicated academic and researcher specializing in renewable energy and electrical engineering. he serves as lecturer and head of the department of renewable energy at the higher technical teachers’ training college of the University of Ebolowa, where he also leads the computer and automation research group. his scholarly interests centre on developing low-environmental-footprint energy solutions, especially solar-powered and hybrid systems, combining experimental studies with modelling and simulation to address energy deficits. among his peer-reviewed contributions are studies such as “Optimal Placement and Sizing of Distributed Energy Generation in an Electrical Network Using the Hybrid Algorithm of Bee Colonies and Newton Raphson” and “Extraction of the Parameters of a Photovoltaic Solar Cell by a Metaheuristic Method Associated With the Lambert-W Function,” reflecting his commitment to advancing solar energy technologies. as of this writing, publicly accessible databases list at least two such articles under his authorship. however, comprehensive bibliometric indicators (h-index, total document count, total citation count) are not available or cannot be reliably verified from open sources.

Profile: Orcid 

Featured Publications 

Mbakop, F. K., Assoualaye, G., Tom, A., Tolok Nelem, A., Bidias, J. B., Leontie, L., Iacomi, F., & Djongyang, N. (2024). Effect of efficiency of a thermophotovoltaic GaSb solar cell subjected to 1D photonic crystal filter and double/multi-layer anti-reflective coatings. Transactions of the Indian National Academy of Engineering.

Ndzana, N. D. M., Tolok Nelem, A., Abanda, Y. A., Pesdjock, M. J. P., Ngouagna, M. V. T., Zeh, O. F., & Ele, P. (2024). Lithium-ion point-of-care ultrasound battery joint state of charge estimation. Scientific African, 15, e02232.

Tolok Nelem, A., Ele, P., Onanena, R., Olivier, V. B., Ngo Bissé, T. J., & Pesdjock, M. J. P. (2023). An application of multicriteria decision aid in switching state control of a hybrid electric power generation network. Journal of King Saud University – Engineering Sciences, 35(4), 1–12.

Tolok Nelem, A., Ele, P., Ndiaye, P. A., Essiane, S. N., & Pesdjock, M. J. P. (2021). Dynamic optimization of switching states of a hybrid power network. International Journal of Control, Automation and Systems, 19, 1–10.

Angela CHAO | Industrial Organization | Women Researcher Award

Prof. Dr. Angela CHAO | Industrial Organization | Women Researcher Award

Southeast University | China

Angela C. Chao is an Associate Professor with tenure in the Department of Economics at Southeast University, where she also directs the Institute of Big Data Platform Economics and Enterprise Growth, and serves on the council of the China Industrial Economics Association. Her research lies in theoretical industrial organization, with particular emphasis on strategic decision-making by platforms, regulation, and issues in technological innovation. She holds a doctoral degree in Industrial Economics from Xi’an Jiaotong University, a master’s in Finance, and a bachelor’s in Business Administration. She has held postdoctoral and visiting scholar appointments including at Oxford University and Stanford University, and currently is an Honorary Research Associate at Oxford’s Smith School of Enterprise and Environment. Her published work spans multiple journal articles, book chapters, and conference papers. She has over [h-index: X], with more than [documents: Y] publications that have been cited [citations: Z] times. She participates in editorial work and academic leadership roles, contributing to both policy and scholarly debates in economics and management. Her work leverages big data analysis and dynamic models to understand enterprise growth, regulatory frameworks, and platform economics.

Profile: Scopus 

Featured Publications 

The role of Fintech in shaping corporate carbon emissions: Evidence from China's firm-level data.