Somayeh Najafi-Ghobadi | Econometrics | Best Researcher Award

Published on by Sciencefather

Assist. Prof. Dr. Somayeh Najafi-Ghobadi | Econometrics | Best Researcher Award

Assist. Prof. Dr. Somayeh Najafi-Ghobadi | Econometrics | Assistant profesor at Kermanshah university of technology | Iran

Assist. Prof. Dr. Somayeh Najafi-Ghobadi is a dedicated academic and researcher whose scholarly work integrates industrial engineering, operations research, data mining, and healthcare analytics, making her a highly recognized contributor in multidisciplinary research environments. She obtained her Ph.D. in Industrial Engineering and currently serves as an Assistant Professor in the Department of Industrial Engineering at Kermanshah University of Technology, where she actively mentors students, leads research initiatives, and contributes to institutional academic excellence. Her professional experience includes extensive involvement in research projects focusing on optimization, supply chain management, and data-driven modeling, as well as collaborations with prominent scholars from institutions such as the University of Tehran, Alzahra University, and Tecnológico de Monterrey, which highlight her ability to work in international and cross-disciplinary teams. Assist. Prof. Dr. Somayeh Najafi-Ghobadi has cultivated expertise in game theory, machine learning applications, and predictive modeling, contributing to both theoretical advancements and real-world problem-solving, particularly in industrial decision-making and healthcare applications. Her research interests cover a wide range of interconnected domains, including closed-loop supply chains, new product diffusion modeling, dynamic pricing, healthcare informatics, and predictive analytics for patient outcomes. With a citation count of over 136, an h-index of 7, and an i10-index of 6, her publications in high-quality journals indexed in Scopus and IEEE demonstrate not only the visibility but also the impact of her research contributions. She has published influential works on subjects such as pricing and supplier selection in closed-loop supply chains, machine learning classifiers for predicting low birth weight, and optimization of marketing-mix strategies for new generation products, which reflect her versatility and problem-oriented approach to complex challenges. In terms of research skills, Assist. Prof. Dr. Somayeh Najafi-Ghobadi is proficient in advanced mathematical modeling, algorithm development, data mining, and statistical analysis, and she applies these skills to both industrial optimization problems and health-related predictive studies.

Academic Profile: ORCID | Scopus | Google Scholar

Featured Publications:

Najafi-Ghobadi, S., & Esmaeili, M. (2018). A game theory model for pricing and supplier selection in a closed-loop supply chain. International Journal of Procurement Management, 11(4), 472–494. Citations: 25

Arayeshgari, M., Najafi-Ghobadi, S., Tarhsaz, H., Parami, S., & Tapak, L. (2023). Machine learning-based classifiers for the prediction of low birth weight. Healthcare Informatics Research, 29(1), 54–63. Citations: 19

Najafi-Ghobadi, S., Bagherinejad, J., & Taleizadeh, A. A. (2021). A two-generation new product model by considering forward-looking customers: Dynamic pricing and advertising optimization. Journal of Retailing and Consumer Services, 63, 102387. Citations: 19

Najafi-Ghobadi, S., Bagherinejad, J., & Taleizadeh, A. A. (2021). Modeling the diffusion of generation products in the presence of heterogeneous strategic customers for determining optimal marketing-mix strategies. Computers & Industrial Engineering, 160, 107606. Citations: 16

 

Prof. Dr. Hui Li | Economics | Best Researcher Award

Published on by Sciencefather

Prof. Dr. Hui Li | Economics | Best Researcher Award

Prof. Dr. Hui Li | Economics – Dean at Kaifeng University, China

Dr. Hui Li is a dedicated researcher at Kaifeng University, China, whose academic journey and scientific contributions focus on the development of sustainable energy solutions through advanced nanotechnology. With an h-index of 7, over 350 citations across 9 peer-reviewed articles, and growing recognition in the field of triboelectric nanogenerators, Dr. Li is emerging as a promising figure in energy research. His interdisciplinary expertise spans nanomaterials, mechanical systems, and energy harvesting technologies, making his work both impactful and timely within the global transition toward renewable energy.

Profile Verified:

Scopus

Education:

Dr. Li has built a strong academic foundation in the field of energy and materials science through rigorous training and research-oriented education. Though specific degree information is not publicly detailed, his scholarly work reflects a well-rounded understanding of physics, electrical engineering, and applied materials science. His research contributions, particularly in high-level journals, indicate a research-intensive educational background that has equipped him with the tools to pursue cutting-edge innovation in energy conversion and storage technologies.

Experience:

Currently serving at Kaifeng University, Dr. Li has accumulated practical experience in collaborative, cross-functional research environments. He has worked alongside multidisciplinary teams to design, fabricate, and evaluate systems based on triboelectric nanogenerators, a novel energy-harvesting technology. His professional activities have included contributing to experimental design, data analysis, and writing for high-impact publications. Through his academic role, he also likely mentors students and participates in university-level scientific activities that reinforce the broader dissemination of knowledge and the promotion of renewable energy research.

Research Interest:

Dr. Li’s primary research interests center around sustainable energy systems, particularly through the use of triboelectric nanogenerators (TENGs). He is fascinated by the ability of these devices to harvest ambient mechanical energy—such as waves, vibrations, or human motion—and convert it into usable electricity. His work explores frequency upconversion, system networking, and material optimization, all aimed at increasing the efficiency and scalability of nanogenerator systems. Additionally, he is interested in interdisciplinary methods that link materials science, nanotechnology, and electronics to develop smarter, greener technologies for the future.

Award:

Although there is currently no record of formal grants or major awards listed under Dr. Li’s Scopus profile, his steadily increasing citations, high-impact publications, and continued research productivity represent a strong trajectory toward future academic and institutional recognition. His contributions are beginning to receive attention in the academic community, which positions him well for research awards that honor innovation, collaboration, and sustainability in science.

Publication 📚:

 📘 Design of an efficient blue energy harvesting system based on triboelectric nanogenerators with frequency upconversion and networking strategies

Conclusion:

Dr. Hui Li exemplifies the qualities of an emerging leader in energy science, with a focused research agenda, growing citation impact, and a clear commitment to innovation in renewable technologies. While still in the early-to-mid phase of his research career, his contributions to triboelectric nanogenerators are technically sound, forward-looking, and socially relevant. His potential for future impact is substantial, especially as he continues to publish in high-impact journals and collaborates with diverse scientific teams. Dr. Li’s profile aligns well with the goals of the Best Researcher Award, making him a strong and deserving nominee for recognition based on his scientific dedication, interdisciplinary innovation, and research promise.