Oznur Karaca | Environmental Science | Research Excellence Award

Published on by Sciencefather

Assoc. Prof. Dr. Oznur Karaca | Environmental Science | Research Excellence Award

Assoc. Prof. Dr. Oznur Karaca | Environmental Science | Associate Professor at Çanakkale Onsekiz Mart University | Turkey

Assoc. Prof. Dr. Oznur Karaca is a distinguished researcher in Geological Engineering whose work spans environmental geotechnics, soil mechanics, engineering geology, GIS, and remote sensing, earning her strong recognition in both academic and applied research communities. Assoc. Prof. Dr. Oznur Karaca completed her higher education in Geological Engineering, culminating in a doctoral degree that laid the foundation for her internationally oriented research career. She has held progressive academic and professional roles, contributing extensively to university-level teaching, interdisciplinary research supervision, and collaborative international projects focused on sustainable remediation, environmental risk assessment, and geo-environmental engineering solutions. Her research interests include electrokinetic remediation, mine tailing contamination, flood susceptibility mapping, geochemical characterization of sediments, groundwater quality assessment, and the integration of GIS-based multicriteria decision analysis for environmental planning. Assoc. Prof. Dr. Oznur Karaca demonstrates strong research skills in geotechnical laboratory experimentation, field investigation, soil and water interaction studies, data modeling, environmental impact assessments, and the development of remediation technologies for metal-contaminated soils. Her scholarly achievements include impactful publications in high-quality journals indexed in Scopus, Web of Science, and IEEE, with notable citation influence highlighted by her cumulative citation record and collaborative outputs with leading researchers worldwide. She has worked with international partners on environmental sustainability projects addressing soil contamination, mining impacts, and groundwater quality, showcasing her capacity to lead and participate in global scientific initiatives. Assoc. Prof. Dr. Oznur Karaca has received recognitions and academic honors for her research productivity, contributions to environmental engineering, and involvement in professional scientific societies. Her awards reflect sustained excellence in research dissemination, conference presentations, and community-engaged environmental solutions. She continues to contribute as a reviewer, mentor, and academic leader across research networks, strengthening scientific exchange and advancing multidisciplinary collaboration. In conclusion, Assoc. Prof. Dr. Oznur Karaca represents a highly accomplished academic whose research, professional expertise, and commitment to environmental problem-solving highlight her as an influential contributor to the field. Her broad skill set, strong publication record, international partnerships, and capacity for innovative geo-environmental solutions underline her potential for continued advancement and recognition within global scientific communities.

Academic Profile: ORCID | Scopus | Google Scholar

Featured Publications:

  1. Karaca, O., Cameselle, C., & Reddy, K. R. (2018). Mine tailing disposal sites: contamination problems, remedial options and phytocaps for sustainable remediation. Citations: 224

  2. Gül, A., Örücü, M. K., & Karaca, O. (2006). An approach for recreation suitability analysis to recreation planning in Gölcük Nature Park. Citations: 120

  3. Karaca, O., Cameselle, C., & Bozcu, M. (2019). Opportunities of electrokinetics for the remediation of mining sites in Biga peninsula, Turkey. Citations: 44

  4. Karaca, O., Cameselle, C., & Reddy, K. R. (2017). Acid pond sediment and mine tailings contaminated with metals: physicochemical characterization and electrokinetic remediation. Citations: 40

  5. Tiryaki, M., & Karaca, O. (2018). Flood susceptibility mapping using GIS and multicriteria decision analysis: Saricay-Çanakkale (Turkey). Citations: 27

 

 

Abbas Guvalov | Nanotechnology | Best Researcher Award

Published on by Sciencefather

Mr. Abbas Guvalov | Nanotechnology | Best Researcher Award

Mr. Abbas Guvalov | Nanotechnology | Azerbaijan University of Architecture and Construction | Azerbaijan

Mr. Abbas Guvalov is a highly respected academic in the field of Materials Science, recognized for his extensive career and long-standing contribution to architectural and construction education. Serving at the Azerbaijan University of Architecture and Construction for several decades, Mr. Abbas Guvalov has established himself as a leading expert in advanced construction materials, ceramic composites, and porous gravel technologies, shaping the scientific direction of sustainable building practices. His educational background reflects a deep specialization in materials-focused research, supported by his progression into a professorial role where he continues to influence both theoretical and applied aspects of material engineering. Throughout his professional experience, Mr. Abbas Guvalov has demonstrated excellence in teaching, supervising students, participating in research collaborations, and contributing to the academic development of his institution. His research interests span material characterization, innovative stone-like clay composites, expanded porous materials, environmentally responsible construction technologies, and the development of high-strength structural components. In terms of research skills, Mr. Abbas Guvalov is proficient in experimental design, material synthesis, structural evaluation, academic writing, scientific analysis, interdisciplinary collaboration, and the implementation of sustainable material technologies. His featured publication, Obtaining High-Quality Expanded Porous Gravel Based on Low-Expanding Stone-Like Clay, published as a book chapter under a reputable scientific publisher, highlights his contribution to the field and his collaborative engagement with other materials scientists. Over the years, Mr. Abbas Guvalov has earned recognition within his academic community for his dedication to research, teaching, and knowledge dissemination; however, publicly listed awards and honors are not available in the verified records, indicating opportunities for further profile enhancement. As a scholar with substantial academic experience, he remains committed to advancing Materials Science through continuous research, participation in global academic networks, and contribution to high-quality scientific output. In conclusion, Mr. Abbas Guvalov exemplifies academic integrity, professional dedication, and a strong commitment to scientific advancement, with continued potential for expanding his international research presence, producing new high-impact publications, and contributing meaningfully to evolving developments in sustainable construction materials.

Academic Profile: ORCID | Scopus

Featured Publications:

  1. Mammadov, H. N., & Guvalov, A. A. (2021). Obtaining High-Quality Expanded Porous Gravel Based on Low-Expanding Stone-Like Clay.

 

 

Natalia Spyropoulou | Education | Research Excellence Award

Published on by Sciencefather

Dr. Natalia Spyropoulou | Education | Research Excellence Award

Dr. Natalia Spyropoulou | Education | Hellenic Open University | Greece

Dr. Natalia Spyropoulou is a highly accomplished researcher whose work focuses on STEAM education, competence development, lifelong learning, course design, and large-scale MOOC development, contributing significantly to digital learning innovation at the Hellenic Open University and Ionian University. She holds a strong academic foundation culminating in a doctorate in education-related research from a recognized European institution, where she specialized in designing technology-enhanced learning environments and competency-driven instructional frameworks for educators. In her professional experience, Dr. Natalia Spyropoulou has served in various academic and research capacities, participating in collaborative international projects that examine the integration of STEM and STEAM methodologies, online professional development programs, and the role of IoT in shaping student engagement and STEM career pathways. She has maintained active research collaborations with leading scholars and institutions, contributing to multidisciplinary initiatives across Europe. Her research interests include educator competence frameworks, digital pedagogy, virtual learning spaces, communities of practice, MOOC usability, STEM career development, and the broader evolution of distance and flexible higher education. Demonstrating robust research skills, she excels in mixed-methods research design, data analysis, MOOC development strategies, instructional design, and evaluation of digital learning tools across formal and informal education settings. Her scholarly impact is supported by more than 509 citations, an h-index of 13 and an i10-index of 15, alongside active contributions to IEEE-indexed and Scopus-indexed publications. She has collaborated with international research teams and has contributed to policy-driven educational projects focused on empowering educators through structured competence frameworks. Dr. Natalia Spyropoulou has also been involved in notable educational innovation initiatives and has been recognized through invitations to participate in academic conferences, professional development initiatives, and community-based educational programs, highlighting her academic service and leadership. Her awards and honors reflect her contributions to STEAM education development, distance learning innovation, and cross-institutional educational collaboration. Dr. Natalia Spyropoulou’s work demonstrates a consistent commitment to enhancing educator preparation, advancing research-based digital learning solutions, and shaping the future of STEAM pedagogy. She continues to expand her research footprint by contributing to international collaborations, advancing evidence-based instructional frameworks, and fostering the development of modern educational ecosystems that support student engagement, career readiness, and educator professional growth.

Academic Profile: ORCID | Scopus | Google Scholar

Featured Publications:

  1. Spyropoulou, N., Pierrakeas, C., & Kameas, A. (2014). Creating MOOC guidelines based on best practices. Citations: 71

  2. Spyropoulou, N., Demopoulou, G., Pierrakeas, C., Koutsonikos, I., & Kameas, A. (2015). Developing a computer programming MOOC. Citations: 49

  3. Spyropoulou, N., & Kameas, A. (2024). Augmenting the impact of STEAM education by developing a competence framework for STEAM educators for effective teaching and learning. Citations: 46

  4. Spyropoulou, N., Glaroudis, D., Iossifides, A., & Zaharakis, I. (2020). Fostering secondary students’ STEM career awareness through IoT hands-on educational activities: Experiences and lessons learned. Citations: 31

  5. Glaroudis, D., Iossifides, A., Spyropoulou, N., Zaharakis, I., & Kameas, A. (2019). STEM learning and career orientation via IoT hands-on activities in secondary education. Citations: 29

 

Xinyue Xu | Computer Science | Research Excellence Award

Published on by Sciencefather

Ms. Xinyue Xu | Computer Science | Research Excellence Award

Ms. Xinyue Xu | Computer Science | University of Chinese Academy of Sciences | China

Ms Xinyue Xu is a dedicated researcher affiliated with the University of Chinese Academy of Sciences, where she advances her work in intelligent defect detection, robust deep-learning architectures, and computer vision applications for industrial automation. Ms Xinyue Xu completed her doctoral studies in a computing-related discipline at the University of Chinese Academy of Sciences, focusing on lightweight neural network optimization, blur-robust models, and intelligent inspection frameworks that address real-world engineering challenges. Her professional experience includes academic research responsibilities within her institution, participation in collaborative laboratory initiatives, and involvement in international research efforts related to machine vision and high-precision defect-detection systems. Her primary research interests include computer vision, artificial intelligence, defect detection in industrial components, lightweight convolutional models, and the development of high-efficiency architectures suitable for real-time inspection tasks. Ms Xinyue Xu possesses strong research skills in model design, data-driven algorithm development, image processing, neural network compression, performance benchmarking, and experimental evaluation across diverse industrial datasets. Her ORCID profile documents her contribution to the Scopus-indexed journal article FDC-YOLO: A Blur-Resilient Lightweight Network for Engine Blade Defect Detection, where she introduces an enhanced lightweight framework capable of handling blur-induced recognition challenges. This publication demonstrates her technical rigour, methodological clarity, and ability to address practical industrial problems through advanced machine-learning models. Although early in her career, Ms Xinyue Xu exhibits promising scholarly potential and continues to strengthen her academic record. Her research visibility and contributions make her eligible for participation in professional associations such as IEEE and ACM, and her academic accomplishments position her well for future recognition in emerging researcher and innovation-focused award categories. Her honors include her contribution to high-quality peer-reviewed research published in an international journal indexed in Scopus. Moving forward, Ms Xinyue Xu is well positioned to expand her publication portfolio, engage in broader interdisciplinary collaboration, strengthen her global research presence, and contribute to the development of next-generation intelligent inspection technologies. With her commitment to scientific advancement, growing research output, and expertise in applied AI, she continues to demonstrate strong potential for leadership and long-term impact in her field.

Academic Profile: ORCID

Featured Publications:

  1. Xu, X., Li, F., Xiong, L., He, C., Peng, H., Zhao, Y., & Song, G. (2025). FDC-YOLO: A blur-resilient lightweight network for engine blade defect detection. Algorithms.

 

 

Yunju Xiao | Biosensors | Best Researcher Award

Published on by Sciencefather

Mrs. Yunju Xiao | Biosensors | Best Researcher Award

Mrs. Yunju Xiao | Biosensors | Junior Physician at Guangdong Provincial People’s Hospital | China

Mrs. Yunju Xiao is an accomplished researcher specializing in biomedical sensing, nanomaterials-based analytical systems, and molecular diagnostics, recognized for her contributions to advancing innovative detection platforms for clinical and translational applications. She completed her education through rigorous training in medical sciences and research methodology, culminating in a doctoral qualification from a leading medical university where she focused on the development of nano-enabled biosensing technologies for sensitive biomarker identification and disease monitoring. Building on her academic foundation, she has gained significant professional experience at Guangdong Provincial People’s Hospital of Southern Medical University, where she contributes to multidisciplinary projects aimed at improving diagnostic precision and healthcare outcomes. Her research interests span catalytic hairpin assembly mechanisms, gold nanoparticle engineering, signal-enhanced detection systems, surface-enhanced Raman spectroscopy, and microRNA-based disease diagnostics, reflecting her dedication to bridging basic nanoscience with practical clinical applications. Mrs. Yunju Xiao’s research skills include expertise in nanoscale material synthesis, molecular probe design, advanced spectroscopic techniques, microfluidic diagnostics, data interpretation, and laboratory protocol optimization, allowing her to make meaningful contributions to emerging diagnostic research. She has authored multiple peer-reviewed publications indexed in Scopus and other leading databases, accumulating notable citations that reflect the visibility and academic value of her work. Her recognized publication in Sensors and Actuators B: Chemical demonstrates her ability to produce impactful research within competitive scientific fields. Throughout her academic and professional career, she has earned recognition for her scholarly output and has received honors for her contribution to collaborative research efforts and high-quality scientific dissemination. Her involvement in scientific communities further supports her commitment to continuous learning and professional advancement. Mrs. Yunju Xiao’s work reflects analytical rigor, innovation, and a strong commitment to addressing scientific challenges related to early disease detection and diagnostic sensitivity. She continues to expand her research through interdisciplinary collaborations, aiming to contribute to the development of next-generation biosensing systems. In conclusion, Mrs. Yunju Xiao exemplifies a promising and dedicated researcher whose background in biomedical diagnostics, strong methodological skills, and expanding publication record position her as an influential contributor to the future of diagnostic technology and biomedical research.

Academic Profile: ORCID | Scopus

Featured Publications:

  1. Xiao, Y. (2026). Catalytic hairpin assembly (CHA)-driven AuNP tetramer assembly-based SERS platform for sensitive detection of EV-miRNAs. Sensors and Actuators B: Chemical.

 

 

Guoli Song | Robotics | Research Excellence Award

Published on by Sciencefather

Prof. Guoli Song | Robotics | Research Excellence Award

Prof. Guoli Song | Robotics | Researcher at Shenyang Institute of Automation Chinese Academy of Sciences | China

Prof. Guoli Song is an accomplished researcher known for his extensive contributions to medical image analysis, biomedical signal processing, robotics-assisted diagnostics, and intelligent healthcare systems, emerging as a leading figure in the integration of artificial intelligence with modern medical technologies. Prof. Guoli Song completed his higher education at the Shenyang Institution of Automation, Chinese Academy of Sciences, where he earned his doctoral degree with a research focus on computational imaging, intelligent robotics, and medical data interpretation, building a strong academic foundation that continues to support his multidisciplinary scholarship. Over the course of his professional career, he has served in prominent research roles within the Chinese Academy of Sciences, where he has participated in several high-impact international projects involving automated disease detection, AI-based brain tumor segmentation, noninvasive biosensing technologies, and robotic navigation systems for clinical applications. His research interests span medical image registration, deep learning–based diagnosis, biomedical signal processing, optimization frameworks, force-sensing technologies, and computational neuroscience, demonstrating a broad intellectual range supported by strong analytical and technical skills. Prof. Guoli Song is highly proficient in designing advanced machine-learning algorithms, developing intelligent diagnostic pipelines, implementing robotics control architectures, and conducting large-scale computational experiments, which have led to publications in IEEE platforms, Scopus-indexed journals, and other reputable venues with a citation impact exceeding several hundreds. His work has earned recognition through academic honors, research excellence acknowledgments, and invitations to contribute to international collaborations, conferences, and journal review boards. He is actively engaged in professional communities and holds affiliations with respected organizations such as IEEE and ACM, reflecting his commitment to maintaining global research standards and fostering scientific knowledge exchange. Notably, his awards and honors stem from his contributions to intelligent medical systems, advanced diagnostic models, and cross-disciplinary engineering innovations. With a strong record of publications, including influential works on medical image segmentation, biosensing devices, gaze estimation for surgical robots, and hybrid feature-based diagnostic frameworks, Prof. Guoli Song continues to advance cutting-edge methodologies that shape the future of automated healthcare. His continued efforts toward developing efficient, accurate, and clinically relevant technologies highlight his ongoing potential for leadership and innovation. Prof. Guoli Song’s accomplishments, research influence, and future-oriented vision firmly establish him as a leading contributor to global scientific advancement and position him for sustained excellence in medical engineering and computational health research.

Academic Profile: Scopus | Google Scholar

Featured Publications:

  1. Song, G., Han, J., Zhao, Y., Wang, Z., & Du, H. (2017). A review on medical image registration as an optimization problem. 119 citations.

  2. Hao, Z., Luo, Y., Huang, C., Wang, Z., Song, G., Pan, Y., et al. (2021). An intelligent graphene-based biosensing device for cytokine storm syndrome biomarkers detection in human biofluids. 92 citations.

  3. Huang, Z., Zhao, Y., Liu, Y., & Song, G. (2021). GCAUNet: A group cross-channel attention residual UNet for slice-based brain tumor segmentation. 88 citations.

  4. Song, G., Huang, Z., Zhao, Y., Zhao, X., Liu, Y., Bao, M., et al. (2019). A noninvasive system for the automatic detection of gliomas based on hybrid features and PSO-KSVM. 54 citations.

  5. Deng, Y., Yang, T., Dai, S., & Song, G. (2020). A miniature triaxial fiber optic force sensor for flexible ureteroscopy. 50 citations.

Guodong Zheng | Aquaculture | Best Researcher Award

Published on by Sciencefather

Assoc. Prof. Dr. Guodong Zheng | Aquaculture | Best Researcher Award

Assoc. Prof. Dr. Guodong Zheng | Aquaculture | Professor at Shanghai Ocean University | China

Assoc. Prof. Dr. Guodong Zheng is a highly respected researcher in aquaculture genetics and fish physiology, working at the Genetics and Breeding Center for Blunt Snout Bream within Shanghai Ocean University, China. He earned his Ph.D. in aquatic sciences (genetics and breeding) and has since built a strong professional career pioneering research in hypoxia tolerance, genetic marker development, and cellular mechanisms of environmental stress in fish. Professionally, he leads international collaborative projects, notably on CRISPR/Cas9 gene editing in fish, transcriptomics under hypoxic stress, and selective breeding of hypoxia-tolerant fish strains. His research interests include molecular adaptation to stress, apoptosis pathways, gill remodeling, gene regulation of hypoxia-responsive factors, and sustainable aquaculture breeding. He possesses advanced research skills: high-throughput RNA sequencing, CRISPR/Cas9 genome editing, primary cell culture (especially gill cell lines), SNP marker mining, and physiological assays (oxidative stress, apoptosis). Among his awards and honors, Dr. Zheng has been recognized for his contributions to aquatic genetic resources, has received research grants for international projects, and serves as guest editor in international journals such as Animals. In addition, he is a valued member of academic societies and regularly supervises Ph.D. students, contributing to capacity building in aquaculture research. In conclusion, Assoc. Prof. Dr. Guodong Zheng’s pioneering work in combining molecular genetics with physiology under environmentally relevant stress demonstrates not only his deep expertise but also his visionary approach to making aquaculture more resilient and sustainable, positioning him as a leading scientist with strong future potential for innovation and global impact.

Academic Profile: ORCID | Scopus

Featured Publications:

Zheng, G., et al. (2026). Triploid induction by hydrostatic pressure in female Megalobrama amblycephala × male Culter alburnus hybrids: Effects on somatic growth enhancement and sterility. Aquaculture.

Zheng, G., et al. (2026). Synergistic effects of hypoxia and Aeromonas hydrophila infection on immune function in blunt snout bream (Megalobrama amblycephala). Aquaculture.

Zheng, G., et al. (2025). Bim gene regulation in hypoxic stress response of blunt snout bream (Megalobrama amblycephala): Mechanisms of apoptosis, oxidative stress, and transcriptional control by c-Ets-2. Comparative Biochemistry and Physiology Part A: Molecular and Integrative Physiology.

Zheng, G., et al. (2025). Identification of KASP-SNP markers correlated with both growth and hypoxia tolerance traits in blunt snout bream (Megalobrama amblycephala). Aquaculture.

Zheng, G., et al. (2025). Knockout of the fih gene by CRISPR/Cas9 enhances the hypoxia tolerance in grass carp (Ctenopharyngodon idella). Aquaculture.

 

 

Mohammad Badrul Alam Miah | Computer Science | Best Researcher Award

Published on by Sciencefather

Prof. Dr. Mohammad Badrul Alam Miah | Computer Science | Best Researcher Award

Prof. Dr. Mohammad Badrul Alam Miah | Computer Science | Professor at Mawlana Bhashani Science and Technology University | Bangladesh

Prof. Dr. Mohammad Badrul Alam Miah is a distinguished academic and research expert whose scholarly contributions span Data and Text Mining, Artificial Intelligence, Machine Learning, Neural Networks, Computer Vision, Photonic Crystal Fiber Design, and Network Communication Systems, making him a prominent figure in multidisciplinary computational research. Prof. Dr. Mohammad Badrul Alam Miah completed his higher education with advanced research training that established a strong methodological foundation for his career, enabling him to engage in both theoretical and applied scientific studies with exceptional depth. His professional experience includes long-standing service as a professor, program director, research supervisor, and senior academic leader, where he contributed extensively to curriculum development, postgraduate training, and international research collaborations across universities and specialized research centers. His research interests are rooted in intelligent systems, biomedical image analysis, AI-driven disease detection, fiber-optic sensing, blockchain-enabled IoT security, and automated information extraction systems, allowing him to integrate emerging technologies with real-world scientific challenges. Prof. Dr. Mohammad Badrul Alam Miah possesses advanced research skills in algorithm development, predictive modeling, feature engineering, neural network architecture design, data preprocessing, photonic fiber simulation, and cross-domain computational analysis, supported by strong proficiency in scientific programming and experimental validation. His recognition includes multiple scholarly honors, editorial review appointments, invited talks, and collaborative engagement with globally recognized researchers, reflecting his reputation as a respected contributor within the academic community. With a citation record exceeding nine hundred, an h-index demonstrating sustained impact, and numerous publications in IEEE, Scopus, Elsevier, and other reputable platforms, he continues to influence both foundational and applied research domains. His scholarly activities highlight his commitment to innovation, mentorship, and interdisciplinary advancement. Prof. Dr. Mohammad Badrul Alam Miah remains actively involved in expanding his research output through international collaborations, exploring advanced AI applications in healthcare, enhancing neural network performance for medical diagnostics, and contributing to knowledge development in data-driven science. His ongoing work positions him as a forward-looking researcher whose efforts significantly enrich global scientific scholarship and technological progress.

Academic Profile: ORCID | Scopus | Google Scholar

Featured Publications:

  1. Miah, M. B. A., & Yousuf, M. A. (2015). Detection of lung cancer from CT image using image processing and neural network. 165 citations.

  2. Shamim, S. M., Miah, M. B. A., Sarker, M. R. A., & Jobair, A. A. (2018). Handwritten digit recognition using machine learning algorithms. 140 citations.

  3. Mehedi, S. K. T., Shamim, A. A. M., & Miah, M. B. A. (2019). Blockchain-based security management of IoT infrastructure with Ethereum transactions. 45 citations.

  4. Sethi, R., Kaushik, I., & Miah, M. B. A. (2020). Hand written digit recognition using machine learning. 40 citations.

  5. Chowdhury, S., Sen, S., Ahmed, K., Paul, B. K., Miah, M. B. A., & Asaduzzaman, S. (2017). Porous shaped photonic crystal fiber with strong confinement field in sensing applications: Design and analysis. 39 citations.

 

 

Farah Nameni | Physiology | Editorial Board Member

Published on by Sciencefather

Assoc. Prof. Dr. Farah Nameni | Physiology | Editorial Board Member

Assoc. Prof. Dr. Farah Nameni | Physiology | Researcher at IAU/ Varamin-Pishva Branch | Iran

Assoc. Prof. Dr. Farah Nameni is an accomplished scholar in exercise physiology whose research spans neuroinflammation, oxidative stress mechanisms, and the physiological pathways linking exercise with neuroprotective outcomes, earning her recognition as a dedicated researcher and academic leader. Her educational background, anchored in advanced studies in physiology at Islamic Azad University Varamin-Pishva Branch, provided the foundation for her extensive academic and scientific contributions, further strengthened by her professional role as a faculty member in the same institution, where she has contributed to teaching, research supervision, and laboratory development. Throughout her academic journey, Assoc. Prof. Dr. Farah Nameni has cultivated strong research interests focused on molecular and cellular responses to exercise interventions, Alzheimer’s disease models, biochemical markers of stress, neurotrophic signaling, and metabolic adaptations, positioning her work at the intersection of physiology, neuroscience, and sports science. She has developed notable research skills in experimental design, animal model studies, biochemical assays, gene expression analysis, and collaborative academic research, supported by multiple peer-reviewed publications in Scopus-indexed journals. Her work demonstrates proficiency in examining oxidative markers, neurotrophic factors, neurotransmitter receptor regulation, and the therapeutic potential of exercise combined with pharmacological or herbal interventions. In addition to her research productivity, Assoc. Prof. Dr. Farah Nameni has contributed to the scientific community through peer-review service and interdisciplinary collaborations, reflecting her growing recognition within the global research landscape. Her awards and honors stem from her academic contributions, successful project participation, and continuous advancements in exercise physiology research, highlighting her commitment to scholarly excellence and ethical scientific inquiry. As her research portfolio continues to expand, she demonstrates strong potential for further contributions to neurophysiological health, exercise-based therapeutic strategies, and translational scientific applications. In conclusion, Assoc. Prof. Dr. Farah Nameni stands as a dedicated and emerging figure in the field, with her educational foundation, academic experience, research achievements, and scholarly engagement positioning her for continued leadership and future breakthroughs in physiology and related health sciences.

Academic Profile: ORCID 

Featured Publications:

  1. Nameni, F., & Elikaei, F. (2025). The response of glutathione oxidase and cytochrome c to exercise training and sodium selenite in the heart tissue of male rats.

  2. Nameni, F., & Dehkordi, M. R. A. K. (2025). The effects of weight training and Aklil-ol-Malek on histopathology and C-reactive protein, nuclear factor erythroid-derived 2-like 2 beta-site amyloid precursor protein cleaving enzyme 1 genes expression in Alzheimer’s disease model rats.

  3. Nameni, F., Akbari, G., Hadavand, V., Entezari, H., Molaii, S., & Ghadami, N. (2024). Effect of Melilotus extract and exercise on oxidative stress and neuroinflammation in an Alzheimer’s mouse model.

  4. Nameni, F., Islami, M. H. A., & Hofmeister, M. (2024). The effect of exercise and sildenafil on brain-derived neurotrophic factor and tropomyosin kinase B receptor in the hippocampus of Alzheimer’s rats.

  5. Nameni, F., & Firuzmand, F. (2023). Simultaneous effect of resistance training and folate nano-liposome on dopamine receptors in the brain hippocampus of Alzheimer’s rats.

 

Nizar Ben Ezzine | Energy | Editorial Board Member

Published on by Sciencefather

Prof. Nizar Ben Ezzine | Energy | Editorial Board Member

Prof. Nizar Ben Ezzine | Energy | Professor at Carthage University | Tunisia

Prof. Nizar Ben Ezzine is an accomplished scholar in the field of energy engineering, widely recognized for his contributions to thermodynamics, solar cooling technologies, and absorption refrigeration systems, and he has established a strong academic and research identity through his advanced education culminating in a doctoral degree in energetics that laid the foundation for his expertise in thermal sciences and sustainable cooling systems. Throughout his professional journey, Prof. Nizar Ben Ezzine has served in reputable academic and research institutions where he has contributed extensively to teaching, mentoring, scientific collaborations, and the development of cutting-edge research initiatives in the areas of thermodynamic modelling, exergy analysis, and high-efficiency refrigeration cycles. His research interests include solar-driven absorption systems, ammonia–water thermodynamic mixtures, diffusion-absorption refrigeration cycles, sustainable thermal energy solutions, and performance optimisation of environmentally friendly cooling systems, which he explores using advanced numerical modelling, experimental investigations, and multi-parameter optimisation techniques. Prof. Nizar Ben Ezzine demonstrates strong research skills in computational modelling of thermal systems, experimental system testing, simulation of absorption chillers, development of solar-powered cooling technologies, and analytical techniques for evaluating irreversibilities in thermal cycles, supported by an extensive record of publications in Scopus-indexed and high-impact journals. His scholarly outputs include influential articles in journals such as Energy, Renewable Energy, the International Journal of Exergy, and the International Journal of Refrigeration, which collectively reflect his scientific depth and sustained impact. With hundreds of citations, an established h-index, and numerous international co-authorships, he has built a collaborative presence within the global energy research community and contributed to significant international research projects addressing sustainable cooling and thermodynamic optimisation challenges. Prof. Nizar Ben Ezzine has been acknowledged for his academic excellence through various research-based recognitions, invitations to scientific committees, and participation in specialized conferences that highlight his leadership within the thermal and renewable energy sectors. His work continues to influence the design and development of future cooling technologies, and his research trajectory demonstrates strong promise for further innovation in areas such as advanced solar cooling, next-generation refrigerant mixtures, and integrated renewable energy systems. In conclusion, Prof. Nizar Ben Ezzine stands as a leading figure whose scientific contributions, professional experience, collaborative engagements, and commitment to sustainability continue to shape advancements in the global field of energy engineering.

Academic Profile: Google Scholar

Featured Publications:

  1. Ezzine, N. B., Garma, R., & Bellagi, A. (2010). A numerical investigation of a diffusion-absorption refrigeration cycle based on R124-DMAC mixture for solar cooling. Energy, 35(5), 1874–1883. Citations: 108

  2. Ezzine, N. B., Garma, R., Bourouis, M., & Bellagi, A. (2010). Experimental studies on bubble pump operated diffusion absorption machine based on light hydrocarbons for solar cooling. Renewable Energy, 35(2), 464–470. Citations: 83

  3. Ezzine, N. B., Barhoumi, M., Mejbri, K., Chemkhi, S., & Bellagi, A. (2004). Solar cooling with the absorption principle: First and Second Law analysis of an ammonia–water double-generator absorption chiller. Desalination, 168, 137–144. Citations: 61

  4. Mejbri, K., Ezzine, N. B., Guizani, Y., & Bellagi, A. (2006). Discussion of the feasibility of the Einstein refrigeration cycle. International Journal of Refrigeration, 29(1), 60–70. Citations: 27

  5. Barhoumi, M., Snoussi, A., Ben Ezzine, N., Mejbri, K. H., & Bellagi, A. (2004). Modelling of the thermodynamic properties of the ammonia/water mixture. International Journal of Refrigeration, 27(3). Citations: 26