Ms. Ifza Shad | Computer Vision | Research Excellence Award

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Ms. Ifza Shad | Computer Vision | Research Excellence Award

University of Central Punjab | Pakistan

Ms. Ifza Shad is a computer vision and artificial intelligence researcher whose work focuses on real-time object detection, medical image analysis, deep learning optimization, and multimodal perception models for complex environments. Her research integrates advanced machine learning architectures, including YOLO-based detectors, attention-driven fusion networks, and lightweight deep learning frameworks designed for resource-efficient deployment in dynamic real-world scenarios. She has contributed to cutting-edge studies in aquatic and surface litter detection, brain tumor diagnosis, protective workwear recognition, and driver-behavior monitoring systems, demonstrating a strong emphasis on safety, healthcare, and environmental sustainability. Her interdisciplinary approach merges computer vision, robotics, and large-scale data processing, allowing her to design algorithms that address challenges in automation, public health, and smart systems. She has authored impactful publications in reputable international journals indexed in Scopus and Web of Science, with her research widely cited and accessible on Google Scholar. Her scholarly record includes peer-reviewed articles, collaborative projects with international researchers, and contributions to academic seminars and conferences. She continues to advance innovative detection models and AI-driven solutions, aiming to enhance real-time decision support systems through robust, interpretable, and computationally efficient algorithms. Her research output reflects a growing citation count, supported by Scopus metrics, Google Scholar indices, and document-level analytics, emphasizing her active role in the global scientific community and her contribution to emerging intelligent systems.

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ORCID

Featured Publications

Shad, I., Zhang, Z., Asim, M., Al-Habib, M., Chelloug, S. A., & Abd El-Latif, A. (2025). Deep learning-based image processing framework for efficient surface litter detection in computer vision applications. Journal of Radiation Research and Applied Sciences, 18(2), 101534.

Shad, I., Bilal, O., & Hekmat, A. (2025). Attention-driven sequential feature fusion framework for effective brain tumor diagnosis. Significances of Bioengineering & Biosciences, 7(3).

Hekmat, A., Zhang, Z., Khan, S. U. R., Shad, I., & Bilal, O. (2024). An attention-fused architecture for brain tumor diagnosis. Biomedical Signal Processing and Control, 101, 107221.

Assoc. Prof. Dr. Ammar Oad | Computer Vision | Research Excellence Award

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Assoc. Prof. Dr. Ammar Oad | Computer Vision | Research Excellence Award

Professor | Shaoyang University | China

Assoc. Prof. Dr. Ammar Oad is an accomplished researcher in Artificial Intelligence with strong expertise in deep learning, computer vision, cybersecurity, and intelligent data-driven systems. His research focuses on designing advanced algorithms for image analysis, object detection, multimodal learning, cross-modal retrieval, and secure AI frameworks capable of addressing modern challenges in threat detection and autonomous systems. Dr. Oad’s scientific contributions span AI-powered fake news detection, plant disease identification using explainable AI, blockchain-enabled cybersecurity mechanisms, sustainable smart grid prediction models, and intelligent pattern recognition. His research impact is reflected in Scopus metrics of 382 citations across 374 documents with an h-index of 9, and Google Scholar metrics of 573 citations, h-index 10, and i10-index 12, demonstrating strong visibility and influence within the scientific community. His work regularly appears in reputable journals such as IEEE Access, Optik, Electronics (MDPI), and leading materials science journals through interdisciplinary collaborations. Dr. Oad also contributes to the academic community as an editorial board member and scientific reviewer for several high-impact journals. His research interests include deep neural architectures, Gaussian mixture models, ensemble learning, blockchain security frameworks, and energy-efficient AI systems for smart cities. By integrating machine learning with cybersecurity principles, he aims to develop intelligent, robust, and transparent AI solutions capable of safeguarding digital infrastructures while advancing the state of automated recognition and decision-making technologies. His growing body of research reflects innovation, rigor, and a commitment to addressing real-world AI challenges.

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Scopus | ORCID | Google Scholar

Featured Publications 

Oad, A., Farooq, H., Zafar, A., Akram, B. A., Zhou, R., & Dong, F. (2024). Fake news classification methodology with enhanced BERT. IEEE Access, 12, 164491–164502.

Oad, A., Abbas, S. S., Zafar, A., Akram, B. A., Dong, F., Talpur, M. S. H., & Uddin, M. (2024). Plant leaf disease detection using ensemble learning and explainable AI. IEEE Access, 12, 156038–156049.

Oad, A., Ahmad, H. G., Talpur, M. S. H., Zhao, C., & Pervez, A. (2023). Green smart grid predictive analysis to integrate sustainable energy of emerging V2G in smart city technologies. Optik, 272, 170146.

Oad, A., Razaque, A., Tolemyssov, A., Alotaibi, M., Alotaibi, B., & Zhao, C. (2021). Blockchain-enabled transaction scanning method for money laundering detection. Electronics, 10(15), 1766.

Li, Y., Liu, W., Pang, X., Oad, A., Liang, D., Zhang, X., Tang, B., Fang, Z., Shi, Z., & Chen, J. (2024). Microwave dielectric properties, Raman spectra and sintering behavior of low loss La7Nb3W4O30 ceramics with rhombohedral structure. Ceramics International.

Ms. Zunaira Khalid | Biophysics | Best Review Paper Award

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Ms. Zunaira Khalid | Biophysics | Best Review Paper Award

Doctoral Researcher | Xi’an jiaotong university | China

Ms. Zunaira Khalid is an emerging biophysics and biosensing researcher whose work spans advanced biosensor design, nanobiosensors, electrochemical sensing platforms, and organoid-integrated diagnostic systems. Her research integrates interdisciplinary approaches from zoology, molecular biology, and biomedical engineering to develop innovative sensing tools for disease detection and environmental health monitoring. She has contributed to the development of biomimetic olfactory and taste-based biosensing systems, label-free detection strategies, and field-effect transistor sensors aimed at improving point-of-care diagnostics. Her foundational research explored parasitology and epidemiology, particularly the prevalence and transmission dynamics of Taenia multiceps and related metacestodes in domestic livestock—helping inform disease management and public health interventions. Building on strong laboratory expertise, she brings hands-on experience with molecular techniques, PCR-based diagnostics, DNA barcoding, microbial analysis, and ecological assessments, complementing her current focus on biosensor innovation. Her scholarly contributions reflect a growing academic footprint, with publications in international journals covering biosensor advancements, nanotechnology, and parasitological epidemiology. She continues to expand her research visibility through scientific presentations, collaborations, and interdisciplinary projects. Her citation record is gradually growing across platforms, with ongoing updates on Scopus and Google Scholar indexing, citation counts, and h-index metrics as additional documents, publications, and citations are processed. Collectively, her work contributes to next-generation diagnostic technologies and promotes translational applications of biosensing in biomedical and ecological domains.

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Google Scholar

Featured Publications

Khalid, Z., Chen, Y., Liu, X., Noureen, B., Chen, Y., Wang, M., Ma, Y., Du, L., & Wu, C. (2025). Recent advances and unaddressed challenges in biomimetic olfactory and taste-based biosensors: Moving toward integrated AI-powered and market-ready sensing systems. Sensors, 25, 7000.

Khalid, Z., Noureen, B., & colleagues. (2024). Prevalence and epidemiology of coenurosis in domestic bovids of Mianwali, Pakistan. International Journal of Animal Biotechnology.

Khalid, Z., Noureen, B., & colleagues. (2023). Green synthesis of silver nanoparticles and evaluation of their antibacterial activity. International Journal of Cell Science and Biotechnology.

Dr. leila malihi | Knowledge Distillation | Machine Learning Research Award

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Dr. leila malihi | Knowledge Distillation | Machine Learning Research Award

Osnabrück University | Germany

Leila Malihi is a researcher in cognitive science with specialization in computer vision, machine learning, and biomedical image analysis. Her work focuses on developing efficient and controllable deep learning frameworks, particularly model compression techniques such as sequential knowledge distillation and pruning, enabling deployment of high-performance neural networks on edge and resource-limited devices. She has contributed significantly to advancing automated medical image analysis, including wound classification, child face recognition, malaria parasite detection, cancer diagnosis, and ECG signal processing. Her research integrates convolutional neural networks, sparse coding, autoencoders, transfer learning, GAN-based synthetic data generation, and modern pattern-recognition techniques to build interpretable, scalable, and real-time AI systems. She has also explored neural network eigenspaces, principal eigenfeatures, and logistic regression probes to better understand the inner inference behavior of deep models. Leila’s scholarly output reflects her interdisciplinary approach, contributing to journals and international conferences in machine learning, medical informatics, and image processing. Her published work has received 88 Scopus citations from 85 documents, with 10 indexed documents and an h-index of 5, demonstrating a growing impact in the field. On Google Scholar, her research has accumulated 134 citations, with an h-index of 6 and an i10-index of 5, further highlighting the relevance of her contributions to computational healthcare, interpretable AI, and efficient deep learning architectures. Her profile reflects a strong commitment to bridging core AI innovation with real-world biomedical applications.

Profile

Scopus | Google Scholar

Featured Publications

Malihi, L., & Heidemann, G. (2023). Efficient and controllable model compression through sequential knowledge distillation and pruning. Journal of Big Data and Cognitive Computing.

Richter, M. L., Malihi, L., Windler, A. K. P., & Krumnack, U. (2023). Analyzing the inference process in deep convolutional neural networks using principal eigenfeatures, saturation, and logistic regression probes. Journal of Applied Research in Electrical Engineering.

Malihi, L., & Malihi, R. (2020). Single stuck-at faults detection using test generation vector and deep stacked sparse autoencoder. SN Applied Sciences, 2(10), 1–10.

Malihi, L., Ansari-Asl, K., & Behbahani, A. (2015). Improvement in classification accuracy rate using multiple classifier fusion toward computer vision detection of malaria parasite. Jundishapur Journal of Health Sciences, 7(3), 26–32.

Malihi, L., Ansari-Asl, K., & Behbahani, A. (2015). Computer-aided diagnosis of malaria parasite using pattern recognition methods. AJUMS Journals, 14(1), 65–74.

Dr. Soumaya Hechmi | Economics | Best Researcher Award

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Dr. Soumaya Hechmi | Economics | Best Researcher Award

Assistant Professor | Imam Mohammad Ibn Saud Islamic University (IMSIU) | Saudi Arabia

Dr. Soumaya Hechmi is an accomplished finance scholar whose research spans corporate finance, private equity, sustainability economics, and macro-financial analysis. Her work investigates how investment behavior, value creation, corporate performance, and governance mechanisms shape firm-level outcomes across both emerging and developed markets. She has developed a strong empirical orientation, applying advanced econometric techniques such as ARDL, FMOLS, DOLS, CCR, fixed-effects modeling, and quantile regression to study financial dynamics, environmental sustainability, and real-estate market behavior. Her research also explores energy economics, CO₂ emissions, renewable and non-renewable energy interactions, and the role of financial inclusion, trade, tourism, and institutional quality in economic development. Across interdisciplinary contributions, she consistently bridges finance, sustainability, and macroeconomic policy. Dr. Hechmi’s scholarly output includes studies on non-performing loans, bank capital adequacy, technological innovation, human development, and market stability, with publications featured in Scopus-indexed, ESCI-indexed, and ARCIF-indexed journals. Her analytical rigor and consistent contributions have earned measurable academic impact, reflected in Scopus metrics of 19 citations across 4 documents with an h-index of 2, and Google Scholar metrics of 59 citations, an h-index of 4, and an i10-index of 2. Her work is recognized for providing actionable insights for policymakers, investors, and financial institutions. Dr. Hechmi continues to expand her research integrating financial development, sustainability challenges, technological innovation, and economic growth, making her a notable contributor to modern financial and economic scholarship.

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Scopus | ORCID | Google Scholar

Featured Publications 

Hechmi, S. (2025). Beyond sunlight: How CO₂ emissions, coal lock-in, and global finance shape Australia’s solar energy consumption – An ARDL analysis with robustness checks. Economics – Innovative and Economics Research Journal.

Ben Saanoun, I., & Hechmi, S. (2025). How can corporate governance moderate the relationship between private benefits of control and firm performance in the French context? Journal of Cultural Analysis and Social Change.

Hechmi, S. (2025). PropTech in the Saudi real estate market: Case studies of NEOM and Qiddiya. Edelweiss Applied Science and Technology, 9(11), 1087–1095.

Hechmi, S. (2024). Impact of profitability, leverage and corporate governance on value creation: Empirical study of Saudi real estate companies. Open Journal of Business and Management, 12(3), 1403–1410.

Abid, I., Hechmi, S., & Chaabouni, I. (2024). Impact of energy intensity and CO₂ emissions on economic growth in Gulf Cooperation Council countries. Sustainability, 16(23), 10266.

Prof. Wenfeng Ding | Computational Hydrology | Editorial Board Member

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Prof. Wenfeng Ding | Computational Hydrology | Editorial Board Member

Changjiang River Scientific Research Institute | China

Prof. Wenfeng Ding is a distinguished researcher in soil erosion science, hydrodynamics, and watershed environmental processes, with extensive contributions to understanding slope-gully erosion mechanisms, sediment transport, and non-point source pollution. His work focuses on the physical mechanisms that drive soil detachment, sediment yield, and runoff behavior under varying topographic, vegetation, and rainfall conditions. He has advanced the field by integrating experimental hydrodynamics, erosion modeling, fractal soil structure analysis, and GIS-based environmental assessment. His research has played a pivotal role in improving soil and water conservation practices, particularly in the Loess Plateau, the Yangtze River Basin, and purple soil regions of Southwest China. Through sustained scientific inquiry, he has contributed to the development and validation of predictive models across multiple spatial scales, including rill erosion processes, slope-gully couplings, and large watershed sediment dynamics. His studies involving rare earth element tracers, erosion-runoff interaction simulations, and long-term hydrological trend assessments have strengthened the scientific basis for ecological restoration and erosion mitigation in fragile environments. With a substantial body of peer-reviewed publications, Wenfeng Ding has achieved strong scholarly impact, reflected in Scopus metrics of 792 citations across 48 documents with an h-index of 14. His influence extends further on Google Scholar, where his citation counts are typically higher due to broader indexing of regional and conference literature. His research continues to support national efforts in soil conservation, watershed rehabilitation, and sustainable land management.

Profile

Scopus

Featured Publications 

Ding, W., & Alkenbyt, H. (2011). Annual discharge and sediment load variation in Jialing River during the past 50 years. Journal of Mountain Science, 8, 664–676.

Ding, W., & Zhang, P. (2012). Fractal dimension features of soil aggregate distribution with different reclamation years on the Loess Plateau. Sensor Letters, 10, 1–7.

Li, M., Yao, W. Y., Ding, W. F., et al. (2009). Effect of grass coverage on sediment yield in the hillslope-gully side erosion system. Journal of Geographical Sciences, 19, 321–330.

Zhang, X. C., Li, Z. B., & Ding, W. F. (2005). Validation of WEPP sediment feedback relationships using spatially distributed rill erosion data. Soil Science Society of America Journal, 69, 1440–1447.

Li, M., Li, Z. B., & Ding, W. F., et al. (2006). Using rare earth element tracers and neutron activation analysis to study rill erosion processes. Applied Radiation and Isotopes, 64, 402–408.

Prof. Vincenzo Maria Romeo | Psychoanalysis | Innovative Research Award

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Prof. Vincenzo Maria Romeo | Psychoanalysis | Innovative Research Award

Researcher | University of Palermo | Italy

Prof. Vincenzo Maria Romeo, MD, PhD, is an accomplished Italian psychiatrist, clinical psychologist, and psychoanalytic scholar whose research spans addiction medicine, psychopathology, psychopharmacology, body-image disturbance, eating disorders, and psychoanalytic models of subjectivation. His scientific work integrates biological, psychological, and socio-cultural dimensions of mental health, with a consistent focus on complex comorbidities such as substance use, behavioral addictions, depression, schizophrenia, and antisocial behavior in adolescents. He has contributed extensively to understanding the intersections between personality structure, executive functioning, emotional processing, and maladaptive behaviors. His scholarship further explores contemporary psychoanalytic anthropology, post-digital identity formation, and innovative conceptual models for interpreting psychological development and psychopathology. Prof. Romeo’s clinical research includes randomized controlled trials, case studies, and cross-sectional investigations on emerging pharmacological treatments, psychodynamic interpretations, and novel therapeutic approaches for addiction and mood disorders. His contributions to pandemic-related psychiatric research have provided valuable insights into mental health vulnerabilities during social restrictions. He has produced influential work on the psychodiagnostic use of the Rorschach test and has authored notable theoretical contributions including the Tripartite Triangle Model and studies on intermittent attachment. His research output reflects strong academic impact with Scopus reporting 285 citations across 13 documents with an h-index of 7, and Google Scholar listing 617 citations, an h-index of 10, and an i10-index of 10. Prof. Romeo’s interdisciplinary approach positions him as a leading voice advancing integrative, psychodynamic, and evidence-based perspectives in contemporary psychiatry and psychology.

Research Publication Profile

Scopus | ORCID | Google Scholar

Featured Publications 

Muscatello, M. R. A., Bruno, A., Pandolfo, G., Mico, U., Scimeca, G., Romeo, V. M., Santoro, V., Settineri, S., Spina, E., & Zoccali, R. A. (2011). Effect of aripiprazole augmentation in treatment-resistant obsessive-compulsive disorder. Journal of Clinical Psychopharmacology, 31(2), 174–179.

Mico, U., Bruno, A., Pandolfo, G., Maria Romeo, V., Mallamace, D., D’Arrigo, C., Spina, E., & Zoccali, R. A., Muscatello, M. R. (2011). Duloxetine as adjunctive treatment to clozapine in schizophrenia. International Clinical Psychopharmacology, 26(6), 303–310.

Scimeca, G., Bruno, A., Pandolfo, G., Mico, U., Romeo, V. M., Abenavoli, E., Schimmenti, A., Zoccali, R., & Muscatello, M. R. (2013). Alexithymia, negative emotions, and sexual behavior in university students. Archives of Sexual Behavior, 42(1), 117–127.

Bruno, A., Quattrone, D., Scimeca, G., Cicciarelli, C., Romeo, V. M., Pandolfo, G., Zoccali, R. A., & Muscatello, M. R. (2014). Exercise addiction, narcissism, and self-esteem. Journal of Addiction, 2014, 1–6.

Martinotti, G., Alessi, M. C., Di Natale, C., Sociali, A., Ceci, F., Lucidi, L., Picutti, E., Di Carlo, F., Corbo, M., Vellante, F., Tourjansky, G., Catalano, G., Carenti, M. L., Incerti, C. C., Bartoletti, L., Barlati, S., Romeo, V. M., Verrastro, V., De Giorgio, F., … di Giannantonio, M. (2020). Psychopathological burden and quality of life in substance users during COVID-19 lockdown. Frontiers in Psychiatry, 11, 572245.

Dr. Tun Naw Sut | Biotechnology | Best Researcher Award

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Dr. Tun Naw Sut | Biotechnology | Best Researcher Award

Sungkyunkwan University | South Korea

Dr. Sut Tun Naw is a nanomedicine and biomaterials researcher whose work focuses on lipid‐based membrane systems, bio-interfaces, and diagnostic technologies. His scholarly impact is evidenced by strong citation metrics across major databases, including Scopus with more than 787 citations, over 51 indexed documents, and an h-index reflecting sustained contributions to the field. His Google Scholar profile further demonstrates consistent influence with citations approaching 963, an h-index in the high 10, and an extensive record of high-quality publications. Collectively, his research profile highlights significant advancements in supported lipid bilayers, membrane interactions, and nanoscale bioengineering.

Publication Profile

Scopus 

ORCID

Google Scholar

Education Background

Dr. Sut Tun Naw completed a dual doctoral program jointly conferred by Nanyang Technological University in Singapore and Sungkyunkwan University in South Korea, where he conducted interdisciplinary work spanning nanomedicine and chemical engineering. Prior to his doctoral training, he earned a Bachelor of Engineering in Materials Science and Engineering at Nanyang Technological University, where he developed foundational knowledge in biomaterials and surface engineering. His academic journey began with a diploma in biomedical engineering from Ngee Ann Polytechnic, providing him early exposure to medical technologies, diagnostics, and laboratory instrumentation. This integrated academic background enables his cross-disciplinary expertise in nanoscience and biomedical engineering.

Professional Experience

Dr. Sut Tun Naw has developed strong research and engineering competencies through a combination of academic and industry roles. He is currently a postdoctoral fellow at Sungkyunkwan University, where he advances biomimetic lipid membrane systems for biosensing and diagnostic platforms. His earlier experiences at Nanyang Technological University included work as a project officer investigating phospholipid self-assembly and membrane fabrication strategies. He has further contributed to translational research as a research intern at the Institute of Bioengineering and Nanotechnology and held engineering positions in Singapore’s medical technology and manufacturing sectors, where he supported equipment testing, compliance evaluation, and device maintenance.

Awards and Honors

Dr. Sut Tun Naw has been recognized through several competitive distinctions reflecting scientific merit and editorial leadership. His research received support from a national-level Creative Challenge Research Grant awarded by the National Research Foundation of Korea, enabling further development of innovative biomimetic technologies. He contributes to the scholarly community as a guest editor for a special issue on biomimicry and functional materials and serves as a topic editor in the field of membrane science. His academic accomplishments have also been acknowledged by graduate scholarship programs that support outstanding researchers developing advanced chemical and nanotechnology solutions.

Research Focus

Dr. Sut Tun Naw’s research centers on supported lipid bilayers, biomimetic membrane coatings, and nanoscale interactions at solid–liquid interfaces. He investigates how lipid assemblies form, reorganize, and respond to environmental and chemical cues, contributing key insights relevant to biosensors, antiviral strategies, and membrane-based diagnostics. His work also examines protein adsorption, membrane morphology, and the physicochemical behavior of bicelles and fatty-acid systems. Through experimental biophysics, nanofabrication, and surface engineering approaches, he aims to design functional lipid platforms for biomedical detection, molecular analysis, and therapeutic applications. His contributions continue to advance nanomedicine and membrane science.

Top Publications

Sut, T. N., Park, S., Choe, Y., & Cho, N. J. (2019). Characterizing the supported lipid membrane formation from cholesterol-rich bicelles. Langmuir, 35(47), 15063–15070. Cited by approximately thirty-eight articles.

Ferhan, A. R., Yoon, B. K., Park, J. H., Sut, T. N., Chin, H., Jackman, J. A., et al. (2019). Solvent-assisted preparation of supported lipid bilayers. Nature Protocols, 14(7), 2091–2118. Cited by approximately one hundred thirty-nine articles.

Park, J. H., Sut, T. N., Jackman, J. A., Ferhan, A. R., Yoon, B. K., & Cho, N. J. (2017). Controlling adsorption and passivation properties of bovine serum albumin on silica surfaces. Physical Chemistry Chemical Physics, 19(13), 8854–8865. Cited by approximately seventy-eight articles.

Yoon, B. K., Jeon, W. Y., Sut, T. N., Cho, N. J., & Jackman, J. A. (2020). Stopping membrane-enveloped viruses with nanotechnology strategies. ACS Nano, 15(1), 125–148. Cited by approximately seventy articles.

Yoon, B. K., Jackman, J. A., Kim, M. C., Sut, T. N., & Cho, N. J. (2017). Correlating membrane morphological responses with micellar aggregation behavior. Langmuir, 33(11), 2750–2759. Cited by approximately sixty-one articles.

Dr. Samer Younes | Nutrition Pharmacology | Editorial Board Member

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Dr. Samer Younes | Nutrition Pharmacology | Editorial Board Member

Tartous University Syria | Syria

Samer Younes is an emerging pharmacy and nutrition science researcher whose work focuses on the interplay between micronutrients, metabolic disorders, endocrine health, and the pharmacological factors influencing disease outcomes. His research contributions highlight critical insights into diabetes management, nutritional interventions, taste physiology, gastrointestinal health, and gender-based differences in pharmacological response. With a growing scholarly footprint, he has authored multiple peer-reviewed publications in reputable journals in the fields of human nutrition, pharmacology, endocrinology, and metabolic disease research. His scientific work emphasizes evidence-based approaches to improving disease treatment outcomes through targeted nutritional strategies and a deeper understanding of biochemical mechanisms. He has conducted impactful studies on micronutrients in diabetes, nutritional factors in COVID-19 management, the role of B-cell replication in metabolic dysfunction, and gender-related disparities in dietary behavior and pharmacology.His academic contributions are increasingly recognized within the scientific community, reflected in his citation metrics, including an h-index of 5 and i10-index of 3, as indexed by Google Scholar, along with a growing number of citations that demonstrate the relevance and influence of his research. His scholarly output is also traceable across major indexing platforms such as Google Scholar and Scopus, ensuring visibility, credibility, and accessibility of his academic work. Samer Younes continues to build a strong research foundation, contributing to interdisciplinary scientific dialogue while advancing knowledge on nutrition-based therapies, endocrine health, and pharmaceutical sciences. His research trajectory positions him as a promising young scholar committed to developing scientifically grounded solutions for improving health outcomes and supporting global public health advancements.

Profile

Google Scholar

Featured Publications 

Younes, S. (2024). The role of micronutrients on the treatment of diabetes. Human Nutrition & Metabolism, 35, 200238.

Younes, S. (2024). The role of nutrition on the treatment of Covid 19. Human Nutrition & Metabolism, 36, 200255.

Younes, S. (2024). The impact of micronutrients on the sense of taste. Human Nutrition & Metabolism, 35, 200231.

Zyad, A. L. F., Martini, N., Esper, A., Al-Frejat, D., Younes, S., & Hanna, M. (2024). GERD: Latest update on acid-suppressant drugs. Current Research in Pharmacology and Drug Discovery, 7, 100198.

Younes, S. (2024). The relationship between gender and pharmacology. Current Research in Pharmacology and Drug Discovery, 7, 100192.

Mr. Eniyew Eskezia Tiguh | Machinery Engineering | Editorial Board Member

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Mr. Eniyew Eskezia Tiguh | Machinery Engineering | Editorial Board Member

Bahir Dar University | Ethiopia

Eniyew Eskezia Tiguh is an emerging researcher in Agricultural Machinery Engineering and Mechanical Engineering, with a strong scholarly focus on agricultural postharvest systems, sustainable materials, renewable-energy-based drying technologies, and mechanical component performance analysis. His research integrates engineering principles with agricultural innovation, particularly aiming to reduce postharvest losses, enhance crop-processing efficiency, and advance the design of eco-friendly engineering solutions. His contributions address critical challenges related to teff harvesting and drying efficiency, greenhouse solar dryer performance, composite material applications, and gear-material behavior under mechanical load. He also explores engineering education effectiveness, contributing evidence-based insights into learning outcomes in technical fields. He has produced impactful research recognized across international platforms, reflected in Scopus metrics: 3 documents, 9 citations, h-index 2, and Google Scholar metrics: 32 citations, h-index 4, i10-index 2. His growing publication record demonstrates interdisciplinary engagement, combining computational modelling, finite element analysis, and experimental system development for real-world agricultural applications. His work on teff postharvest loss reduction and greenhouse solar dryers has gained notable attention, highlighting his commitment to improving food security through engineering solutions. Overall, his research trajectory reflects a blend of innovation, analytical rigor, and a strong commitment to advancing mechanical and agricultural engineering research.

Profile

Scopus | ORCID | Google Scholar

Featured Publications 

Tiguh, E. E., Delele, M. A., Ali, A. N., Kidanemariam, G., & Fanta, S. W. (2024). Assessment of harvest and postharvest losses of teff and methods of loss reduction. Heliyon, 10(9).

Eskezia, T. D., & Abera, A. (2017). Finite element analysis of internal door panel of a car by considering bamboo fiber reinforced epoxy composite. Journal of Applied Mechanical Engineering, 6(1), 2168–9873.

Tiguh, E. E., Delel, M. A., Ali, A. N., Gelaw, G. K. M., Fanta, S. W., & Bayable, M. (2025). Development and performance evaluation of greenhouse solar dryer for unthreshed teff crops. Results in Engineering, 25, 104495.

Eskezia, E., & Abebaw, M. (2022). Effect of gear materials on the surface contact strength of spur gears. Proceedings of Engineering and Technology Innovation, 22, 50.

Tiguh, E. E. (2021). Investigation of performance of students in engineering drawing in Ethiopian universities. Journal of Engineering and Technology, 12(1), 81–91.