Prof. Dr. Lala Sahondra Rafarasoa | Entomological Monitoring | Best Researcher Award

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Prof. Dr. Lala Sahondra Rafarasoa | Entomological Monitoring | Best Researcher Award

Full Professor | University of Antananarivo | Madagascar

Professor RAFARASOA LalaSahondra is a distinguished Malagasy researcher and academic leader specializing in medical and veterinary entomology, with extensive contributions to the fields of vector control, biodiversity, and environmental health. As Head of the Medical and Veterinary Entomological Laboratory at the Faculty of Sciences, University of Antananarivo, she has significantly advanced the understanding of insect vectors and their ecological and epidemiological roles. Her multidisciplinary research spans national, regional, and international collaborations, integrating medical entomology with agro-ecological and public health frameworks. She has played a key role in major initiatives, including CNRS’s DP SPAD project on sustainable production systems, the IAEA’s regional program on sterile insect techniques for vector management, and NASA/UCAR’s GLOBE ZIKA and MALARIA projects for global mosquito surveillance. A passionate educator and mentor, she has guided numerous undergraduate, postgraduate, and doctoral students while fostering scientific capacity in Madagascar and beyond. Her research output reflects a strong scholarly impact, with Scopus indexing 5 documents, 125 citations, and an h-index of 4, while Google Scholar records additional citations across her collaborative works. Professor Rafarasoa’s contributions demonstrate a vital intersection of entomology, public health, and citizen science, reinforcing her position as a leading figure in global mosquito monitoring and vector-borne disease prevention.

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Featured Publications

Rafarasoa, L. S., Carney, R. M., Azam, F., Gehrisch, K., Bhuiyan, T., Riantsoa, V., Low, R. D., Zohdy, S., Andrianjafy, T. M., & Ramahazomanana, M. A. (2025). Artificial intelligence and citizen science as a tool for global mosquito surveillance: Madagascar case study. Insects, 16(11), 1098.

Assoc. Prof. Dr. Rui Zheng | Management Science | Best Researcher Award

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Assoc. Prof. Dr. Rui Zheng | Management Science | Best Researcher Award

Wuhan University of Technology | China

Assoc. Prof. Dr. Rui Zheng is an accomplished Associate Professor and Master’s Supervisor at the School of Safety Science and Emergency Management, Wuhan University of Technology. Her research focuses on supply chain risk management, social networks in operations management, and emergency logistics network optimization. Dr. Zheng’s scholarly contributions have significantly advanced understanding of consumer behavior, disruption risk, and strategic decision-making in supply chain systems. Her work integrates quantitative modeling, behavioral analysis, and data-driven decision-making to address challenges in sustainable and resilient operations. She has led multiple national and enterprise-funded projects, emphasizing incentive mechanisms, panic buying behavior, and the role of digital technology in enhancing operational efficiency. Dr. Zheng has authored a book titled Product Promotion Strategy Research Based on Social Networks and has published extensively in prestigious journals, including Journal of Cleaner Production, Production and Operations Management, Omega—International Journal of Management Science, and Computers and Industrial Engineering. Her research outputs are widely recognized, with over 201 Scopus citations across 8 indexed publications, an h-index of 4, and a growing academic footprint on Google Scholar.

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featured publications :

Zheng, R., Wang, C. Y., & Yin, S. Q. (2025). Estimating carbon emissions from in-store shopping and timely home delivery of fresh produce: Evidence from China. Journal of Cleaner Production, 501, 145222.

Zheng, R., Shou, B., & Chen, Y. (2023). Differential pricing in social networks with strategic consumers. Production and Operations Management, 00, 1–18.

Zheng, R., Shou, B., & Yang, J. (2021). Supply disruption management under consumer panic buying and social learning effects. Omega—International Journal of Management Science.

Li, Y., Zheng, R., & Guo, J. (2022). Managing disruption risk in competing multitier supply chains. International Transactions in Operational Research.

Zheng, R., Wang, R., & Yang, C. (2020). How consumer valuation heterogeneity impacts firms’ profit: Peer influence makes a difference. Computers and Industrial Engineering.

Dr. Williams Jiménez-García | Vulnerability | Breakthrough Research Award

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Dr. Williams Jiménez-García | Vulnerability | Breakthrough Research Award

Consultant MinJusticia | National University of Colombia | Colombia

Dr. Williams Gilberto Jiménez-García is a Colombian researcher and policy expert specializing in security governance, organized crime, and drug trafficking dynamics. His work integrates criminological theory, spatial analysis, and public policy design to understand violence and institutional responses across Latin America and Europe. With over a decade of academic and governmental experience, his research has focused on developing evidence-based frameworks for understanding criminal markets, territorial governance, and multidimensional indicators for public safety. Jiménez-García’s approach combines quantitative and qualitative methods to examine the spatial dependence of violence, social disorganization, and institutional vulnerability, contributing to both theoretical and applied criminology. His findings have informed innovative public policies and national observatories on crime and security. His scholarly productivity includes more than twenty peer-reviewed publications in high-impact international journals, books, and policy reports. His academic influence is reflected in Scopus with 27 citations across 8 indexed documents and an h-index of 4, while his Google Scholar profile shows 197 citations, an h-index of 8, and an i10-index of 6, evidencing his growing international research visibility.

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Scopus | ORCID | Google Scholar

Featured Publications 

Jiménez-García, W. G. (2025). Why are some drug markets more violent than others? An analysis of violence using fuzzy logic. Social Sciences.
Jiménez-García, W. G. (2025). Espacios de crimen: homicidios, drogas y dependencia espacial en tres ciudades latinoamericanas. Revista Criminalidad.
Jiménez-García, W. G. (2025). Violencia criminal, sociedad y estado: tendencias delictivas y políticas públicas de seguridad. Editorial Atelier.
Jiménez-García, W. G. (2023). Violent drug markets: relation between homicide, drug trafficking and socioeconomic disadvantages. Social Sciences.
Jiménez-García, W. G. (2023). Comprensión del homicidio en las ciudades capitales colombianas: un estudio de vulnerabilidad. Latin American Research Review.

Avraham Lalum | Machine Learning | Best Researcher Award

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Mr. Avraham Lalum | Machine Learning | Best Researcher Award

PhD | University of Córdoba | Israel

Avraham (Avi) Lalum is a distinguished legal scholar and researcher specializing in the intersection of real estate law, artificial intelligence, and conflict resolution. His research explores advanced AI-driven models for risk management in real estate transactions, integrating decision-oriented mediation (DOM), behavioral analytics, and deep learning to enhance investment decision frameworks. Lalum’s scholarly contributions bridge the gap between legal regulation and computational modeling, offering innovative methodologies for explainable AI in property law, negotiation, and human–machine interaction. His studies emphasize how artificial intelligence can simulate human reasoning to mitigate financial risk and promote fairness in high-stakes negotiations. His works are widely recognized in Scopus and Web of Science-indexed journals, contributing significantly to the fields of law, data science, and behavioral AI. With a growing academic impact reflected in over 300 citations and an h-index of 6 on Scopus (and 9 on Google Scholar), Lalum’s publications demonstrate both theoretical depth and practical application in LegalTech and AI ethics.

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ORCID

Featured Publications 

Lalum, A., López del Río, L. C., & Villamandos, N. C. (2024). Synthetic reality mapping of real estate using deep learning-based object recognition algorithms. SN Business & Economics, Springer.
Lalum, A., Caridad López del Río, L., & Ceular Villamandos, N. (2025). Multi-dimensional AI-based modeling of real estate investment risk: A regulatory and explainable framework for investment decisions. Mathematics, MDPI.

 

Mr. Sachin Sravan Kumar Komati | Deep Learning | Best Researcher Award

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Mr. Sachin Sravan Kumar Komati | Deep Learning | Best Researcher Award

AI Engineer | Florida International University | United States

Sachin Sravan Kumar Komati is an accomplished researcher in Artificial Intelligence and Machine Learning, specializing in biomedical applications, particularly in gastrointestinal disease diagnosis, cancer prognosis, and postoperative complication prediction. His research integrates deep learning, computer vision, and multimodal AI frameworks to develop intelligent healthcare solutions. He has contributed significantly to the fields of predictive analytics, medical imaging, and surgical AI, creating advanced models using LSTM, Vision Transformers, and Autoencoders for enhanced diagnostic precision. His works explore AI-driven insights in clinical and imaging datasets, focusing on improving real-time disease detection and patient-specific treatment strategies. Sachin’s scholarly contributions include numerous peer-reviewed publications in reputed international journals such as PLOS One, Gastroenterology, Gastrointestinal Endoscopy, Critical Care Medicine, and the Journal of Clinical Oncology. His research has earned global recognition through multiple conference acceptances, including at ACG, AASLD, and UEG Week. According to Google Scholar, he has received 2 citations, with an h-index of 1 and an i10-index of 0, reflecting his emerging influence in AI-driven healthcare research. His Scopus metrics also indicate growing visibility and scholarly impact. Sachin’s research continues to advance the integration of artificial intelligence into clinical decision-making and medical imaging, aiming to bridge the gap between AI innovation and patient-centered healthcare.

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Google Scholar | ORCID

Featured Publications

Boppana, S. H., Tyagi, D., Komati, S. S. K., Boppana, S. L., Raj, R., & Mintz, C. D. (2025). AI-delirium guard: Predictive modeling of postoperative delirium in elderly surgical patients. PLOS One, 20(6), e0322032.

Boppana, S. H., Thota, M., Maddineni, G., Komati, S. S. K., Aakash, F., & Dang, A. K. (2025). Enhancing gastrointestinal bleeding detection in wireless capsule endoscopy using convolutional autoencoders. American College of Gastroenterology, 120(10S2).

Boppana, S. H., Chitturi, R. H., Komati, S. S. K., Raj, R., & Mintz, C. D. (2025). DiabCompSepsAI: Integrated AI model for early detection and prediction of postoperative complications in diabetic patients using a Random Forest Classifier. Journal of Clinical Medicine, 14(20), 7173.

Boppana, S. H., Thota, M., Maddineni, G., Komati, S. S. K., & Mintz, C. D. (2025). Predictive modeling of GI disease: GastroEndo-Seq for progression and outcome forecasting. Gastroenterology, 120(10S2).

Boppana, S. H., Thota, M., Maddineni, G., Komati, S. S. K., & Mintz, C. D. (2025). Vision Transformer-based framework for risk stratification and prognostic assessment in gastrointestinal lesion management. Gastrointestinal Endoscopy, 120(10S2).

Ms. Maram Almodhwahi | AI Embedded Systems | Best Researcher Award

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Ms. Maram Almodhwahi | AI Embedded Systems | Best Researcher Award

Wright State University | United States

Ms. Maram Abdulaziz Almodhwahi is a dedicated researcher in the field of Computer Science and Engineering with a strong focus on artificial intelligence, embedded systems, and intelligent transportation technologies. Her research primarily explores the development of intelligent driver monitoring systems, emphasizing facial expression recognition and real-time safety enhancement through edge AI deployment on low-power microcontrollers. Her work integrates multimodal sensor fusion and edge computing to enable real-time decision-making for automotive and emergency response applications. Maram has also contributed to the intersection of Artificial Intelligence (AI) and the Internet of Things (IoT), designing efficient and adaptive systems for human-centered computing and safety-critical environments. Her scholarly contributions have been recognized through peer-reviewed journals and conference participation, reflecting a blend of theoretical insight and practical innovation. Her published works are indexed in Scopus and Google Scholar, where she maintains an active research profile with multiple citations, reflecting her growing influence in the areas of embedded AI and human-machine interaction. Her documentation and analytical capabilities are supported by strong technical proficiency in programming, machine learning, and data analysis tools. Maram’s ongoing research aims to enhance autonomous safety systems through adaptive and context-aware AI models, contributing significantly to advancements in intelligent computing for real-world applications.

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ORCID

Featured Publications 

Almodhwahi, M. A., & Wang, B. (2025). A facial expression-aware edge AI system for driver’s safety monitoring. Sensors Journal (MDPI).

Dr. Tosin Oyewole | Biological Systems Engineering | Best Researcher Award

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Dr. Tosin Oyewole | Biological Systems Engineering | Best Researcher Award

Dr. Tosin Oyewole | Postdoctoral Research Associate | University of Nebraska-Lincoln | United States

Dr. Tosin Oyewole is a highly motivated researcher in Agricultural and Biosystems Engineering, specializing in bio-based materials, oil processing, and biopolymer development. Her research focuses on optimizing refining and bleaching processes to enhance the quality and yield of epoxidized vegetable oils such as soybean and hempseed oils. She has extensive expertise in chemical process design, biocomposite fabrication, and characterization techniques including GC, FTIR, and HPLC. Dr. Oyewole’s work integrates chemical engineering principles with agricultural sustainability to produce renewable, high-performance materials aimed at reducing dependency on petroleum-based polymers. She has made significant scholarly contributions through publications and conference presentations in international platforms such as AOCS and ASABE. Her research on biobased epoxy blends and refining optimization has drawn attention within the scientific community, demonstrating the potential of green chemistry in industrial applications. According to Scopus, Dr. Oyewole has 2 indexed documents, 1 citation, and an h-index of 1, reflecting a growing academic impact. Her Google Scholar profile also shows consistent contributions to sustainable bioengineering. She is an active member of professional associations including ASABE, NPA, and the National Society of Black Engineers, emphasizing her dedication to collaborative research and leadership in science and innovation.

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Scopus

Featured Publications 

Oyewole, T., Sarker, N., Dhaliwal, G., Biggane, E., & Monono, E. (2024). Investigating the effect of refining parameters on acetic acid removal and the quality of crude epoxidized soybean oil. Journal of the American Oil Chemists’ Society.

Oyewole, T., Sarker, N., Biggane, E., & Monono, E. (2025). Effect of degumming and bleaching on the yield and quality of epoxidized hempseed oil. Chemical Engineering Journal.

Dimitris Ziouzios | Robotics | Best Researcher Award

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Dr. Dimitris Ziouzios | Robotics | Best Researcher Award

Dr. Dimitris Ziouzios | Researcher | University of Western Macedonia | Greece

Dr. Dimitris Ziouzios is a dedicated researcher at the University of Western Macedonia, whose work spans robotics, embedded systems, and FPGA-based applications. His research emphasizes the integration of intelligent systems with real-world challenges such as environmental sustainability, smart waste management, and educational robotics. With over 23 completed and ongoing research projects, Dr. Ziouzios has made impactful contributions through innovations that merge automation, machine learning, and IoT technologies. His work has led to one patent, numerous collaborations with research institutions and industry partners including CERTH, the University of Wuppertal, and local municipalities, and over 14 publications indexed in SCI and Scopus journals. His research influence is reflected in a Google Scholar record of 514 citations with an h-index of 12, and a Scopus record of 345 citations with an h-index of 10. Beyond his technical research, Dr. Ziouzios contributes to advancing smart city infrastructures and robotics education, promoting environmental awareness and empathy through technology-driven learning. His consistent scholarly output and multidisciplinary collaborations highlight his strong commitment to innovation and applied research excellence.

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Google Scholar

Featured Publications

Ziouzios, D., Tsiktsiris, D., Baras, N., & Dasygenis, M. (2020). A distributed architecture for smart recycling using machine learning. Future Internet, 12(9), 141.

Ziouzios, D., Karlopoulos, E., Fragkos, P., & Vrontisi, Z. (2021). Challenges and opportunities of coal phase-out in western Macedonia. Climate, 9(7), 115.

Ziouzios, D., Baras, N., Balafas, V., Dasygenis, M., & Stimoniaris, A. (2022). Intelligent and real-time detection and classification algorithm for recycled materials using convolutional neural networks. Recycling, 7(1), 9.

Ziouzios, D., Rammos, D., Bratitsis, T., & Dasygenis, M. (2021). Utilizing educational robotics for environmental empathy cultivation in primary schools. Electronics, 10(19), 2389.

Ziouzios, D., Dasygenis, M. (2023). Effectiveness of the IoT in regional energy transition: The smart bin case study. Recycling, 8(1), 28.

 

Prof. Wei Wu | Medicine | Best Researcher Award

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Prof. Wei Wu | Medicine | Best Researcher Award

Prof. Wei Wu | Director | Guangdong Provincial Institute of Public Health Guangdong Provincial Center for Disease Control and Prevention | China

Dr. Wei Wu is a distinguished public health scientist specializing in labor and environmental hygiene, microbial epidemiology, and health data analytics. His research primarily explores the intersection of gut microbiota, metabolic diseases, and public health, employing advanced population cohort and multi-omics data analysis to uncover novel biomarkers and disease risk genes. Dr. Wu’s studies contribute significantly to understanding nutrient–gut flora–host interactions, guiding innovative therapeutic targets for metabolic and infectious diseases. He has also made substantial contributions to vaccine health economics and hygiene assessment in rail transit systems. As a postgraduate supervisor and active member of multiple national scientific committees, Dr. Wu plays a vital role in shaping public health policy and research in China. His impactful scientific output has earned recognition in leading journals, including Nature Medicine and Microbiome. According to Scopus, he has published 35 documents with over 1,577 citations, an h-index of 13, and his work is widely cited across 1,498 documents. On Google Scholar, his publications have similarly received extensive academic engagement, underscoring his global research influence in environmental and preventive health sciences.

Publication Profile

Scopus | ORCID

Featured Publications

He, Y., Wu, W., Zheng, H. M., Li, P., McDonald, D., Sheng, H. F., et al. (2018). Regional variation limits applications of healthy gut microbiome reference ranges and disease models. Nature Medicine, 24(10), 1532–1535.

He, Y., Wu, W., Wu, S., Zheng, H. M., Li, P., Sheng, H. F., et al. (2018). Linking gut microbiota, metabolic syndrome and economic status based on a population-level analysis. Microbiome, 6(1), 172.

Guo, X., Yan, M., Huang, D., Chen, S., Zhang, D., Li, Z., Yang, X., & Wu, W. (2023). A large scale 16S ribosomal RNA gene amplicon dataset of hand, foot and mouth patients and healthy individuals. Scientific Data, 10(48), 1–6.

Yan, M., Guo, X., Ji, G., Huang, R., Huang, D., Li, Z., Zhang, D., Chen, S., Cao, R., Yang, X., & Wu, W. (2023). Mechanism-based role of the intestinal microbiota in gestational diabetes mellitus: A systematic review and meta-analysis. Frontiers in Immunology, 13(3), 1–13.

Wang, H., Luo, L., & Wu, W. (2023). SAS statistical analysis and applications from introduction to mastery (2nd ed.). Posts & Telecom Press.

Dr. Maryam Shojaee | Metabolomic | Best Researcher Award

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Dr. Maryam Shojaee | Metabolomic | Best Researcher Award

Dr. Maryam Shojaee | Physcian Resident | Faculty of Medicine Tehran University of Medical Science | Canada

Dr. Maryam Shojaee is a highly dedicated medical researcher and clinician with a strong background in internal medicine, public health, and clinical research. Her professional journey reflects a dynamic blend of medical practice, research coordination, and scholarly contributions to advancing medical science. She has actively participated in research related to neonatology, infectious diseases, trauma, and public health, with special attention to COVID-19 outcomes, spinal cord injury management, and patient safety. Her experience spans clinical data extraction, literature reviews, and the publication of peer-reviewed articles that explore critical issues in medicine, including pulmonary hypertension, inflammatory biomarkers, and healthcare system challenges. Dr. Shojaee’s research work demonstrates a commitment to integrating clinical practice with academic inquiry to improve diagnostic and therapeutic outcomes. Her publications have collectively gained recognition, earning her 50 citations across 50 documents with an h-index of 2 on Scopus, while her Google Scholar profile reflects growing academic visibility and scholarly impact. She has also contributed to educational mentorship, academic discussions, and multidisciplinary collaborations in healthcare and research institutions. Her ongoing focus lies in translational research, clinical epidemiology, and improving patient-centered care through data-driven studies and evidence-based approaches.

Publication Profile

Scopus

Featured Publications 

Kaveh, M., Mahboobipour, A. A., Bitaraf, A., Shojaei, M., & Mohammadpour Ahranjani, B. (2022). A prospective study of neonates with persistent pulmonary hypertension of the newborn: Prevalence, clinical outcomes, and risk factors. Iranian Journal of Neonatology.

Kheyri, Z., Metanat, S., Hosamirudsari, H., Akbarpour, S., Shojaei, M., Faraji, N., & Mansouri, F. (2022). Neutrophil-to-lymphocyte ratio cut-off point for COVID-19 mortality: A retrospective study. Acta Medica Iranica.

Masoud, S. A., Zahra, G., Habibi, A. R., Zahra, A., Mahdi, S. A., Moein, K., Shojaei, M., & Abbas, R. (2021). Reasons for delayed spinal cord decompression in individuals with traumatic spinal cord injuries in Iran: A qualitative study from the perspective of neurosurgeons. Chinese Journal of Traumatology.

Tabary, M., Ahmadi, S., Amirzade-Iranaq, M. H., Shojaei, M., Asl, M. S., Ghodsi, Z., & Azarhomayoun, A. (2021). The effectiveness of different types of motorcycle helmets: A scoping review. Accident Analysis & Prevention.