Yingmin Chen | Agricultural Engineering | Research Excellence Award

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Assoc Prof Dr. Yingmin Chen | Agricultural Engineering | Research Excellence Award 

Shanxi Agricultural University | China

Associate Professor Yingmin Chen is an accomplished researcher specializing in postharvest engineering, heat and mass transfer, and computational fluid dynamics (CFD) applications in agricultural product cooling systems. He holds a strong academic background that spans physics, optoelectronic materials, and agricultural engineering. Dr. Chen completed his Bachelor’s degree (2010–2014) in Physics and Electronics Science at Hunan University of Science and Technology, followed by a Master’s degree (2014–2016) at the Institute of Optoelectronic Materials and Technology, South China Normal University. His academic journey culminated in a Ph.D. (2018–2021) at the College of Agricultural Engineering, Shanxi Agricultural University, where he developed deep expertise in airflow dynamics, cooling modeling, and fruit storage engineering. Dr. Chen currently serves as an Associate Professor and is the recipient of the Shanxi Provincial Basic Research Program – Young Scientist Research Project (Jan 2023–Dec 2025) for his pioneering study titled “Study on Heat and Mass Transfer Process During Forced-Air Cooling of Peaches Based on Fluid-Structure Interaction Simulation.” His project focuses on understanding and optimizing the forced-air cooling process of peaches, integrating CFD techniques and fluid–structure interaction models to enhance cooling efficiency, quality preservation, and energy consumption in postharvest handling. He has produced a series of influential publications in high-quality journals, contributing significantly to the field of fruit cooling technologies. His works include a comprehensive analysis of air-flow velocity on peach precooling efficiency using CFD, published in the International Food Research Journal (2022); simulation and model verification of forced-air cooling under varying air supply temperatures, published in INMATEH – Agricultural Engineering (2021); and a detailed sensitivity analysis of heat and mass transfer characteristics under different air-inflow velocities, featured in Food Science & Nutrition (2020). His more recent publications, such as his 2024 and 2025 papers in Food Science, investigate ventilation modes and differential pressure precooling efficiency for packaged and layered peaches, advancing theoretical understanding and practical solutions for postharvest cooling systems. Through his multidisciplinary training and growing research impact, Associate Professor Chen has established himself as a leading young scholar in agricultural product cooling technology. His work supports improvements in supply chain efficiency, fruit quality preservation, and sustainable postharvest engineering practices. He continues to integrate advanced simulation technologies and practical engineering design to address real-world challenges in agricultural logistics and cold-chain management.

Profile: Orcid

Featured Publications

Chen, Y. (2024). Effect of vent mode on the differential pressure pre-cooling efficiency of layered peaches. Food Science, 45(3), 150–158.

Chen, Y., Song, H., & Su, Q. (2022). Multi-parameter analysis of air flow velocity on peach precooling efficiency using CFD. International Food Research Journal, 29(2), 456–465. https://doi.org/10.47836/ifrj.29.2.22

Chen, Y., Song, H., & Su, Q. (2021). CFD-based simulation and model verification of peaches forced air cooling on different air supply temperatures. INMATEH – Agricultural Engineering, 63(1), 61–72. https://doi.org/10.35633/inmateh-63-06

Chen, Y., Song, H., Chen, Z., Zhao, R., Su, Q., Jin, P., Sun, Y., & Wang, H. (2020). Sensitivity analysis of heat and mass transfer characteristics during forced-air cooling process of peaches on different air-inflow velocities. Food Science & Nutrition, 8(12), 6592–6602. https://doi.org/10.1002/fsn3.1951

Friday Benedict | Predictive Analytics | Worldwide Research and Innovation Data Excellence Award

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Mr. Friday Benedict | Predictive Analytics | Worldwide Research and Innovation Data Excellence Award

Ahmadu Bello University, Zaria | Nigeria

Benedict Friday is a dedicated chemist and educator whose academic and professional journey reflects a strong commitment to scientific advancement, teaching excellence, and community impact. He is currently pursuing a Master of Science degree in Physical Chemistry at Ahmadu Bello University, Zaria, where he also completed a Professional Diploma in Education after earning a Bachelor of Science in Chemistry with Second Class Upper Division from the Federal University of Agriculture, Makurdi. His experience spans teaching roles at secondary schools and part-time laboratory demonstration at the university level, where he supports undergraduate practical sessions in Chemistry. Beyond academia, he has gained administrative and organizational experience working as a Fleet Officer in the transport division of a major cement company, as well as field experience in telecommunications marketing and water treatment laboratory operations. His research interests include physical chemistry, environmental chemistry, water quality analysis, and material science. Known for teamwork, communication skills, creativity, and leadership, he continues to develop professionally through teaching, research, and community engagement. He remains committed to contributing innovative solutions to scientific and educational challenges while advancing knowledge in the chemical sciences.

Profile : Orcid

Featured Publication

Design and screening of novel geniposide derivatives as xanthine oxidase inhibitors for hyperuricemia treatment using QSAR, Molecular docking, Molecular dynamics simulation, ADMET, and DFT Approaches, 2025.

Limin Xiao | Healthcare and Transformative Tourism | Research Excellence Award

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Ms. Limin Xiao | Healthcare and Transformative Tourism | Research Excellence Award

Sun Yat-sen University | China

Limin Xiao is a dedicated and emerging scholar in tourism management, currently serving as a visiting Ph.D. student funded by the prestigious China Scholarship Council (CSC). She is pursuing her doctoral studies at the School of Business, Sun Yat-sen University—one of China’s leading institutions under Project 985—where she specializes in tourism management with a focus on transformative experiences and AI service applications in tourism. Born in Wuhan in December 1999, Limin has built a strong interdisciplinary academic foundation that integrates business administration, English studies, and tourism research. She completed her dual bachelor’s degrees in English and Business Administration at the School of Foreign Languages, China University of Geosciences (Project 211), where she ranked first in her school with a GPA of 4.13/5.0 and earned direct admission to postgraduate study. Limin’s research trajectory is marked by a deep interest in how tourists experience transformation, particularly within cultural, wellness, and digitally empowered tourism contexts. She has contributed to several high-quality publications, including an accepted paper in Tourism Management Perspectives and ongoing submissions to Tourism Tribune and the International Journal of Contemporary Hospitality Management. Her early research in translation studies has also appeared in Overseas English. Limin has presented her work at major academic conferences such as MTCON’23 in Istanbul, APMA 2023 in Guangzhou, the China Marketing Science Conference, and the China Tourism Research Annual Conference. Her scholarship demonstrates a robust theoretical grounding, drawing from self-expansion theory, liminality, embodiment cognition, and narrative persuasion models. She is simultaneously advancing multiple working papers that examine topics such as cultural tourism employees’ self-expansion, immersive digital-empowered tourism, and AI-driven storytelling for cultural identity formation. Her academic excellence has been consistently recognized through numerous national and international awards, including the highly competitive National Scholarship (top 0.2%), Meritorious Winner in the Mathematical Contest in Modeling (top 8%), first prizes in multiple national English competitions, and a professional qualification in translation (CATTI Level 3). She has also received honors for research innovation and academic presentation, including the Outstanding Final Report Award from the Ministry of Education and the Outstanding Paper Award at the 2024 Annual Forum on Frontiers of Tourism Research. With strong analytical skills, interdisciplinary training, and growing expertise in transformative tourism and AI-enabled visitor engagement, Limin Xiao represents a promising young researcher contributing innovative insights to the global tourism scholarship community.

Profile: Scopus

Featured Publications

Han, X., Zheng, Y., Wu, J. (Snow), & Xiao, L. (2025). Transformative value in cultural tourism: Scale development and its impact on tourist eudaimonic well-being. Tourism Management Perspectives. (Accepted February 2025)

Han, X., Zheng, Y., & Xiao, L. (n.d.). The effect of tourists’ initiative in wellness tourism on perceived transformation: From a perspective of transformative tourism. Tourism Tribune. (Second round of review)

Han, X., Liu, H., Xiao, L., & Zheng, Y. (n.d.). More innovative, more popular? The effect of amenity innovation on customers’ booking intentions in P2P accommodation. International Journal of Contemporary Hospitality Management. (Awaiting review)

Xiao, L. (2020). The translation of tourist attraction descriptions from the perspective of eco-translatology: A case study of the Hubei Provincial Museum. Overseas English, 2020(6), 65–66.

Zitong Gao | Big data Integration | Research Excellence Award

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Ms. Zitong Gao | Big data Integration | Research Excellence Award

Dalian University | China

Ms. Zitong Gao is a dedicated nursing graduate student specializing in quantitative research methodologies within the field of chronic disease management. Building on a Bachelor of Science in Nursing and currently pursuing a Master of Science in Nursing at Dalian University, she has developed a strong academic foundation in nursing theories, advanced health assessment, geriatric nursing, and evidence-based practice. Her research experience includes participating in quantitative studies, collecting and analyzing data, and contributing to the development of academic manuscripts. In addition to her research background, she completed a comprehensive clinical internship at a university-affiliated hospital, where she gained hands-on experience in internal medicine, surgery, and holistic patient care through assessment, care planning, implementation, and evaluation. Skilled in statistical software such as SPSS, Mplus, Excel, and Stata, she integrates data-driven approaches into her research work. Her professional interests focus on improving patient outcomes, chronic disease self-management, gerontological nursing, and advancing nursing practice through rigorous quantitative inquiry. She has earned her nurse qualification certificate, demonstrating a solid commitment to professional standards in clinical care. With a strong blend of academic training, research competence, and clinical experience, she aims to contribute meaningfully to nursing science and patient-centered healthcare advancements.

Profile : Orcid

Featured Publication

Latent transition of social participation and its relationship with frailty among older adults with chronic non-communicable diseases in China: A national longitudinal study, 2025

Myeong-Ho Yeo | Environmental Data Analysis | Research Excellence Award

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Assoc. Prof. Dr. Myeong-Ho Yeo | Environmental Data Analysis | Research Excellence Award

University of Guam | Guam

Dr. Chris (Myeong-Ho) Yeo is a tenured Associate Professor of Water Engineering and Hydrology and Chair of the Environmental Science Graduate Program at the University of Guam. He holds a Ph.D. in Civil Engineering and Applied Mechanics from McGill University, and M.S. and B.S. degrees in Environmental Engineering from Chungnam National University. His research focuses on water quality monitoring and modeling, stormwater and flood management, climate change adaptation and mitigation, and the fate and transport of land-based pollutants, particularly in coastal and island ecosystems. Dr. Yeo has extensive experience developing computational fluid dynamics (CFD) models, statistical downscaling, stochastic rainfall modeling, and integrated watershed management tools. He has led numerous research projects for agencies including USGS, NASA, FEMA, and the Department of Defense, contributing to long-term monitoring of coral reef and freshwater resources across Guam, CNMI, and FSM. He is recognized for his scientific leadership, earning the Triton Faculty of the Year Award and holding Professional Engineer licensure in Environmental Engineering. His work integrates applied research with community resilience, sustainable water management, and climate-informed decision-making. Through his scholarship, teaching, and service, Dr. Yeo advances the understanding and management of water resources under climate variability, supporting sustainable environmental planning and the protection of coastal and freshwater systems in the Pacific region.

Profile : Orcid

Featured Publications

Yeo, M.-H., Kim, Y.S., Houk, P., Chang, A., & Lugwid, A. (2026). Ridge-to-reef linkages in Apra Harbor, Guam describe spatial and temporal variation in water quality and coral reef assemblages. Marine Pollution Bulletin.

Yeo, M.-H., Patil, U.D., Chang, A., & King, R. (2023). Changing Trends in Temperatures and Rainfalls in the Western Pacific: Guam. Climate.

Yeo, M.-H., Nguyen, V.-T.-V., Kim, Y.S., & Kpodonu, T.A. (2022). An Integrated Extreme Rainfall Modeling Tool (SDExtreme) for Climate Change Impacts and Adaptation. Water Resources Management.

Yeo, M.-H., Pangelinan, J., & King, R. (2022). Identifying Characteristics of Guam’s Extreme Rainfalls Prior to Climate Change Assessment. Water.

Yeo, M.-H. (corresponding author), et al. (2021). Application of a SWAT Model for Supporting a Ridge-to-Reef Framework in the Pago Watershed in Guam. Water, 13(23), 3351.

Xiaoxia Yu | Data Analysis Innovation |  Best Scholar Award  

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Mr. Xiaoxia Yu | Data Analysis Innovation |  Best Scholar Award  

Chongqing University of Technology | China

Dr. Xiaoxia Yu is a scholar in mechanical engineering whose work advances intelligent diagnostics and predictive maintenance for large-scale rotating machinery, particularly wind turbines. With a Ph.D. in Mechanical Engineering and earlier degrees in Vehicle Engineering and Armored Vehicle Engineering, she has built a strong interdisciplinary foundation that integrates mechanical systems knowledge with advanced computational modeling. Her research spans fault diagnosis, health assessment, digital twin systems, graph neural networks, reinforcement learning, and signal processing, supported by a growing publication record that includes 29 documents, 477 citations by 448 documents, and an h-index of 7. As a Lecturer, she leads research projects funded by regional scientific agencies and has contributed to national-level R&D initiatives related to machinery health management. Her work appears in high-impact journals, and she has secured patents focused on structural health monitoring, image recognition, and intelligent fault detection. Recognized with competitive grants and academic honors, she continues to influence the fields of renewable energy reliability and smart manufacturing. Through her commitment to innovation, research leadership, and engineering application, she is emerging as a key contributor to the development of intelligent, data-driven mechanical health monitoring systems.

Profiles : Scopus | Orcid | Google Scholar

Featured Publications

Yu, X., Tang, B., & Zhang, K. (2021). Fault Diagnosis of Wind Turbine Gearbox Using a Novel Method of Fast Deep Graph Convolutional Networks. IEEE Transactions on Instrumentation and Measurement, 70, 1–14.

Yu, X., Tang, B., & Deng, L. (2023). Fault Diagnosis of Rotating Machinery Based on Graph Weighted Reinforcement Networks Under Small Samples and Strong Noise. Mechanical Systems and Signal Processing, 186, 109848.

Zhang, K., Tang, B., Deng, L., & Yu, X. (2021). Fault Detection of Wind Turbines by Subspace Reconstruction‑Based Robust Kernel Principal Component Analysis. IEEE Transactions on Instrumentation and Measurement, 70, 1–11.

Li, B., Tang, B., Deng, L., & Yu, X. (2020). Multiscale Dynamic Fusion Prototypical Cluster Network for Fault Diagnosis of Planetary Gearbox Under Few Labeled Samples. Computers in Industry, 123, 103331.

Xiong, P., Tang, B., Deng, L., Zhao, M., & Yu, X. (2021). Multi‑block Domain Adaptation with Central Moment Discrepancy for Fault Diagnosis. Measurement, 169, 108516.

Umme Habiba | Machine Learning and AI Applications | Research Excellence Award

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Mrs. Umme Habiba | Machine Learning and AI Applications | Research Excellence Award

North Dakota State University(NDSU) | United States

Umme Habiba is a dedicated researcher and educator in computer science whose work centers on machine learning, deep learning, transformer-based architectures, explainable AI, and swarm intelligence, particularly within medical data analysis. She is pursuing her Ph.D. and M.Sc. in Computer Science at North Dakota State University, where she has gained extensive teaching experience as an instructor of record and graduate teaching assistant across several undergraduate courses. Her research contributions span clinical text mining, medical risk prediction, brain–computer interface modeling, IoT security, and usability analysis of mHealth applications, with publications in reputable international journals. She has also collaborated on projects involving mobile sensor–based spatial analysis, voice-controlled IoT automation systems, and hybrid ML models for network intrusion detection. Her academic journey began with a bachelor’s degree in Computer Science and Engineering, where she developed a strong foundation in data-driven system design and intelligent applications. She has received consistently high teaching evaluations and has demonstrated a commitment to interdisciplinary research and student learning. Her long-term goal is to contribute impactful solutions at the intersection of artificial intelligence and healthcare while advancing as both a researcher and an educator.

Profile : Orcid

Featured Publication

PSO-optimized TabTransformer architecture with feature engineering for enhanced cervical cancer risk prediction, 2026

Skye Playsted | Educational Data Analysis | Best Researcher Award

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Ms. Skye Playsted | Educational Data Analysis | Best Researcher Award

The University of Queensland | Australia

Skye Playsted is an academic educator and researcher in TESOL and literacy education whose work integrates classroom experience, practitioner research, and reflective pedagogy. She holds qualifications including a PhD candidature, MEd, PGDipEd, BA, and Cert IV TAE, and has taught extensively across Australian universities such as the University of Queensland, University of New England, University of Wollongong, and the University of Southern Queensland. Her academic experience includes coordinating and teaching a wide range of undergraduate and postgraduate courses in English, TESOL, literacy, and curriculum studies, as well as contributing to preservice teacher development. As a research assistant, she has collaborated on projects examining education privatisation, co-teaching, and university student engagement. Her research focuses on pronunciation teaching, practitioner inquiry, LESLLA contexts, teacher professional learning, and translanguaging-informed pedagogies, with publications in leading journals and edited collections. She has served in numerous professional, volunteer, and peer-review roles and has delivered many national and international conference presentations. Recognised with multiple awards—including a Higher Education Academy Fellowship and several prestigious scholarships—she is committed to inclusive, evidence-based education. With 5 documents, 13 citations by 13 documents, and an h-index of 2, she continues to expand her scholarly contributions while supporting future educators.

Profiles : Scopus | Orcid

Featured Publications

Playsted, S., & Thomas, D. P. (2026). “Language teachers regaining a sense of praxis in pronunciation teaching and learning through Exploratory Practice as professional learning in Australia” in System.

Playsted, S., Fortier, V., & Beaulieu, S. (2025). “Classroom-based Research in LESLLA Contexts: Methodological Challenges and Affordances” in Proceedings of the 20th Anniversary LESLLA Symposium.

Playsted, S. (2025). “Planning with a model text to integrate speaking and listening into English language lessons” in English Australia Journal.

Playsted, S., Thomas, D. P., & Wilkinson, J. (2024). “Exploratory practice puzzling as praxis-oriented pronunciation teacher learning in Australian adult migrant EAL education” in Language Teaching Research.

Playsted, S. (2024). “Book review of Guskaroska, A., Zawadzki, Z., Levis, J., Challis, K., & Prikazchikov, M. (2024). Teaching pronunciation with confidence. Iowa State University.” in TESOL in Context.

Diamant Thaci | Emerging Research Trends | Best Researcher Award

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Prof. Dr. Diamant Thaci | Emerging Research Trends | Best Researcher Award

Universität zu Lübeck | Germany

Prof. Dr. med. Diamant Thaçi is a leading dermatologist and inflammation medicine expert whose career spans clinical practice, translational research, and academic leadership. After completing a postdoctoral fellowship and receiving a DAAD Scholarship for highly talented young scientists, he specialized in dermatology and venereology and advanced through key roles at J.W. Goethe University Frankfurt, including Senior Physician for dermatological clinical research and chronic inflammatory skin diseases. He later earned his venia legendi and held a W2 Professorship before assuming major leadership positions at the University of Lübeck, where he currently directs the Institute for Inflammation Medicine, the Excellence Center for Inflammation Medicine, and the Inflammation Board. His research focuses on atopic dermatitis, psoriasis, psoriatic arthritis, and novel immunomodulatory therapies, contributing extensively to pivotal international clinical trials. With 379 documents, 20,448 citations by 13,334 documents, and an h-index of 68, he is recognized as a Highly Cited Researcher and serves on multiple international councils and editorial boards. His awards include the Theodor Stern Foundation Prize and multiple distinctions from EADV and other societies. Overall, he is regarded as one of the most influential figures in modern inflammation and dermatology research.

Profiles : Scopus | Orcid

Featured Publications

Curman, P., Thaçi, D., & Ludwig, R. J. (2025). “Increased Cardiovascular Risk in Chronic Spontaneous Urticaria: A Large Real-World Cohort Study” in Allergy.

Lebwohl, M., Gooderham, M. J., Warren, R. B., Thaçi, D., Foley, P., Gottlieb, A. B., Torres, T., Popmihajlov, Z., Jou, Y.-M., Linaberry, M., et al. (2025). “Outcomes of Psoriasis Area and Severity Index (PASI) and PASI components in two phase III trials of deucravacitinib in patients with moderate to severe plaque psoriasis” in Clinical and Experimental Dermatology.

Olbrich, H., Kridin, K., Zirpel, H., Hernandez, G., Sadik, C. D., Gaffal, E., Thaçi, D., & Ludwig, R. J. (2025). “Glucagon-like peptide-1 receptor agonists and reduced mortality, cardiovascular and psychiatric risks in patients with psoriasis: a large-scale cohort study” in British Journal of Dermatology.

Alfarsi, S., Recke, A., Gaffal, E., Klein, J. P., Zirpel, H., Kridin, K., Thaçi, D., Olbrich, H., Bieber, K., & Ludwig, R. J. (2025). “Increased risk of psychiatric disease in patients with prurigo nodularis” in British Journal of Dermatology.

Thaçi, D., Ohtsuki, M., Maul, J.-T., Szegedi, A., Luna, P. C., Lynde, C. W., Soliman, A. M., Wang, H., Kaufmann, C., Ashley, D. G., et al. (2025). “Correction: Real-World Effectiveness of Risankizumab in Patients with Moderate-to-Severe Psoriasis: Interim Analysis from the VALUE Global Prospective Post-marketing Observational Study at 25 Months” in Dermatology and Therapy.

Almudena García-García | Climate Change Data Analysis | Best Researcher Award

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Dr. Almudena García-García | Climate Change Data Analysis | Best Researcher Award

Helmholtz Centre for Environmental Research – UFZ | Germany

Dr. Almudena García-García is a scientist specializing in remote sensing and environmental sciences, currently affiliated with the Helmholtz Centre for Environmental Research (UFZ) and the Remote Sensing Centre for Earth System Research at Leipzig University. She earned her Ph.D. in Environmental Science from Memorial University of Newfoundland and St. Francis Xavier University, following an M.Sc. in Earth Sciences and a B.Sc. in Physics. With extensive experience as a course and lab instructor, research assistant, and project manager, her work focuses on climate extremes, soil heat dynamics, hydrology, and biodiversity under changing environmental conditions. Dr. García-García has led and contributed to multiple national and international research projects, including DFG-funded studies on soil heat extremes and ESA’s 4DHYDROLOGY initiative. She has co-authored numerous high-impact peer-reviewed publications on soil moisture, transpiration, land-surface modeling, and Earth observation data integration. Recognized for her scientific excellence, she has received the Governor General Graduate Medal, the Moire A. Wadleigh Award, and a nomination to the 73rd Lindau Nobel Laureate Meeting. Dr. García-García has supervised bachelor, master, and Ph.D. students, fostering the next generation of environmental scientists. Her research combines remote sensing, Earth system modeling, and observational data to better understand the impacts of climate variability and extremes on terrestrial and hydrological systems.

Profile : Orcid

Featured Publications

Beltrami, H., González-Rouco, J. F., Peng, J., Cuesta-Valero, F. J., García-García, A., & García-Pereira, F. (2025, November 12). Robust increase in observed heat storage by the global subsurface. Science Advances.

Mahecha, M. D., Bastos, A., Bohn, F. J., Eisenhauer, N., Feilhauer, H., Hickler, T., Kalesse-Los, H., Migliavacca, M., Otto, F. E. L., Peng, J., et al. (2024). Biodiversity and climate extremes: Known interactions and research gaps. Earth’s Future.

Garcia-Pereira, F., Gonzalez-Rouco, J. F., Melo-Aguilar, C., Steinert, N. J., Garcia-Bustamante, E., de Vrese, P., Jungclaus, J., Lorenz, S., Hagemann, S., Cuesta-Valero, F. J., et al. (2024). First comprehensive assessment of industrial-era land heat uptake from multiple sources. Earth System Dynamics, 15, 547–2024.

Garcia-Pereira, F., Gonzalez-Rouco, J. F., Schmid, T., Melo-Aguilar, C., Vegas-Canas, C., Steinert, N. J., Roldan-Gomez, P. J., Cuesta-Valero, F. J., Garcia-Garcia, A., & Beltrami, H., et al. (2024). Thermodynamic and hydrological drivers of the soil and bedrock thermal regimes in central Spain. Soil, 10, 1–2024.

Meng, X., Hu, J., Peng, J., Li, J., Leng, G., Ferhatoglu, C., Li, X., Garcia-Garcia, A., & Yang, Y. (2024). Validation and expansion of the soil moisture index for assessing soil moisture dynamics from AMSR2 brightness temperature.