Assylbek Jomartov | Robot simulator | Robotics Achievement Award

Prof. Assylbek Jomartov | Robot simulator | Robotics Achievement Award

Joldasbekov Institute of Mechanics and Engineering | Kazakhstan

Prof. Assylbek Jomartov is a researcher at the Institute of Mechanics and Engineering named after Academician U. A. Dzholdasbekov, Kazakhstan, specializing in mechanical engineering, robotics, and dynamic system modeling, with a strong focus on parallel and cable-driven robotic systems. His research addresses the design, dynamics, and experimental validation of advanced robotic mechanisms, including applications in earthquake simulation, industrial mixing systems, and medical robotics. He has authored 45 publications, receiving 125 citations with an h-index of 6, and has collaborated with 42 co-authors, reflecting broad international engagement. His work contributes to safer engineering systems, robotics-based medical solutions, and applied mechanical innovation with tangible societal and technological impact.

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Mehdi Hosseini Chagahi | Medical Imaging | Research Excellence Award

Dr. Mehdi Hosseini Chagahi | Medical Imaging | Research Excellence Award

University of Tehran | Iran

Dr. Mehdi Hosseini Chagahi is a researcher affiliated with the University of Tehran, specializing in financial data science, artificial intelligence, and cryptocurrency market forecasting. His work focuses on advanced deep learning architectures, particularly transformer-based and multimodal fusion frameworks that integrate market data with sentiment signals for trend prediction. He has authored 2 publications, accumulating 9 citations, with an h-index of 1, reflecting emerging scholarly impact. His recent open-access publication in IEEE Access (2025) demonstrates methodological innovation in cross-attention modeling. Through interdisciplinary collaboration at the intersection of AI and fintech, his research contributes to improved decision-support systems and broader societal understanding of digital financial markets.

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9

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Muhammad Nadeem Ali | Intrution Detection | Research Excellence Award

Mr. Muhammad Nadeem Ali | Intrution Detection | Research Excellence Award

Hongik University | South Korea

Mr. Muhammad Nadeem Ali is an emerging researcher in computer science and information engineering, with a focus on cybersecurity, intrusion detection systems, explainable artificial intelligence (XAI), optimization algorithms, and smart urban mobility solutions. He has authored 26 peer-reviewed publications, receiving 132 citations with an h-index of 6, reflecting steady scholarly impact. His recent work emphasizes interpretable AI models, such as bio-inspired optimization for secure and transparent cyber systems, alongside surveys on sustainable smart transportation. Affiliated with Hongik University, South Korea, he has collaborated with 49 international co-authors, demonstrating strong global research engagement. His research contributes to enhanced digital security, intelligent systems, and socially sustainable urban technologies.

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132

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Yu’e Cha | Population Health | Research Excellence Award

Assoc. Prof. Dr. Yu’e Cha | Population Health | Research Excellence Award

The National Institute of Environmental Health | China

Assoc. Prof. Dr. Yu’e Cha is a researcher at the Chinese Center for Disease Control and Prevention specializing in environmental health and exposomics, with a focus on how chemical exposures influence endocrine function and women’s reproductive health. With 12 scientific publications, 7 h-index and 176 citations, she has contributed meaningful insights into population-level exposure profiling using advanced high-resolution analytical techniques. Her work, including a recent open-access study in Environment International examining associations between chemical mixtures and sex hormones in women of childbearing age, demonstrates methodological strength in untargeted exposomic analysis and evidence-based assessment of environmental risks. Collaborating with nearly 100 co-authors, she participates in large, interdisciplinary research networks that advance environmental epidemiology and public-health science. Cha’s contributions support improved risk evaluation, inform chemical-safety policies, and enhance understanding of environmental determinants of health, thereby promoting better health outcomes for vulnerable populations and strengthening global public-health protection.

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Zeng Xiangjin | Robot | Best Academic Researcher Award

Prof. Dr. Zeng Xiangjin | Robot | Best Academic Researcher Award

Professor | Wuhan Institute of Technology | China

Prof. Dr. Xiangjin Zeng is a researcher at the Wuhan Institute of Technology specializing in computer vision, deep learning, and intelligent image processing. His work focuses on advanced techniques for super-resolution, object detection, infrared imaging, and image captioning, integrating attention mechanisms and modern CNN–Transformer architectures. He has authored 37 publications with 165 citations and 6 h-index, reflecting growing global recognition. Dr. Zeng has collaborated with over 30 co-authors, contributing to multidisciplinary advancements in multimedia applications and AI-driven visual analysis. His research supports practical innovations in surveillance, smart imaging systems, and human–machine interaction, strengthening the societal impact of next-generation visual technologies.

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165

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37

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6

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Bellel Nadir | Renewable Energy | Best Researcher Award

Prof. Bellel Nadir | Renewable Energy | Best Researcher Award

Dean | University of Constantine 1 | Algeria

Prof. Bellel Nadir is a multidisciplinary researcher specializing in sustainable materials, thermal–fluid systems, and energy-efficient engineering solutions. With a portfolio of 20 scientific publications, 126 citations and 7 h-index, his work advances bio-based construction materials and solar-driven thermal technologies. Notable contributions include the development of lightweight bio-concretes using agricultural waste and optimized CFD-based designs for solar concentrator systems. His research is strengthened by collaborations with more than 20 international co-authors, reflecting broad academic engagement. Bellel’s work supports global sustainability goals by promoting renewable-energy applications, valorizing biomass residues, and improving eco-friendly construction practices, thereby offering measurable environmental and societal benefits.

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Eleonora Lorenza Zich | Quantum Computing | Research Excellence Award

Ms. Eleonora Lorenza Zich | Quantum Computing | Research Excellence Award

Politecnico di Milano | Italy 

Ms. Eleonora L. Zich is a researcher at the Politecnico di Milano, focusing on computational electromagnetics and advanced optimization methodologies. Her work integrates evolutionary algorithms, quantum-inspired computing, and numerical modeling to address complex electromagnetic design problems with enhanced efficiency and precision. Zich has authored 8 scientific publications, which have collectively received 8 citations, contributing to an h-index of 2, reflecting a developing yet increasingly recognized research trajectory. A notable example of her recent work is the 2025 article “Quantum Selection for Genetic Algorithms Applied to Electromagnetic Design Problems,” which demonstrates her commitment to innovating optimization frameworks for engineering applications. By incorporating quantum-based selection mechanisms into genetic algorithms, she advances computational strategies that can significantly improve the performance of electromagnetic design workflows. Zich collaborates with ten co-authors, indicating active participation in interdisciplinary research networks spanning electrical engineering, applied physics, and computational sciences. These collaborations enhance the breadth and applied relevance of her contributions, particularly in fields such as telecommunications, sensing technologies, and electronic component optimization. Through her focus on algorithmic innovation and computational efficiency, Zich’s work supports the development of advanced tools that have the potential to influence both academic research and industrial technological progress.

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Tamanna Yasmin | Neuroscience | Tech Advancement Award

Ms. Tamanna Yasmin | Neuroscience | Tech Advancement Award

Ph.D Researcher | Korea Institute of Science and Technology | South Korea

Ms. Tamanna Yasmin, affiliated with the Korea Institute of Science and Technology, conducts interdisciplinary research at the interface of neurobiology, metabolism, and natural-product pharmacology. Her work focuses on understanding how metabolic modulation affects neuronal excitability and energy homeostasis, with particular emphasis on obesity and metabolic disorders. She has demonstrated the therapeutic potential of bioactive compounds, such as gintonin from Korean red ginseng, in preclinical models, bridging natural-product research with neuroscience and metabolic disease. To date, she has authored 3 peer-reviewed publications, which have collectively received 67 citations and contributed to an h-index of 1, reflecting a growing impact within the scientific community. Collaborating across disciplines including pharmacology, nutrition, and biomedical sciences, she advances both fundamental knowledge and translational approaches for metabolic and neurophysiological health. Her work holds promise for developing innovative, physiology-based interventions that address global challenges in metabolic disorders, obesity, and brain-body health.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. Nam, Y. H., Hong, B. N., Rodriguez, I., Park, M. S., Jeong, S. Y., Lee, Y.-G., Shim, J. H., Yasmin, T., Kim, N. W., Koo, Y. T., Lee, S. H., Paik, D.-H., Jeong, Y. J., Jeon, H., Kang, S. C., Baek, N.-I., & Kang, T. H. (2020). Steamed Ginger May Enhance Insulin Secretion through KATP Channel Closure in Pancreatic β-Cells Potentially by Increasing 1-Dehydro-6-Gingerdione Content. Nutrients, 12(2), 324. https://doi.org/10.3390/nu12020324 MDPI+1

Cited by: 40

2. Nuankaew, W., Heemman, A., Wattanapiromsakul, C., & colleagues. (2021). Anti-insulin resistance effect of constituents from Senna siamea on zebrafish model, its molecular docking, and structure–activity relationships. Journal of Natural Medicines, 75(3), 520–531. https://doi.org/10.1007/s11418-021-01490-5 SpringerLink+1

Cited by: 16

3. Park, S., Jeong, S. Y., Nam, Y. H., Park, J. H., Rodriguez, I., Shim, J. H., Yasmin, T., Kwak, H. J., Oh, Y., Oh, M., & colleagues. (2021). Fatty Acid Derivatives Isolated from the Oil of Persea americana (Avocado) Protects against Neomycin-Induced Hair Cell Damage. Plants, 10(1), 171. https://doi.org/10.3390/plants10010171 MDPI+1

Cited by: 11

4. Yasmin, T., Lee, Y., Kim, W. S., Lee, B., R. Lee, H. Hwang, M. H. Nam, S. Y. Nah, & colleagues. (2025). Lipid-Enriched Gintonin from Korean Red Ginseng Marc Alleviates Obesity via Oral and Central Administration in Diet-Induced Obese Mice. Nutrients, 17(23), 3794.

5. Yasmin, T., Lee, Y., Hwang, H., Seo, J., Kim, M. S., Park, M., Oh, S.-J., Nam, M.-H., & Rhim, H. (2025). Elevated O-GlcNAcylation Enhances Metabolic Rate and Reduces the Excitability of Hypothalamic ARC Neurons in 10-month-old Male Mice. Experimental Neurobiology, 34(4), 147–155. https://doi.org/10.5607/en25012 PMC+2KIST Pubs+2

Ms. Tamanna Yasmin’s research integrates natural-product pharmacology with neuro-metabolic science, aiming to develop novel, physiologically grounded interventions for metabolic disorders and obesity, contributing to global health, biomedical innovation, and translational neuroscience.

Muhammad Firoz Mridha | Machine Learning | Best Researcher Award

Prof. Dr. Muhammad Firoz Mridha | Machine Learning | Best Researcher Award

Professor | American International University | Bangladesh

Prof. Dr. Muhammad Firoz Mridha, a researcher at the American International University–Bangladesh (AIUB), has established a strong scholarly profile in computer science with notable contributions to machine learning, data analytics, cybersecurity, IoT, and applied artificial intelligence. With 319 publications, over 4,629 citations, and an h-index of 33, his work demonstrates sustained academic productivity and global research impact. His studies often address practical and emerging challenges—such as intelligent decision-support systems, secure digital infrastructures, and data-driven solutions for healthcare and smart environments—positioning his contributions at the intersection of theoretical advancement and real-world application. Collaboration is a defining feature of his career, reflected in partnerships with 575 co-authors, enabling multidisciplinary knowledge exchange and strengthening international research networks. His work has supported technological development, digital inclusion, and innovation-oriented problem-solving, particularly in contexts where data-centric technologies can improve societal outcomes.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. Mridha, M. F., Keya, A. J., Hamid, M. A., Monowar, M. M., & Rahman, M. S. (2021). A comprehensive review on fake news detection with deep learning. IEEE Access, 9, 156151–156170.

Cited by: 297

2. Mridha, M. F., Das, S. C., Kabir, M. M., Lima, A. A., Islam, M. R., & Watanobe, Y. (2021). Brain–computer interface: Advancement and challenges. Sensors, 21(17), 5746.

Cited by: 296

3. Jim, J. R., Talukder, M. A. R., Malakar, P., Kabir, M. M., Nur, K., & Mridha, M. F. (2024). Recent advancements and challenges of NLP-based sentiment analysis: A state-of-the-art review. Natural Language Processing Journal, 6, 100059.

Cited by: 271

4. Rayed, M. E., Islam, S. M. S., Niha, S. I., Jim, J. R., Kabir, M. M., & Mridha, M. F. (2024). Deep learning for medical image segmentation: State-of-the-art advancements and challenges. Informatics in Medicine Unlocked, 47, 101504.

Cited by: 227

5. Mridha, M. F., Lima, A. A., Nur, K., Das, S. C., Hasan, M., & Kabir, M. M. (2021). A survey of automatic text summarization: Progress, process and challenges. IEEE Access, 9, 156043–156070.

Cited by: 197

Prof. Dr. Muhammad Firoz Mridha’s research advances data-driven intelligence and secure digital systems, contributing to global technological innovation and societal problem-solving. His work supports scalable, real-world applications—particularly in developing regions—promoting inclusive, ethical, and sustainable digital transformation.

Marcin Kwapisz | Simulations | Research Excellence Award

Dr. Marcin Kwapisz | Simulations | Research Excellence Award

Senior Researcher | Czestochowa University of Technology | Poland 

Dr. Marcin Kwapisz is a materials engineering and nondestructive evaluation (NDE) researcher at the Częstochowa University of Technology, specializing in the mechanical behavior of materials under complex loading and in the development of advanced diagnostic technologies for industrial applications. With a portfolio of 30 publications, 74 citations, and an h-index of 5, he has contributed to strengthening scientific understanding of alternate pressing, multiaxial compression, and magnetic-based assessment techniques. His work places particular emphasis on Barkhausen Noise (BN) testing, where he has co-developed robotic and integrated measuring heads that improve the precision, repeatability, and automation of structural integrity evaluation in ferromagnetic materials. Collaborating with over 28 co-authors, Kwapisz engages in cross-disciplinary research bridging materials science, mechanical engineering, sensor technology, and automation, resulting in outputs that support enhanced quality control, reduced failure risk, and greater manufacturing efficiency. Collectively, his research advances modern inspection methodologies and contributes to safer, more reliable, and technologically progressive engineering practices worldwide.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. Knapiński, M., Dyja, H., Kawałek, A., Kwapisz, M., & Koczurkiewicz, B. (2013). Physical simulations of the controlled rolling process of plate X100 with accelerated cooling. Solid State Phenomena, 199, 484–489.
Cited by: 19

2. Dyja, H., Knapiński, M., Kwapisz, M., & Snopek, J. (2011). Physical simulation of controlled rolling and accelerated cooling for ultrafine-grained steel plates. Archives of Metallurgy and Materials, 56, 447–454.
Cited by: 10

3. Kawałek, A., Bajor, T., Kwapisz, M., Sawicki, S., & Borowski, J. (2021). Numerical modeling of the extrusion process of aluminum alloy 6XXX series section. Journal of Chemical Technology & Metallurgy, 56(2).
Cited by: 7

4. Dyja, H., Kwapisz, M., Laber, K., & Knapiński, M. (2011). Analysis of the effect of the tool shape on the stress and strain distribution in the alternate extrusion and multiaxial compression process. Archives of Metallurgy and Materials.
Cited by: 7

5. Rydz, D., Garstka, T., Koczurkiewicz, B., & Kwapisz, M. (2014). Walcowanie blach grubych ze stopu magnezu AZ31. Hutnik, Wiadomości Hutnicze, 81(5).
Cited by: 6