Tamanna Yasmin | Neuroscience | Tech Advancement Award

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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

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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

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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

Tapasi Bhattacharjee | Security | Editorial Board Member

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Dr. Tapasi Bhattacharjee | Security | Editorial Board Member

Professor | Techno International New Town | India

Dr. Tapasi Bhattacharjee is a researcher at Techno India Group, Kolkata, with core expertise in sustainable operations management, production–inventory optimization, and circular economy–driven decision models. With 13 publications, h-index of 4 and 63 citations, her work focuses on developing analytical and optimization frameworks that address real-world challenges such as managing perishable goods, emission-sensitive production environments, and resource-efficient inventory systems. Her recent research, including studies on price–time–circularity-responsive systems, demonstrates strong capability in integrating environmental sustainability with advanced quantitative techniques. Collaborating with 18 co-authors across interdisciplinary domains, she contributes to the design of greener and more resilient supply chains, offering insights valuable to industry, policymakers, and academia. Overall, her scholarly contributions support global efforts toward low-carbon manufacturing, sustainable resource use, and data-driven industrial innovation.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. Bhattacharjee, T., Maity, S. P., & Islam, S. R. (2017). Hierarchical secret image sharing scheme in compressed sensing. Signal Processing: Image Communication, 61, 21–32.
Cited by: 36

2. Bhattacharjee, T., & Maity, S. P. (2017). An image-in-image communication scheme using secret sharing and M-ary spread spectrum watermarking. Microsystem Technologies, 23(9), 4263–4276.
Cited by: 13

3. Bhattacharjee, T., & Rout, R. K. (2017). Affine Boolean classification in secret image sharing for progressive quality access control. Journal of Information Security and Applications, 33, 16–29.
Cited by: 13

4. Bhattacharjee, T., Singh, J. P., & Nag, A. (2012). A novel (2, n) secret image sharing scheme. Procedia Technology, 4, 619–623.
Cited by: 9

5. Bhattacharjee, T., & Maity, H. K. (2022). On FPGA implementation in medical secret image sharing with data hiding. Multimedia Tools and Applications.
Cited by: 6

Dr. Tapasi Bhattacharjee’s research advances secure image sharing, data protection, and intelligent watermarking techniques that strengthen digital trust in an increasingly visual and interconnected world. Her innovations support safer medical imaging, confidential communication, and resilient information systems for society and industry.

Pedro Pérez-Soriano | Sports biomechanics | Breakthrough Research Award

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Prof. Dr. Pedro Pérez-Soriano | Sports Biomechanics | Breakthrough Research Award

Professor | University of Valencia | Spain

Prof. Dr. Pedro Pérez Soriano, from Universitat de València, Spain, is an accomplished researcher in sports science, biomechanics, and human movement analysis, with a focus on optimizing athletic performance, injury prevention, and ergonomic comfort. His work investigates the effects of fatigue, footwear, surface conditions, and equipment adjustments on kinematics, impact accelerations, and physiological responses in running and cycling. With 130 publications, over 1,631 citations, and an h-index of 21, he demonstrates significant scholarly influence, complemented by collaborations with 290 co-authors worldwide. Key contributions include pioneering studies on sex-specific footwear responses, sprinting acceleration asymmetries, and the replicability of sports science research, often integrating advanced biomechanical modeling, sensor-based analysis, and infrared thermography. His research bridges theory and practice, informing sports equipment design, training protocols, and athlete safety measures, with broad societal and industrial relevance. Through these efforts, Pérez Soriano has advanced understanding of human movement while providing actionable insights that enhance performance, reduce injury risk, and guide evidence-based interventions in sports and exercise science globally.

Profiles: Scopus | ORCID

Featured Publications

1. Murphy, J., Caldwell, A. R., Mesquida, C., Brick, N., Parr, B., Quinn, R., Bolger, R., & Warne, J. (2025). Estimating the replicability of sports and exercise science research. Sports Medicine, 55(10), 2659–2679.

Cited by: 8

2. Catalá‑Vilaplana, I., Encarnación‑Martínez, A., Camacho‑García, A., Sanchis‑Sanchis, R., & Pérez‑Soriano, P. (2025). Influence of surface condition and prolonged running on impact accelerations. Sports Biomechanics, 24(4), 1064–1078.

Cited by: 4

Bao Peng | Big Data | Excellence in Research Award

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Prof. Bao Peng | Big Data | Excellence in Research Award

Professor | Shenzhen University of Information Technology | China

Prof. Bao Peng is an expert in millimeter-wave radar sensing, computer vision, and intelligent signal processing, with a focus on device-free human sensing, gesture recognition, and multimodal data fusion. He has published 54 papers, cited over 580 times, 13 h-index and collaborated with more than 110 researchers globally. His key contributions include cross-modal radar frameworks with information-maximization enhancement, lightweight self-attention-free transformer models for gesture recognition, and fusion-driven architectures for end-to-end human motion understanding, enabling efficient, low-data, and interpretable AI solutions. His work also extends to industrial applications, such as intelligent monitoring of unmanned pumping stations and YOLO-based infrastructure inspection, demonstrating broad societal and industrial relevance. By combining advanced signal processing with practical AI deployment, Prof. Peng’s research strengthens human–machine interaction, autonomous systems, and smart sensing technologies, contributing to safer, more efficient, and globally impactful innovations.

Profile: Scopus

Featured Publications

1. (2025). Cross-modal device-free radar sensing with information maximization enhancement and few-shot learning. IEEE Transactions on Microwave Theory and Techniques.

2. (2025). Device-free gesture recognition using multidimensional feature representation and lightweight self attention-free transformer. IEEE Transactions on Consumer Electronics.

3. (2025). End-to-end human motion recognition with multidomain dual attention transformer fusion network and millimeter-wave radar. IEEE Transactions on Consumer Electronics.

Cited by: 7

4. (2024). Visual analysis method for unmanned pumping stations on dynamic platforms based on data fusion technology. Eurasip Journal on Advances in Signal Processing.

Cited by: 1

5. (2024). GAM-YOLOv8n: Enhanced feature extraction and difficult example learning for site distribution box door status detection. Wireless Networks.

Cited by: 5

Prof. Bao Peng research transforms radar-based perception into practical AI solutions, advancing intelligent monitoring, autonomous systems, and human–machine interaction to foster safer, smarter, and more sustainable technological ecosystems.

Dawood Khan | Information Theory | Best Researcher Award

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Dr. Dawood Khan | Information Theory | Best Researcher Award

Lecturer | University of Balochistan | Pakistan

Dr. Dawood Khan is an emerging scholar in mathematical analysis, with a focused research portfolio spanning fractional calculus, convexity theory, superquadratic functions, and fractional integral inequalities. With 24 publications, 111 citations, 6 h-index and collaborations with 30 co-authors, he has contributed to advancing analytical methods used in optimization, dynamical systems, and applied modeling. His recent works, including studies on HH f-divergence, multiplicative calculus, and strongly convex functions, published in reputable journals such as Kuwait Journal of Science (2026) and Boundary Value Problems (2025), demonstrate both methodological rigor and thematic innovation. Dr. Khan’s research enhances the precision of mathematical tools employed in engineering, physics, and computational sciences, offering new perspectives for tackling complex real-world problems. His growing academic influence, reflected through an h-index of 6, underscores a sustained trajectory of scholarly impact and interdisciplinary collaboration, contributing to the global advancement of contemporary mathematical analysis.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. Khan, D., & Butt, S. I. (2024).Superquadraticity and its fractional perspective via center-radius cr-order relation. Chaos, Solitons & Fractals, 182, 114821.
Cited by: 26

2. Khan, D., Butt, S. I., & Seol, Y. (2025).Analysis on multiplicatively-superquadratic functions and related fractional inequalities with applications. Fractals,33(03), 2450129.
Cited by: 22

3. Butt, S. I., & Khan, D. (2025).Integral inequalities of h-superquadratic functions and their fractional perspective with applications. Mathematical Methods in the Applied Sciences, 48(2), 1952–1981.
Cited by: 22

4. Butt, S. I., & Khan, D. (2025).Superquadratic function and its applications in information theory via interval calculus. Chaos, Solitons & Fractals, 190, 115748.
Cited by: 12

5. Khan, D., Butt, S. I., & Seol, Y. (2024).Analysis of superquadratic function and related fractional integral inequalities with applications. Journal of Inequalities and Applications, 2024(1), 137.
Cited by: 12

Dr. Dawood Khan’s work strengthens foundational mathematical frameworks that underpin modern scientific and industrial modeling. His research advances global innovation by improving analytical tools essential for engineering, data science, and computational technologies.

Tannaz Alamfard | Molecular Dynamics Simulations | Research Excellence Award

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Ms. Tannaz Alamfard | Molecular Dynamics Simulations | Research Excellence Award

Technische Universität Dresden | Germany

Ms. Tannaz Alamfard is a researcher specializing in polymer science and molecular dynamics simulations, with a focus on understanding the thermo-mechanical behavior of elastomeric materials such as cis-1,4-polyisoprene. Her work investigates how molecular structure, temperature, and strain rate influence macroscopic material properties, providing insights critical for high-performance applications in automotive, biomedical, and flexible electronic systems. With 8 publications, 84 citations and h-index of 5 she has developed a growing scholarly impact, supported by collaborations with 9 international co-authors. Her research integrates computational modeling and materials engineering to optimize polymer performance, bridging fundamental science with practical industrial applications. By advancing predictive modeling of polymer behavior, her work contributes to the development of safer, more durable, and sustainable materials, demonstrating both scientific rigor and societal relevance.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. Nayak, C., Aghajamali, A., Alamfard, T., & Saha, A. (2017). Tunable photonic band gaps in an extrinsic Octonacci magnetized cold plasma quasicrystal. Physica B: Condensed Matter, 525, 41–45.

Cited by 41

2. Aghajamali, A., Alamfard, T., & Barati, M. (2014). Effects of loss factors on zero permeability and zero permittivity gaps in 1D photonic crystal containing DNG materials. Physica B: Condensed Matter, 454, 170–174.

Cited by 23

3. Aghajamali, A., Alamfard, T., & Hayati, M. (2015). Loss factor dependence of defect mode in a 1D defective lossy photonic crystal containing DNG materials. Optik, 126(21), 3158–3163.

Cited by 12

4. Aghajamali, A., Alamfard, T., & Nayak, C. (2021). Investigation of reflectance properties in a symmetric defective annular semiconductor–superconductor photonic crystal with a radial defect layer. Physica B: Condensed Matter, 605, 412770.

Cited by 10

5. Alamfard, T., Lorenz, T., & Breitkopf, C. (2023). Thermal conductivities of uniform and random sulfur crosslinking in polybutadiene by molecular dynamic simulation. Polymers, 15(9), 2058.

Cited by 9

Ms. Tannaz Alamfard’s research advances the understanding of polymer mechanics, enabling the design of high-performance, sustainable materials that support innovation across science, industry, and global technology development.

Liangyong Chu | Ocean Engineering | Excellence in Research Award

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Prof. Dr. Liangyong Chu | Ocean Engineering | Excellence in Research Award

Professor | Jimei University | China

Prof. Dr. Liangyong Chu is a maritime systems and safety researcher at the Fisheries Research Institute of Fujian, Xiamen, China, specializing in maritime supply chain resilience, emergency management, and risk governance. With 21 publications ,5 h-index and 63 citations, his work advances understanding of how global maritime networks withstand and recover from disruptions driven by environmental hazards, operational failures, and geopolitical pressures. His recent contributions—including an open-access framework for achieving high maritime supply chain resilience and a comprehensive systematic review of maritime emergency management—demonstrate strong capability in integrating systems analysis, bibliometrics, and applied policy perspectives. Collaborating with more than 40 co-authors, Dr. Chu has built a multidisciplinary research profile that bridges logistics, marine science, and public safety domains. His scholarship supports improved decision-making for governments, port authorities, and industry stakeholders, strengthening operational continuity, enhancing emergency preparedness, and promoting sustainable and resilient maritime development on a global scale.

Profile: Scopus

Featured Publications

1. Han, Y., & Chu, L. (2025). A systematic review and bibliometric analysis for maritime emergency management. Journal of Sea Research.

Cited by: 3

2. Xu, M., Ma, X., Zhao, Y., & Qiao, W. (2023). A systematic literature review of maritime transportation safety management. Journal of Marine Science and Engineering, 11(12), 2311.

Cited by: 2

Prof. Dr. Liangyong Chu’s research enhances the stability and safety of global maritime systems by advancing frameworks for resilience and emergency management. His work supports science-driven policymaking and operational innovation that help safeguard coastal communities, strengthen international trade continuity, and promote sustainable maritime development.

Mahmoud Iskandarani | AI | Editorial Board Member

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Prof. Mahmoud Iskandarani | AI | Editorial Board Member

Professor | Al-Ahliyya Amman University | Jordan

Prof. Mahmoud Zaki Iskandarani’s research focuses on advancing wireless communication systems with specialization in wireless sensor networks (WSNs), intelligent reflecting surfaces (IRS), robotic communication platforms, adaptive beamforming techniques, and electromagnetic field modeling. With 84 publications, 167 citations, 5 h-index his scholarly output reflects sustained productivity and growing global recognition. His recent works address energy-efficient communication for robotic WSNs, SINR enhancement through adaptive IRS design, hybrid beamforming using Gaussian interpolation, and analytical–numerical modeling supported by neural predictors, demonstrating strong integration of computational intelligence with communication engineering. He has also contributed to transportation and mobility research through studies on BRT system impacts on congestion and safety, highlighting his capacity for multidisciplinary problem-solving. Collaborating with 11 co-authors across diverse domains, he publishes in reputable international journals such as IEEE Access, Journal of Communications, Journal of Robotics, and Cogent Engineering, reinforcing the breadth and relevance of his contributions. Collectively, his research advances theoretical models and practical frameworks that improve spectral efficiency, path-loss prediction accuracy, energy optimization, and network reliability in emerging 6G-oriented and autonomous systems, generating technological and societal value across communication, robotics, and smart mobility sectors.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. Gardner, J. W., Iskandarani, M. Z., & Bott, B. (1992). Effect of electrode geometry on gas sensitivity of lead phthalocyanine thin films. Sensors and Actuators B: Chemical, 9(2), 133–142.

Cited by: 63

2. Iskandarani, M. Z. (2008). Effect of information and communication technologies (ICT) on non-industrial countries—Digital divide model. Journal of Computer Science, 4(4), 315.

Cited by: 41

3. Shilbayeh, N. F., & Iskandarani, M. Z. (2004). Quality control of coffee using an electronic nose system. American Journal of Applied Sciences, 1(2), 129–135.

Cited by: 41

4. Iskandarani, M. Z. (2025). Effect of Intelligent Reflecting Surface on WSN Communication with Access Points Configuration. IEEE Access, 13, 13380–13394.

Cited by: 29

5. Iskandarani, M. Z. (2025). Energy and path loss analysis of wireless sensor networks on a robotic body (WS Robotic). Bulletin of Electrical Engineering and Informatics, 14(3), 1794–1807.

Cited by: 25

Prof. Mahmoud Zaki Iskandarani’s work advances the performance, adaptability, and intelligence of wireless communication systems, contributing to the foundations of future 6G networks and autonomous robotic platforms. His research supports societal and industrial innovation by enabling more efficient connectivity, improved mobility systems, and smarter technological infrastructures worldwide.