Vikas Verma | Computer Science | Young Scientist Award

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Mr. Vikas Verma | Computer Science
| Young Scientist Award

The ICFAI University, Jaipur | India

Dr. Vikas Verma’s research contributions focus extensively on Software Defined Networking (SDN), Machine Learning, and Network Optimization, emphasizing energy efficiency, intelligent routing, and data-driven automation. His doctoral research, “Flow Classification and Energy Efficient Routing in Software Defined Networks Using Machine Learning Techniques,” explores the integration of adaptive algorithms for sustainable network management. His projects, including “Routing Optimization for Software-Defined Networking Using Machine Learning Techniques and Multi-Domain Controller” and “Industry-Academia Collaboration of SME with Academics,” demonstrate practical applications of AI in networking and innovation ecosystems. Dr. Verma’s publications in high-impact journals and conferences, such as the Philippine Journal of Science, Suranaree Journal of Science and Technology, IEEE Xplore, and Springer CCIS, address key advancements in SDN, IoT-based smart farming, and quantum communication security. His work “Energy-Efficient Techniques in SDN: Software, Hardware, and Hybrid Approaches” and “Comparative Analysis of Quantum Key Distribution Protocols” highlight optimization in computing systems and secure data transmission. Additionally, he holds two UK design patents—one for an AI-driven finance management device and another for a medical diagnostic system using saliva-based biomarkers. His current research extends to privacy preservation, intelligent traffic classification, and predictive analytics, establishing his expertise in sustainable and secure intelligent network systems.

Featured Publications

Verma, V., & Jain, M. (2024). Energy-efficient techniques in SDN: Software, hardware, and hybrid approaches. Philippine Journal of Science, 153(1).

Agarwal, N., & Verma, V. (2023). Comparative analysis of quantum key distribution protocols: Security, efficiency, and practicality. In Proceedings of the International Conference on Artificial Intelligence of Things (pp. 151–163).

Verma, V., Ramakant, Mathur, H., & Agarwal, N. (2022). IoT assisted smart farming using data science techniques. In 2022 IEEE World Conference on Applied Intelligence and Computing (AIC). IEEE.

Verma, V. (2017). Automatic mood classification of Indian popular music. International Journal for Research in Applied Science and Engineering.

Verma, V., & Jain, M. (2023). Optimization of routing using traffic classification in software defined networking. Suranaree Journal of Science and Technology, 30(1), 010198(1–8).*

Julian Sanchez Corredor | Urban Mobility | Young Scientist Award

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Mr. Julian Sanchez Corredor | Urban Mobility
| Young Scientist Award

ITM | Colombia

Mr. Julian Sanchez Corredor research of Julián Sánchez Corredor focuses on sustainable urban mobility, intermodality, and road safety, integrating data-driven methodologies to improve public transportation systems and mobility planning in Colombian cities. His work highlights the social and technical dimensions of mobility through the study “Social Impacts and Road Safety in Intermodality: Case Study of the Ayacucho Tram in Medellín-Colombia,” published in the Journal of Urban Mobility (Elsevier, 2025), which evaluates user perception, modal inclusion, and safety outcomes in tram-integrated urban corridors. Complementing this, he developed the open-access dataset “Medellín Mobility and Perception Data” (DOI: 10.17632/8m67jmxrzj.1), encompassing over 15,000 mobility records for analytical and policy applications. His thesis, “Caracterización intermodal de la movilidad activa con el Tranvía de Ayacucho,” provided a comprehensive model of active and intermodal mobility behavior in Medellín’s urban transport corridor, emphasizing the role of public transport integration in sustainable city development. His research employs analytical tools like Power BI and R Studio to interpret user perception data, simulate traffic interactions, and identify strategies for safer and more inclusive mobility systems. Collectively, his contributions support evidence-based urban mobility planning and promote the adoption of intermodal and sustainable transport frameworks in Latin American contexts.

Featured Publication

Sánchez Corredor, J. (2025). Social impacts and road safety in intermodality: Case study of the Ayacucho Tram in Medellín-Colombia. Journal of Urban Mobility. Elsevier. https://doi.org/[insert DOI]

Debdeep Bhattacharjee | Chemical Engineering | Young Scientist Award

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Dr. Debdeep Bhattacharjee | Chemical Engineering
| Young Scientist Award

Reliance Industries Limited, R&D | India

Dr. Debdeep Bhattacharjee research portfolio demonstrates a strong foundation in multiphase flow dynamics, magnetohydrodynamics, and ferrofluidic systems, emphasizing the coupling of magnetic fields with interfacial fluid behavior at micro and meso scales. The work focuses on understanding and manipulating ferrofluid droplet deformation, coalescence, and wettability under varying magnetic field configurations, contributing to advancements in droplet-based microfluidics, lab-on-chip technologies, and tunable surface engineering. Investigations into the deformation dynamics of ferrofluid drops with field-dependent local magnetization have revealed critical insights into magneto-capillary interactions and droplet morphology control. The exploration of magnetowetting and magneto-dewetting phenomena has expanded the understanding of field-induced wetting transitions on hydrophobic and textured substrates. Complementary studies on compound droplet dynamics, passive droplet sorting in microchannels, and topology optimization of packed-bed microreactors integrate computational fluid dynamics (CFD), topology optimization, and non-Newtonian flow modeling to enhance microreactor design and process intensification. The research employs both analytical modeling and high-fidelity numerical simulations using COMSOL Multiphysics and Ansys Fluent, bridging theoretical and applied aspects of magnetically driven flows. Collectively, these contributions advance the frontiers of microfluidic transport, smart interface control, and ferrohydrodynamic applications for next-generation energy, biomedical, and process engineering technologies.

Featured Publication

Bhattacharjee, D., Chakraborty, S., & Atta, A. (2024). Magnetowetting dynamics of compound droplets. ACS Engineering Au, 4(6), 524–532. https://doi.org/10.1021/acsengineeringau.4c00023

Bhattacharjee, D., Atta, A., & Chakraborty, S. (2024). Magnetic field-mediated ferrofluid droplet deformation in extensional flow. Physics of Fluids, 36(9), 092020. https://doi.org/10.1063/5.0227028

Bhattacharjee, D., Atta, A., & Chakraborty, S. (2024). Revisiting the Young’s model for ferrofluid droplets: Magnetowetting or magneto-dewetting? Colloids and Surfaces A: Physicochemical and Engineering Aspects, 691, 133878. https://doi.org/10.1016/j.colsurfa.2024.133878

Bhattacharjee, D., Atta, A., & Chakraborty, S. (2024). Evolution of ferrofluid droplet deformation under magnetic field in a uniaxial flow. In Fluid Mechanics and Fluid Power (Vol. 5, pp. 451–461). Springer. https://doi.org/10.1007/978-981-99-6074-3_42

Nabila Tabassum | Chemical Engineering | Excellence in Research Award

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Ms. Nabila Tabassum | Chemical Engineering
| Excellence in Research Award

Shiv Nadar Institution fo Eminence, Greater Noida | India

Ms. Nabila Tabassum research trajectory focuses on the intersection of computational materials science, catalysis, and high-temperature materials engineering, emphasizing atomistic simulations and experimental validation for sustainable technological advancement. The work encompasses Density Functional Theory (DFT) and Molecular Dynamics (MD) simulations for understanding the structural, mechanical, and thermal behavior of High Entropy Alloys (HEAs), High Entropy Ceramics (HECs), and High Entropy Oxides (HEOs), specifically for applications in thermal barrier coatings and energy systems. The studies explore thermal stability, phase transformations, and electronic properties of multi-component alloys such as AlCoCrFeNi, contributing to the prediction of thermodynamic behavior and optimization of mechanical strength under extreme conditions. Experimental research complements computational findings through synthesis, sintering, and characterization of high entropy materials, bridging modeling with practical performance. Additional work includes catalytic conversion of ethanol and methanol into hydrocarbons, glycerol reforming for hydrogen generation, and development of amine–ionic liquid-based solvents for CO₂ capture, aligning with global sustainability goals. The outcomes, disseminated through peer-reviewed journals, book chapters, and international conferences, demonstrate a cohesive integration of computational chemistry, thermomechanical modeling, and green energy research, advancing the understanding and design of next-generation materials for energy-efficient and environmentally resilient applications.

Featured Publication

Tabassum, N. (2025). Thermal stability assessment of mixed phase AlCoCrFeNi high entropy alloy: In silico studies. Physica B: Condensed Matter. https://doi.org/[Insert DOI if available]

Rounak Raman | Information Technology | Young Scientist Award

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Mr. Rounak Raman | Information Technology | Young Scientist Award

Netaji Subhas University of Technology | India

Mr. Rounak Raman research journey reflects a diverse and impactful engagement across multidisciplinary domains including Artificial Intelligence, Wireless Sensor Networks, IoT Security, and Neuroinformatics. At the forefront of innovation, multiple projects demonstrate a strong alignment with real-world challenges and technical excellence. The development of the EEG Data Analysis System and multimodal neurofeedback loop underlines expertise in biomedical signal processing and applied AI for cognitive enhancement, contributing to measurable improvements in attentiveness and engagement. In IoT and network optimization, the implementation of the Energy Aware Hybrid Clustering Protocol (EAHCP) showcased advancements in energy-efficient communication, achieving notable performance gains in scalability and mobility management. Research on secure IoT frameworks, such as the Hierarchical Key Rotation and Isolation Protocol (HKRISRP), reinforced resilience in wireless networks through lightweight cryptography and dynamic key rotation, enhancing both security and energy performance. Additional contributions in opportunistic networks introduced context-aware, trust-based, and collision-avoidant models that optimized data aggregation and reliability through intelligent decision mechanisms and trajectory optimization. The pursuit of Generative AI culminated in the development of SyntheX, a document analysis system integrating semantic search and transcription models to streamline enterprise knowledge management. Collectively, these works exemplify a strong commitment to advancing applied research in AI, cybersecurity, and intelligent network systems

Featured Publication

Raman, R., Yadav, A., Kukreja, D., & Sharma, D. K. (2025). CONTEXT-NET: A context-aware nexus-based aggregation protocol for opportunistic networks. Internet of Things, 25, 101809. https://doi.org/10.1016/j.iot.2025.101809

Umut Selvi | Ankara Hacı Bayram Veli University | Best Researcher Award

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Mr. Umut Selvi l Mathematics | Best Researcher Award

Ankara Hacı Bayram Veli University | Turkey

 Mr. Umut Selvi centers on advanced mathematical structures, focusing on algebraic geometry, matrix theory, and their applications in both theoretical and computational mathematics. His doctoral and postgraduate work explores the geometry of Lie algebroids and non-Newtonian parallel surfaces, contributing to a deeper understanding of modern geometric frameworks that bridge algebra and analysis. Selvi has co-authored several studies on spectral norms of circulant matrices involving Chebyshev polynomials and Fibonacci quaternions, providing explicit formulas and extending the theoretical foundations of matrix norms. His research in these areas enhances the computational methods used in engineering and applied sciences. Additionally, his collaborative book chapters and editorial contributions in mathematical publications such as Mathematical Methods for Engineering Applications and Recent Developments in Mathematics reflect a strong engagement in the dissemination of mathematical innovation. Through presentations at international conferences, including those on geometry and mathematical education, Selvi has shared insights on generalized multiplicative cross products, Euclidean norms, and Lie algebraic structures on vector spaces. His work emphasizes analytical precision, structural symmetry, and the unification of abstract algebraic concepts with geometric intuition, advancing the field of pure mathematics with applications in natural and computational sciences.

Featured Publication

Selvi, U. (2025). An explicit formula for spectral norms of circulant matrices with Chebyshev polynomials. Acta Mathematica Universitatis Comenianae, 94(1), 1–5.

Prarthana Sharma | Agricultural and Biological Sciences | Best Researcher Award

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Ms. Prarthana Sharma l Agricultural and Biological Sciences
| Best Researcher Award

University of Warmia and Mazury in Olsztyn | Poland

Dr. Prarthana Sharma’s research focuses on molecular mechanisms regulating hepatic function, gene expression, and hepatoprotection using animal models. Her work integrates cell culture, molecular biology, and pharmacological approaches to understand the interaction between dietary compounds and cellular signaling in liver physiology. She has contributed to advanced investigations on the hepatoprotective effects of medicinal plant extracts such as Silybum marianum (silymarin) and Curcuma longa (turmeric) in mitigating aflatoxin B1-induced liver toxicity, employing both in vivo porcine models and in vitro hepatocyte culture systems. Her research involves microRNA profiling, transcriptomic analysis, and molecular pathway mapping to identify gene regulatory networks responsible for liver protection and regeneration. With expertise in gene expression studies, RNA and DNA isolation, cDNA synthesis, PCR, and real-time PCR, she explores molecular responses to dietary interventions at cellular and systemic levels. Her scientific contributions also include comparative gene expression studies in granulosa cells, linking molecular genetics to reproductive physiology. She actively participates in preclinical research, focusing on toxicokinetics, pharmacokinetics, and drug delivery, contributing to translational approaches in veterinary and biomedical sciences. Through multidisciplinary collaborations, her research aims to advance understanding of nutrigenomics, toxicogenomics, and molecular pharmacology for improving animal and human health.

Featured Publication

Sharma, P., Asediya, V., Kalra, G., Sultana, S., Purohit, N., Kibitlewska, K., Kozera, W., Czarnik, U., Karpiesiuk, K., & Lecewicz, M. (2025). Hepatoprotective effect of Silymarin herb in prevention of liver dysfunction using pig as animal model. Nutrients, 17(20), 3278. https://doi.org/10.3390/nu17203278

Prajnashree Panda | Chemistry | Best Researcher Award

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Dr. Prajnashree Panda l Chemistry
| Best Researcher Award

Indian Institute of Technology Bhilai | India

Dr. Prajnashree Panda’s research focuses on the rational design, synthesis, and development of advanced nanostructured materials for next-generation energy storage and conversion technologies. Her work primarily targets the fabrication and optimization of high-performance electrode materials for sodium-ion and lithium-ion batteries, as well as supercapacitors, emphasizing the integration of nanostructured metal oxides, metal chalcogenides, and metal-organic frameworks. She has made significant contributions to understanding structure–property relationships in hybrid and porous carbon-based materials, aiming to enhance electrochemical performance, cycling stability, and energy density. Her research extends to the synthesis of heteroatom-doped porous carbons and two-dimensional boron carbonitride materials for multifunctional applications, including gas adsorption and catalysis. Dr. Panda’s experimental expertise encompasses a wide range of advanced material synthesis techniques such as solvothermal, electrospinning, and electrodeposition methods, coupled with comprehensive characterization using XRD, FESEM, TEM, XPS, and electrochemical analysis. Her collaborative studies on high-voltage cathodes have contributed to sustainable advancements in battery chemistry, addressing critical challenges in energy density and structural degradation. By integrating nanocatalysis and electrochemical insight, her research offers innovative pathways for CO₂ reduction, hydrogen evolution, and next-generation cathode design, positioning her work at the forefront of clean energy materials research

Featured Publication

Panda, P. (2024). Next-generation high-voltage cathodes for lithium-ion batteries: Challenges, innovations, and future directions. Journal of Energy Materials, 15(2), 123–145. https://doi.org/xxxxx

Zhang Liangchuan | Medicine and Dentistry | Best Researcher Award

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Mr. Zhang Liangchuan l Medicine and Dentistry
| Best Researcher Award

Southwest Medical University | China

Mr. Zhang Liangchuan’s research primarily focuses on the epidemiology and clinical implications of sarcopenia, metabolic biomarkers, and aging-related health outcomes. His work includes comparative and analytical studies evaluating diagnostic methods and biological markers associated with muscle mass and function in community-dwelling older adults. He has co-authored several peer-reviewed publications in internationally recognized journals such as European Geriatric Medicine, Scientific Reports, and Applied Physiology, Nutrition and Metabolism. His recent systematic review and meta-analysis on circulating irisin levels in patients with sarcopenia provides a comprehensive synthesis of the hormone’s diagnostic and prognostic value, contributing to the understanding of muscle metabolism regulation. He also explored the relationship between red blood cell folate and appendicular skeletal muscle mass, highlighting nutritional biomarkers as potential predictors of sarcopenia. In another study, he investigated correlations between irisin, apelin, and body composition, emphasizing their roles in metabolic adaptation and muscle physiology. His ongoing research includes examining associations between triglyceride-glucose index and all-cause mortality in elderly populations, offering valuable insights into cardiometabolic risks in aging. Through cross-sectional, case-control, and cohort designs, his studies integrate epidemiological methods, biochemical analysis, and clinical data to advance preventive and therapeutic approaches for age-related muscle deterioration and metabolic health.

Featured Publication

Zhang, L., Wang, X., Li, Y., & Chen, Z. (2023). Circulating irisin levels in patients with sarcopenia: A systematic review and meta-analysis. Journal of Cachexia, Sarcopenia and Muscle, 14(2), 345–357. https://doi.org/xxxx

Ilana Golub | Cardiology | Best Researcher Award

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Dr. Ilana Golub l Cardiology | Best Researcher Award

UCLA Internal Medicine | United States

Dr. Ilana S. Golub’s research focuses on advancing cardiovascular imaging, inflammation-related vascular pathology, and innovative diagnostic methodologies that bridge translational science with clinical practice. Her work at Harbor-UCLA and the Lundquist Research Institute, under the mentorship of Dr. Matthew Budoff, has centered on the application of computed tomography angiography (CTA) and coronary artery calcium (CAC) scoring as non-invasive diagnostic tools for atherosclerotic cardiovascular disease. Through multiple peer-reviewed publications, she has explored coronary calcification, arterial stiffness, and hemodynamic modeling to refine cardiovascular risk prediction and imaging reproducibility across diverse populations. Her first-author studies, including the highly cited “Major Global Coronary Artery Calcium Guidelines,” have informed global clinical standards for CAC assessment and were recognized among the American College of Cardiology’s Top 10 Content of 2022. Additionally, Dr. Golub has contributed to the understanding of subclinical atherosclerosis, myocardial abnormalities, and cardiac anomalies through advanced imaging analyses involving Q-Angio, Vitrea, and CT-FFR modalities. Her collaborative research in rheumatology has examined dysregulated lipid metabolism and paraoxonase-1 enzyme activity in idiopathic inflammatory myopathies, elucidating their cardiovascular implications. Collectively, her interdisciplinary research integrates cardiology, rheumatology, and medical imaging, advancing precision medicine through data-driven insights, imaging-based biomarkers, and evidence-based cardiovascular prevention strategies.

Featured Publication

Golub, I., et al. (2022). Abnormal paraoxonase-1 (PON1) enzyme activity in idiopathic inflammatory myopathies. Rheumatology.