Hesham Khalaf | Mathematics | Best Researcher Award

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Assist. Prof. Dr. Hesham Khalaf | Mathematics
| Best Researcher Award

Department of mathematics, Faculty of Science, Assiut University | Egypt

Assist. Prof. Dr. Hesham Khalaf dynamical systems research encompasses the analytical and numerical investigation of chaotic, hyperchaotic, fractional-order, and distributed-order models, with emphasis on understanding system behavior across different dimensions. Core contributions include examining symmetry properties, identifying equilibrium points, and performing stability, multistability, and bifurcation analyses to reveal transitions between periodic, chaotic, and hyperchaotic states. Advanced synchronization techniques—such as modulus-modulus, N-tuple compound, dual combination, and distributed-order synchronization—are applied to explore how distinct nonlinear systems interact, converge, or desynchronize under various coupling schemes. These synchronization strategies support practical applications in secure communications, image encryption, neural networks, circuit implementation, and control systems. Additional work investigates fractional-order derivatives and distributed-order operators, which capture memory effects and enhance the modeling of real-world processes. Research includes proposing new high-dimensional fractional-order hyperchaotic systems, studying their dynamic features, and applying them to grayscale and color image encryption. Numerical simulation methods, MATLAB-based modeling, and system dynamics tools are used to validate analytical results and visualize attractor structures. Further studies explore dynamical behaviors of classical models such as the Lorenz system, detuned laser models, and complex-valued chaotic systems, contributing to the advancement of applied mathematics, complex systems analysis, and modern chaos theory.

Featured Publication

Khalaf, H., Mahmoud, G. M., Bountis, T., & AboElkher, A. M. (2025). A distributed-order fractional hyperchaotic detuned laser model: Dynamics, multistability, and dual combination synchronization. Fractal and Fractional, 9(10), Article 668. https://doi.org/10.3390/fractalfract9100668

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