Dr. Muhammad Iqbal | Computational Methods | Research Excellence Award

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Dr. Muhammad Iqbal | Computational Methods | Research Excellence Award

Associate Professor | Bacha Khan University | Pakistan

Dr. Muhammad Iqbal is a distinguished researcher whose scholarly profile reflects sustained excellence in chemistry with strong integration of Computational Methods in advanced scientific inquiry. His work demonstrates authoritative use of Computational Methods to analyze molecular systems, interpret coordination chemistry behavior, and enhance predictive accuracy, where Computational Methods consistently guide hypothesis development, data interpretation, and validation. Through extensive peer reviewed publications indexed in SCI and Scopus, he has contributed impactful knowledge supported by rigorous Computational Methods that strengthen reproducibility and translational relevance. His research output shows meaningful citation influence and international visibility, while Computational Methods enable collaborative alignment with interdisciplinary researchers and institutional partners. By applying Computational Methods to complex chemical challenges, his contributions advance analytical efficiency, resource optimization, and knowledge driven innovation with tangible societal and scientific benefits. His academic service and research dissemination reflect a commitment to quality, integrity, and global standards, with Computational Methods remaining central to methodology, collaboration, and impact across his scholarly endeavors. Google Scholar profile of 380 Citations, 13 h-index, 13 i10 index.

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Featured Publications

Dr. Pooja Sharma | Computational Chemistry | Research Excellence Award

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Dr. Pooja Sharma | Computational Chemistry | Research Excellence Award

Assistant Professor | Chandigarh University | India

Dr. Pooja Sharma is a dedicated researcher whose work in Computational Chemistry consistently advances the understanding of material behaviour for sustainable energy technologies. Her contributions in Computational Chemistry focus on theoretical investigations of perovskite materials, optoelectronic properties, and structural modelling for improved solar-energy systems. Through extensive publications in high-quality journals, she demonstrates strong proficiency in Computational Chemistry, integrating density functional theory, conceptual modelling, and simulation-driven interpretation of electronic structures. Her expertise in Computational Chemistry has supported multidisciplinary collaborations with research groups working on photovoltaics, molecular modelling, and material innovation. She applies Computational Chemistry to explore environmentally relevant materials, contributing to societal progress by enabling cleaner and more efficient technologies. Her sustained involvement in collaborative projects and workshops highlights her commitment to advancing Computational Chemistry as a tool for scientific development, while her academic contributions reflect a deep understanding of the broader impact of material research. As a leading voice in Computational Chemistry, she continues to enhance knowledge exchange across academia, fostering innovation in sustainable energy applications. Her research orientation, grounded in Computational Chemistry, reinforces her role as a scholar with meaningful influence. Google Scholar Profile Of Citations 104, h-index 5, i10-index 4.

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Featured Publications

Prof. Dr. Jinju Sun | Computational Methods | Best Researcher Award

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Prof. Dr. Jinju Sun | Computational Methods | Best Researcher Award

Professor | Xi'an Jiaotong University | China

Prof. Dr. Jinju Sun is a distinguished scholar in the School of Energy and Power Engineering at Xi’an Jiaotong University, renowned for her pioneering contributions to fluid mechanics, turbomachinery, and multiphase flow systems through advanced Computational Methods. Her educational journey spans cryogenic engineering to a PhD in turbomachinery and engineering mechanics, which laid the foundation for her expertise in Computational Methods applied to turbomachinery optimization, Lattice Boltzmann modeling, and Vortex Method simulations. Throughout her professional career, she has served as a researcher, lecturer, and professor, advancing research through numerous national and international collaborations emphasizing Computational Methods in fluid dynamics and green energy system design. She has received prestigious honors, including the Donald Julius Groen Prize and the Arthur Charles Main Award from the Institution of Mechanical Engineers (UK), in recognition of her outstanding achievements utilizing Computational Methods for energy system modeling and flow optimization. Her research interests include cryogenic liquid turbines, compressor instabilities, and innovative Computational Methods for fluid-structure interaction and multiphase flow behavior. She has authored numerous high-impact publications and holds multiple international patents that demonstrate her excellence in Computational Methods-based innovation. Prof. Dr. Jinju Sun’s research skills encompass CFD modeling, LBM, topology optimization, and Computational Methods-driven analysis for turbomachinery and green energy systems. In conclusion, her dedication to advancing Computational Methods in engineering has positioned her as a global leader driving innovation, sustainability, and scientific excellence in modern energy and power engineering.

Profile: ORCID

Featured Publications

1. Qu, Y., Sun, J., Song, P., & Wang, J. (2025). Enhancing efficiency and economic viability in Rectisol system with cryogenic liquid expander. Asia-Pacific Journal of Chemical Engineering.

2. Ge, Y., Peng, J., Chen, F., Liu, L., Zhang, W., Liu, W., & Sun, J. (2023). Performance analysis of a novel small-scale radial turbine with adjustable nozzle for ocean thermal energy conversion. AIP Advances.

3. Fu, X., & Sun, J. (2023). Three-dimensional color-gradient lattice Boltzmann model for simulating droplet ringlike migration under an omnidirectional thermal gradient. International Journal of Thermal Sciences.

4. Song, P., Sun, J., Wang, S., & Wang, X. (2022). Multipoint design optimization of a radial-outflow turbine for Kalina cycle system considering flexible operating conditions and variable ammonia-water mass fraction. Energies.

5. Song, P., Wang, S., & Sun, J. (2022). Numerical investigation and performance enhancement by means of geometric sensitivity analysis and parametric tuning of a radial-outflow high-pressure oil–gas turbine. Energies.

Assoc. Prof. Dr. Osama Hussein Galal | Stochastic Fluid Dynamics | Excellence in Research

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Assoc. Prof. Dr. Osama Hussein Galal | Stochastic Fluid Dynamics | Excellence in Research

Associated Professor | Fayoum University | Egypt

Assoc. Prof. Dr. Osama Hussein Galal is a distinguished academic specializing in Stochastic Fluid Dynamics, whose professional journey reflects exceptional expertise in Engineering Mathematics and Physics. His academic and research trajectory demonstrates profound engagement with Stochastic Fluid Dynamics in analyzing uncertainty quantification, fractional-order systems, and fluid flow modeling. Over his extensive academic tenure, he has served as an educator, researcher, consultant, and supervisor, contributing significantly to Stochastic Fluid Dynamics applications in non-Newtonian fluid analysis, stochastic differential equations, and advanced computational mechanics. His professional experience extends to engineering consultancy and structural design, where he integrated Stochastic Fluid Dynamics methodologies for enhanced prediction accuracy in complex engineering systems. Assoc. Prof. Dr. Osama Hussein Galal has guided numerous postgraduate dissertations focusing on Stochastic Fluid Dynamics and uncertainty modeling in power systems, beam analysis, and transmission lines. His research interest revolves around integrating Stochastic Fluid Dynamics with machine learning, renewable energy modeling, and fractional calculus applications. Recognized for his scholarly contributions, he has received several awards for excellence in teaching, research supervision, and scientific publications. His research skills encompass analytical modeling, stochastic simulation, and the mathematical treatment of Stochastic Fluid Dynamics in engineering contexts, establishing him as a leading voice in the field. Through his numerous publications in reputed international journals, he has advanced global understanding of Stochastic Fluid Dynamics and its engineering implications. His career exemplifies the fusion of theoretical rigor and practical innovation, positioning him as a prominent figure in modern computational and stochastic analysis. Google Scholar profile of 102 Citations, 6 h-index, 5 i10-index.

Profiles: Google Scholar | ORCID

Featured Publications

1. Hatata, A., Galal, O. H., Said, N., & Ahmed, D. (2021). Prediction of biogas production from anaerobic co-digestion of waste activated sludge and wheat straw using two-dimensional mathematical models and an artificial neural network. Renewable Energy, 178, 226–240.

2. Galal, O. H., El-Tahan, W., El-Tawil, M. A., & Mahmoud, A. A. (2008). Spectral SFEM analysis of structures with stochastic parameters under stochastic excitation. Structural Engineering and Mechanics: An International Journal, 28(3), 281–294.

3. Galal, O. H., El-Tawil, M. A., & Mahmoud, A. A. (2002). Stochastic beam equations under random dynamic loads. International Journal of Solids and Structures, 39(4), 1031–1040.

4. Galal, O. H. (2013). A proposed stochastic finite difference approach based on homogenous chaos expansion. Journal of Applied Mathematics, 2013(1), 950469.

5. El-Beltagy, M. A., Wafa, M. I., & Galal, O. H. (2012). Upwind finite-volume solution of Stochastic Burgers’ equation. Scientific Research Publishing.

Sathya Arumugam Thirumalai | Computational Methods | Young Scientist Award

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Mr. Sathya Arumugam Thirumalai | Computational Methods | Young Scientist Award

Mr. Sathya Arumugam Thirumalai | Indian Institute of Technology Roorkee | India

Mr. Sathya Arumugam Thirumalai is a highly motivated researcher whose work integrates Computational Methods with experimental nanomaterial science, emphasizing sustainability, environmental protection, and advanced detection technologies. His academic journey, from IIT Roorkee to TU Dresden, reflects an enduring commitment to merging experimental nanotechnology with Computational Methods for the synthesis and characterization of perovskite, MXene, and 2D materials. Mr. Sathya’s professional experience spans renowned institutions like IISc Bengaluru, BARC Mumbai, and IIT Roorkee, where he utilized Computational Methods in density functional theory (DFT) simulations, material modeling, and radiation detector design. His research, grounded in Computational Methods, has contributed to multiple journal publications addressing gas sensing, field emission, and radiation detection. He applies Computational Methods to optimize nanomaterial performance, enhance photonic properties, and improve the efficiency of radiation detectors. Recognized with several awards and fellowships, including the National Talent Search Fellowship and the Saxon Student Mobility Grant, he has demonstrated excellence in both theoretical and practical domains. His technical mastery extends to Python, MATLAB, COMSOL, and VASP, emphasizing his strength in applying Computational Methods across interdisciplinary fields. Mr. Sathya’s skill in Computational Methods enables him to bridge theoretical simulations with experimental validation, ensuring scientific precision and innovation. His collaborative engagements with global research groups highlight his leadership and cross-disciplinary adaptability. In conclusion, Mr. Sathya exemplifies how Computational Methods can revolutionize material science, fostering technological advancements that align with sustainability and human welfare.

Profiles: Google Scholar | ORCID

Featured Publications

1. Sathya, A. T., Jethawa, U., Sarkar, S. G., & Chakraborty, B. (2025). Pd-decorated MoSi₂N₄ monolayer: Enhanced nitrobenzene sensing through DFT perspective. Journal of Molecular Liquids, 427, 127310.

2. Sathya, A. T., Kandasamy, M., & Chakraborty, B. (2024). Strain induced nitrobenzene sensing performance of MoSi₂N₄ monolayer: Investigation from density functional theory. Surfaces and Interfaces, 55, 105386.

3. Sanyal, G., Vaidyanathan, A., Sathya, A. T., & Chakraborty, B. (2025). Efficient catechol sensing in newly synthesized 2D material Ti₂B MBene: Insights from density functional theory simulations. Langmuir, 41(33), 22525–22534.

4. Sathya, A. T., Sarkar, S. G., Bakhtsingh, R. I., & Mondal, J. (2024). Suppression of shielding effect of large area field emitter cathode in radio frequency gun environment. Physica Scripta, 99(12), 125301.

Prof. Viktor Mykhas’kiv | Computational Methods | Best Researcher Award

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Prof. Viktor Mykhas’kiv | Computational Methods | Best Researcher Award

Leading Scientific Researcher | Institute for Applied Problemss of Mechanics and Mathematics | Ukraine

Prof. Viktor Mykhas’kiv is a distinguished researcher at the Pidstryhach Institute for Applied Problems of Mechanics and Mathematics, National Academy of Sciences of Ukraine. His academic achievements include a Doctor of Science in Physics and Mathematics and a professorship in Mechanics of Deformable Solids. His extensive expertise in Computational Methods spans across Computational Mechanics, Materials Science, Structural Mechanics, and Multiscale Mathematical Modeling. Through his pioneering work, he has applied Computational Methods to study wave propagation, metamaterials, and nanomechanics, advancing knowledge in multiple scattering theory. His research leadership in international collaborations under INTAS, STCU, DAAD, DFG, and Fulbright programs highlights his ability to integrate Computational Methods within global scientific frameworks. As a team leader and project manager, he has promoted innovative Computational Methods in the investigation of elastic metamaterials and complex lattice structures. He has published widely, authoring over seventy-six Scopus-indexed papers, two books, and contributing to editorial boards of international journals like Mathematical Methods and Physicomechanical Fields. His commitment to excellence in Computational Methods is reflected in his role as a member of the European Structural Integrity Society. He has also served as a visiting researcher in the USA and Germany, applying Computational Methods to solve advanced mechanical and physical problems. His awards and honors recognize his groundbreaking use of Computational Methods in applied mechanics and theoretical modeling. With remarkable research skills and professional integrity, Prof. Viktor Mykhas’kiv continues to contribute significantly to global scientific progress. Scopus profile of 474 Citations, 76 Documents, 14 h-index.

Profiles: Scopus | ORCID

Featured Publications

1. Stankevych, V. Z., & Mykhas’kiv, V. V. (2023). Intensity of dynamic stresses of longitudinal shear in a periodically layered composite with penny-shaped cracks. Journal of Mathematical Sciences, 269(2), 268–280.

2. Mykhas’kiv, V. V., & Stasyuk, B. M. (2021). Effective elastic moduli of short-fiber composite with sliding contact conditions at interfaces. Mechanics of Composite Materials, 57(6), 845–854.

3. Mykhas’kiv, V., & Stankevych, V. (2019). Elastodynamic problem for a layered composite with penny-shaped crack under harmonic torsion. ZAMM – Zeitschrift für Angewandte Mathematik und Mechanik, 99(8), e201800193.

4. Mykhas’kiv, V. V., Zhbadynskyi, I. Y., & Zhang, C. (2019). On propagation of time-harmonic elastic waves through a double-periodic array of penny-shaped cracks. European Journal of Mechanics - A/Solids, 74, 68–77.

5. Zhbadynskyi, I. Y., & Mykhas’kiv, V. V. (2018). Acoustic filtering properties of 3D elastic metamaterials structured by crack-like inclusions. Proceedings of the International Seminar/Workshop on Direct and Inverse Problems of Electromagnetic and Acoustic Wave Theory (DIPED), 54–59.