Assoc. Prof. Dr. Mohammad Silani | Engineering | Research Excellence Award

Associate Professor | Isfahan University of Technology | Iran

Assoc. Prof. Dr. Mohammad Silani is a distinguished figure in Engineering research, widely recognized for his contributions to computational mechanics, multiscale material modeling, fracture mechanics, and advanced numerical simulations. With an extensive background in Engineering applications, his work integrates molecular dynamics, finite element analysis, stochastic modeling, and phase-field theory to address complex material behavior in composite and nanocomposite structures. His Engineering research extends across multiscale modeling, machine learning–assisted simulations, and high-fidelity experimentation, establishing him as a leading contributor to Engineering innovation in computational materials science. He has served in multiple advanced academic and scientific capacities, has supervised doctoral and postgraduate research, and has actively collaborated internationally with institutions and Engineering research groups across Europe, Asia, and Australia. His scholarly output reflects a strong Engineering foundation, comprising many high-impact journal publications, conference contributions, and collaborations that have advanced computational Engineering and numerical methodology. His work on nanostructures, wear modeling, fatigue crack propagation, and hydrogen embrittlement demonstrates a deep Engineering perspective in bridging theory, simulation, and physical behavior. As a reviewer for numerous international journals, his expertise supports the global Engineering community through critical evaluation and scientific refinement. His research continues to influence structural integrity, biomaterial mechanics, lattice optimization, composites Engineering, mechanical design, and simulation-driven material development at multi-scale and multi-physics levels. His sustained contributions to Engineering research, academic leadership, and scientific cooperation reflect a career dedicated to advancing knowledge, improving computational frameworks, and developing reliable Engineering tools for industrial and scientific application. His work stands as a reference point for emerging researchers in Engineering modeling and mechanical material characterization, highlighting precision, innovation, and impactful academic leadership in modern Engineering science. Google Scholar profile of 3041 Citations, 22 h-index, 32 i10-index.

Profile: Google Scholar

Featured Publications

1. Koupaei, F. B., Javanbakht, M., Silani, M., Mosallanejad, M. H., & Saboori, A. (2026). Mechanics-based phase-field model for directional microstructure evolution: Multiscale finite element simulation of IN718 in DED process. Computational Materials Science, 261, 114342.

2. Sabetghadam-Isfahani, A., Silani, M., Javanbakht, M., & others. (2025). Molecular dynamics analysis of temperature and shear stress effects on nickel bi-crystal amorphization. Iranian Journal of Chemistry and Chemical Engineering, e732047.

3. Varshabi, N., Jafari, M., Jamshidian, M., Silani, M., Thamburaja, P., & Rabczuk, T. (2025). Phase-field modeling of stressed grain growth in nanocrystalline metals. International Journal of Mechanical Sciences, 110951.

4. Saffari, M. M., Javanbakht, M., Silani, M., & Jafarzadeh, H. (2025). Stress analysis of nanostructures including nanovoids and inclusions based on nonlocal elasticity theory with different kernels. International Journal of Applied Mechanics, 17(6), 2550041.

5. Sabetghadam-Isfahani, A., Javanbakht, M., & Silani, M. (2025). Atomistic-informed phase-field modeling of edge dislocation evolution in Σ3, Σ9, and Σ19 silicon bi-crystals. Computational Materials Science, 254, 113893.

Dr. Wu Qiuxuan | Robotics and Automation | Best Researcher Award

Teacher | Hangzhou Dianzi university | China

Dr. Wu Qiuxuan, an Associate Professor at the School of Automation, Hangzhou Dianzi University, is a distinguished researcher whose expertise and leadership have significantly advanced the field of Robotics and Automation. With a Ph.D. in Control Science and Engineering from Shanghai Jiaotong University, his academic journey reflects a deep commitment to innovation in Robotics and Automation, particularly in the areas of soft robotics, evolutionary learning, and home energy systems. Dr. Wu’s professional experience includes academic and research roles, notably as a visiting scholar at the Australian National University, where he furthered his understanding of intelligent robotic systems. His extensive research on bipedal robots, underwater biomimetic designs, and bio-inspired control algorithms has earned him international recognition. Dr. Wu has authored impactful papers in leading journals such as IEEE Robotics and Automation Letters and Bioinspiration & Biomimetics, contributing to global advancements in Robotics and Automation. His work integrates advanced modeling, deep reinforcement learning, and optimization techniques to enhance robotic adaptability and performance. Over the years, Dr. Wu has received numerous research grants supporting his pioneering studies on service robots, industrial automation, and 3D bioprinting technologies, underscoring his central role in the evolution of Robotics and Automation. With 721 citations, an h-index of 11, and an i10-index of 20, his scholarly influence continues to grow. Dr. Wu’s research skills encompass algorithmic innovation, system optimization, and control engineering, blending theoretical insight with practical application. In conclusion, Dr. Wu Qiuxuan stands as a driving force in Robotics and Automation, whose interdisciplinary expertise continues to shape intelligent systems and inspire the next generation of automation research worldwide.

Featured Publications

1. Cai, N., He, M., Wu, Q., & Khan, M. J. (2019). On almost controllability of dynamical complex networks with noises. Journal of Systems Science and Complexity, 32(4), 1125–1139.

2. Chi, X., Liu, B., Niu, Q., & Wu, Q. (2012). Web load balance and cache optimization design based nginx under high-concurrency environment. Proceedings of the Third International Conference on Digital Manufacturing & Automation, 69–73.

3. Wu, Q., Yang, X., Wu, Y., Zhou, Z., Wang, J., Zhang, B., Luo, Y., Chepinskiy, S. A., ... (2021). A novel underwater bipedal walking soft robot bio-inspired by the coconut octopus. Bioinspiration & Biomimetics, 16(4), 046007.

4. Wu, Q., Gu, Y., Li, Y., Zhang, B., Chepinskiy, S. A., Wang, J., Zhilenkov, A. A., ... (2020). Position control of cable-driven robotic soft arm based on deep reinforcement learning. Information, 11(6), 310.

5. Chi, X., Wang, C., Wu, Q., Yang, J., Lin, W., Zeng, P., Li, H., & Shao, M. (2023). A ripple suppression of sensorless FOC of PMSM electrical drive system based on MRAS. Results in Engineering, 20, 101427.