Prof. Steven Dufour | Fluid Mechanics | Best Researcher Award

Published on by High Energy Physics

Prof. Steven Dufour | Fluid Mechanics | Best Researcher Award

Polytechnique Montreal | Canada

Prof. Steven Dufour is a distinguished faculty member at École Polytechnique de Montréal with extensive international academic experience, including visiting professorships in the United States, Saudi Arabia, and Brazil. He is an active member of IEEE, SIAM, and PMI, and has led numerous research projects in computational methods and fluid mechanics, supervising a large number of researchers across different levels. His projects span areas such as scientific machine learning, quantum computing, wireless power transfer, magnetohydrodynamics, turbulence modeling, superconductivity, artificial neural networks, numerical methods, and optimization for engineering systems. He has taught a wide range of mathematical and engineering courses, including finite element methods, deep learning mathematics, linear algebra, and scientific computing, and has coordinated major undergraduate programs. Prof. Dufour also plays a strong leadership role in university governance, contributing significantly to academic councils, program development, labor agreement negotiations, and institutional committees, demonstrating consistent commitment to advancing engineering education and research.

Khademi, A., & Dufour, S. (2025). Physics-informed neural networks with trainable sinusoidal activation functions for approximating the solutions of the Navier–Stokes equations. Computer Physics Communications.

Khademi, A., Salari, E., & Dufour, S. (2025). Simulation of 3D turbulent flows using a discretized generative model physics-informed neural networks. International Journal of Non-Linear Mechanics, 170, 104988.

Khademi, A., & Dufour, S. (2024). A novel discretized physics-informed neural network model applied to the Navier–Stokes equations. Physica Scripta, 99(7), 076016.

Arab, H., Wang, D., Wu, K., & Dufour, S. (2022). A full-wave discontinuous Galerkin time-domain finite element method for electromagnetic field mode analysis. IEEE Access, 10, 125243–125253.

Arab, H., Arabsalmanabadi, B., & Dufour, S. (2022). A novel time-domain numerical methodology for the electromagnetic analysis of an H-plane tee power divider. The Journal of Engineering, 2022(10), 1032–1036.

Dr. Wang Dongbao | Multiphase Flow | Best Researcher Award

Published on by High Energy Physics

Dr. Wang Dongbao | Multiphase Flow | Best Researcher Award

Jiangsu University | China

Dr. Wang Dongbao is a researcher specializing in experimental studies of complex liquid–liquid flows influenced by electric fields and process intensification technologies. His work focuses on understanding the fundamental behavior of multi-scale droplets in liquid media using advanced microfluidic techniques and high-speed camera visualization to bridge the gap between academic research and industrial applications. His research interests encompass electrohydrodynamics (EHD), microfluidics and flow dynamics, experimental multiphase flow, biofuel and reaction kinetics, and process intensification. Dr. Wang has extensive experience with experimental techniques such as high-speed imaging, particle image velocimetry (PIV), and rheological analysis. He is currently a Postdoctoral Research Associate at University College London (Jun. 2023 – May 2025) and a Lecturer at Jiangsu University (Aug. 2020 – present). His research is supported by major funding sources, including the National Natural Science Foundation of China, the China Postdoctoral Science Foundation, and the UK Engineering and Physical Sciences Research Council (EPSRC) under the PREMIERE project, focusing on interactions and multiphase flow fields.

Profile:  Scopus | Orcid 

Featured Publications

Hang, Y., Wang, J., Wang, D., Wang, D., Gao, J., & Li, B. (2025). Behavioral characteristics of charged particle-laden droplets with the effect of non-uniform electric field. Colloids and Surfaces A: Physicochemical and Engineering Aspects.

Wang, D., Chagot, L., Wang, J., & Angeli, P. (2025). Effect of electric field on droplet formation in a co-flow microchannel. Physics of Fluids.

Wang, D., Wang, J., Wang, D., & Bi, Q. (2024). Electrically driven coalescence of charged conical droplet in non-uniform electric field. Chemical Engineering Science.

Chaimongkol, N. P., Deethayat, T., Wang, D., & Kiatsiriroat, T. (2023). Waste heat harvesting from continuous blowdown for power generation via organic Rankine cycle network: Case study of a coal-fired power plant. Results in Engineering.

Zuo, L., Wang, J., Mei, D., Wang, D., Zhang, W., Xu, H., Yao, J., & Zhao, T. (2023). Atomization and combustion characteristics of a biodiesel–ethanol fuel droplet in a uniform DC electric field. Physics of Fluids.