Dr. Abdolreza Farhadian | Flow Assurance | Excellence in Research Award

Dr. Abdolreza Farhadian | Flow Assurance | Excellence in Research Award

Kazan Federal University | Russia

Dr. Abdolreza Farhadian is a leading researcher in the oil and gas field, specializing in the development of environmentally friendly and advanced classes of kinetic hydrate inhibitors, anti-agglomerants, and corrosion inhibitors. His work focuses on hybrid inhibition strategies to simultaneously manage hydrate formation and corrosion challenges while overcoming compatibility issues between conventional inhibitors. He is also actively engaged in designing innovative kinetic hydrate promoters to enhance natural gas storage and transportation, along with carbon dioxide sequestration via clathrate hydrates. His research further extends to the development of oil-soluble catalysts and surfactants for heavy oil aquathermolysis, contributing to improved recovery efficiency. Dr. Farhadian has held progressive research leadership roles at Kazan Federal University and currently leads a joint research laboratory in collaboration with Dalian University of Technology. He has been a key contributor to multiple major industrial and government-supported projects and has received international recognitions including Top 2% Scientist rankings and multiple advisory and editorial board appointments. His broader research interests encompass gas storage, flow assurance, CO₂ capture, hydrogen storage, corrosion inhibition, biomaterials synthesis, water desalination, and enhanced oil recovery.

Chen, Z., Farhadian, A., Sadeh, E., Chen, C., & Striolo, A. (2025). Counterion-dependent promotion of methane hydrate formation by anionic biosurfactants: A molecular perspective for efficient gas storage. Chemical Engineering Journal, 170846.

Zhang, Y., Qiang, Y., Zhang, W., Ramakrishna, S., Farhadian, A., & Jin, Y. (2025). Formation of a green protective layer by symmetric imidazolium-based ionic liquids for metal corrosion inhibition: Interfacial adsorption and mechanistic insights. Colloids and Surfaces A: Physicochemical and Engineering Aspects, 723, 137299.

Chen, Z., Farhadian, A., Sadeh, E., & Chen, C. (2025). Micellization effects in surfactant-enhanced gas hydrate formation for efficient solidified methane storage. Energy, 332, 137088.

Sadeh, E., Liu, Y., Farhadian, A., Semenov, M. E., & Mohammadi, A. (2025). Impact of hydroxyl group in surfactant structure on methane hydrate formation, pelletization, and dissociation for advanced transportable methane pellets. Journal of Colloid and Interface Science, 690, 137306.

Liu, Y., Farhadian, A., Chen, C., Chen, Z., Chen, X., Yang, L., & Wang, H. (2025). Molecular dynamics insights into surfactant-regulated methane hydrate nucleation and growth: Comparative roles of sodium oleate and hydroxylated sodium oleate. Crystal Growth & Design, 25(12), 4426–4440.

Prof. Steven Dufour | Fluid Mechanics | Best Researcher Award

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. Xu Liu | Fluid Cross-Sectional Velocity Field | Best Researcher Award

Dr. Xu Liu | Fluid Cross-Sectional Velocity Field | Best Researcher Award

Research Institute of Highway Ministry of Transport | China

Dr. Xu Liu is an Assistant Researcher at the Research Institute of Highway Ministry of Transport with extensive experience in multiphase flow detection, computational fluid dynamics (CFD), structural mechanics simulation, and precision sensor development. He has actively contributed to multiple National Natural Science Foundation of China (NSFC) projects and provincial innovation initiatives, focusing on gas–liquid and liquid–solid two-phase flow measurement, intelligent sensing systems, and metrological assurance in smart city applications. Xu Liu has published several high-impact SCI and Scopus-indexed papers on flow sensors, velocity field reconstruction, and turbulence modeling, integrating intelligent algorithms, CFD simulations, and sensor optimization to address key challenges in industrial flow monitoring. His work emphasizes practical engineering applications, combining theoretical modeling, experimental techniques, and data-driven approaches to enhance flow measurement accuracy and reliability.

Profile: Orcid 

Featured Publications

Liu, X., Song, Y., Zhao, D., Lan, K., Zhai, K., Wang, M., & Fang, L. (2025). Study on velocity profile of gas–liquid two-phase stratified flow in pipelines based on transfer component analysis–back propagation neural network. Physics of Fluids.

Dr. Wang Dongbao | Multiphase Flow | Best Researcher Award

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.