Muhammad Naveed Khan | Chemical Engineering | Best Researcher Award

Dr. Muhammad Naveed Khan | Chemical Engineering | Best Researcher Award

Zhejiang university | China

Dr. Muhammad Naveed Khan is an accomplished researcher in applied mathematics and computational fluid dynamics, recognized internationally for his extensive contributions to non-Newtonian fluid modeling, hybrid nanofluid behavior, and advanced numerical simulation techniques. With a strong research foundation built through doctoral training in applied mathematics and continuous postdoctoral work at leading academic institutions, he has established himself as a prolific scholar in contemporary fluid mechanics and heat transfer analysis. Dr. Khan’s research focuses on a wide spectrum of computational and theoretical problems, including partial differential equations, heat and mass transfer analysis, hybrid nanofluid and ternary nanofluid flows, magnetohydrodynamics (MHD), bioconvection, multiphase flow stability, and Newtonian and non-Newtonian fluid behaviors under complex physical constraints. His expertise extends to modern transport theories such as Cattaneo–Christov heat flux, Darcy–Forchheimer porous media flow, swirling and rotational fluid systems, chemically reactive micropolar flows, and mixed convection phenomena. His contributions also include exploring the thermophysical roles of nanomaterials, bio-convection mechanisms, cross-diffusion effects, and entropy generation in next-generation heat transfer systems. With 80 SCI-indexed research publications, Dr. Khan has built a substantial scientific footprint, contributing first-author articles to high-impact journals such as Tribology International, Journal of Molecular Liquids, Case Studies in Thermal Engineering, Surfaces and Interfaces, and Journal of Computational Design and Engineering. His work consistently appears in Q1-ranked journals, demonstrating both scientific rigor and high relevance to global research challenges in energy engineering, fluid mechanics, and material science. His citation metrics—highlighted by more than 1700 citations, an h-index of 25, and an i10-index of 47—reflect his strong influence in the field. He has been recognized among the Top 2% most-cited scientists worldwide by Stanford University for consecutive years, underscoring the global impact of his scholarship. His research engagement includes supervising postgraduate scholars, contributing as a reviewer for more than 30 international scientific journals, and developing advanced computational solutions using COMSOL Multiphysics, MATLAB, MAPLE, and Mathematica. Dr. Khan’s ongoing projects include numerical modeling of drag–lift forces, chemically reactive micropolar systems, MHD nanofluid flows, entropy minimization, and multi-slip non-Newtonian flows over complex geometries. His sustained contributions strengthen theoretical fluid mechanics and support emerging applications in energy systems, environmental modeling, advanced heat exchangers, and high-performance engineering materials.

Profiles: Orcid | Google Scholar

Featured Publications

Khan, A. A., Khan, M. N., Ahammad, N. A., Ashraf, M., Guedri, K., & Galal, A. M. (2022). Flow investigation of second grade micropolar nanofluid with porous medium over an exponentially stretching sheet. Journal of Applied Biomaterials & Functional Materials. https://doi.org/10.1177/22808000221089782

Ahmad, S., Nadeem, S., & Khan, M. N. (2022). Heat enhancement analysis of the hybridized micropolar nanofluid with Cattaneo–Christov and stratification effects. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science. https://doi.org/10.1177/09544062211010833

Zhang, J., Ahmed, A., Khan, M. N., Wang, F., Abdelmohsen, S. A. M., & Tariq, H. (2022). Swirling flow of fluid containing (SiO₂) and (MoS₂) nanoparticles analyzed via Cattaneo–Christov theory. Journal of Applied Biomaterials & Functional Materials. https://doi.org/10.1177/22808000221094685

Khan, M. N., Nadeem, S., Abbas, N., & Zidan, A. M. (2021). Heat and mass transfer investigation of a chemically reactive Burgers nanofluid with an induced magnetic field over an exponentially stretching surface. Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering. https://doi.org/10.1177/09544089211034941

Khan, A. A., Khan, M. N., Nadeem, S., Hussain, S. M., & Ashraf, M. (2021). Thermal slip and homogeneous/heterogeneous reaction characteristics of second-grade fluid flow over an exponentially stretching sheet. Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering. https://doi.org/10.1177/09544089211064187

Khan, M. N., & Nadeem, S. (2021). MHD stagnation point flow of a Maxwell nanofluid over a shrinking sheet (multiple solution). Heat Transfer. https://doi.org/10.1002/htj.22098

Mr. Alessandro Becci | Chemical Engineering | Young Scientist Award

Mr. Alessandro Becci | Chemical Engineering | Young Scientist Award

Università Politecnica delle Marche, Italy.

Alessandro Becci is a dedicated researcher specializing in sustainable development and chemical processes at Università Politecnica delle Marche, Italy. His work is pioneering in the fields of environmental technologies and urban mining, aiming to advance circular economy practices across Europe. With an academic background in Environmental Sustainability and a Ph.D. focused on metal recovery biotechnologies, Alessandro brings both depth and innovation to recycling and resource management.

Profile

Scopus

Orcid

Education🎓

Alessandro holds both a Bachelor’s and a Master’s degree in Environmental Sustainability and Civil Protection, completed in 2015 and 2017, respectively, from Università Politecnica delle Marche in Italy. He later pursued a Ph.D. at the same university, specializing in the development of chemical process theories with a focus on biotechnologies for metal recovery from waste. His research combines environmental science and sustainable technologies to advance methods for waste management and resource recovery, contributing to more sustainable industrial processes.

Experience💼

Since joining Università Politecnica delle Marche as a Researcher in Environmental Technologies, Alessandro has played a key role in advancing high-impact European projects. He teaches Data Elaboration, focusing on data-driven approaches to sustainable development, and collaborates on various international initiatives with leading institutions in Spain, Denmark, and Italy. His work reflects a commitment to environmental innovation and cross-border research partnerships aimed at addressing pressing ecological challenges.

Research Interests🔬

Alessandro's research covers a range of fields critical to environmental sustainability, including urban mining, life cycle assessment (LCA), and bio-hydrometallurgy. His work integrates these areas to address key challenges in resource recovery and waste management.

Commitment to the Circular Economy
Driven by a commitment to advancing the circular economy, Alessandro focuses on the recycling of electronic waste and the recovery of critical raw materials. His research aims to reduce environmental impact by promoting sustainable reuse and resource efficiency.

Innovation in Resource Management
Alessandro also applies mathematical modeling in resource management, exploring innovative solutions to optimize resource use. His work aligns closely with Europe’s sustainability goals, supporting initiatives to create a more resilient and eco-friendly economy.

Awards🏆

Alessandro's contributions have positioned him as a valued researcher in European sustainability, with projects funded under prestigious programs like Horizon2020.

His patented bioleaching process for circuit board recycling further demonstrates his expertise and dedication to impactful environmental research.

Publications Top Notes📚

Life Cycle Assessment of Rare Earth Elements-Free Permanent Magnet Alternatives: Sintered Ferrite and Mn–Al–CACS Sustainable Chemistry & Engineering, 2023-09-11.Cited by 15 articles. Link

Life Cycle Assessment of Biomethane vs. Fossil Methane Production and SupplyEnergies, 2023-06-06. Cited by 10 articles. Link

Bioremediation of Sediments Contaminated with Polycyclic Aromatic Hydrocarbons: Technological Innovation Patented ReviewInternational Journal of Environmental Science and Technology, 2022-06. Cited by 20 articles. Link

Sustainable Strategies for the Exploitation of End-of-Life Permanent MagnetsProcesses, 2021-05. Cited by 30 articles. Link

Environmental Sustainability Analysis of Case Studies of Agriculture Residue ExploitationSustainability, 2021-04. Cited by 18 articles. Link

 

 

 

 

Haowei Zhang | Engineering | Best Researcher Award

Dr. Haowei Zhang | Engineering | Best Researcher Award

Ph.D student, The University of Hong Kong, Hong Kong.

👨‍🔬 Haowei Zhang is a dynamic researcher specializing in structural health monitoring, concrete structure damage detection, and computer vision-based bridge Weight-In-Motion (WIM) systems. With a Ph.D. in progress at The University of Hong Kong, he has made significant contributions through cutting-edge research and impactful publications in top-tier journals. Haowei’s work spans deep learning, machine learning, and advanced imaging techniques for infrastructure health assessment, making him a standout researcher in civil engineering.

Profile

Google Scholar

Education 🎓

Dr. Haowei Zhang is a current Ph.D. student in Civil Engineering at The University of Hong Kong, under the supervision of Prof. Ray Kai Leung Su. His doctoral research builds on his expertise in bridge safety performance and vehicle non-contact weigh-in-motion (WIM) technology. He holds a Master’s degree in Civil Engineering from Southeast University, where he focused on the safety performance of bridges, supervised by Prof. Gang Wu and Prof. Kang Gao. Prior to that, he earned his Bachelor’s degree from Northeastern University in China, with a thesis on experimental building design supervised by Prof. Zhechao Wang. During his undergraduate studies, he also attended a summer training program at the University of Oxford, where he explored micromechanics and its applications in liquid metal 3D printing.

Experience 💼

Dr. Haowei Zhang is currently pursuing a Ph.D. in Civil Engineering at The University of Hong Kong, supervised by Prof. Ray Kai Leung Su. He holds a Master’s degree in Civil Engineering from Southeast University, where his research focused on vehicle non-contact weigh-in-motion (WIM) technology and the safety performance of bridges. Additionally, he earned his Bachelor’s degree from Northeastern University, specializing in experimental building design.

Professionally, Dr. Zhang serves as a Junior Researcher at Dongqu Intelligent Transportation Infrastructure Technology (2023-present), where he contributes to the development of computer vision models and equipment for transportation infrastructure. He has also led research projects on bridge monitoring, concrete structure damage detection, and deep learning algorithms for weight identification. During his master’s studies, he worked as a part-time college psychological counselor at Southeast University, providing psychological support and managing data files for graduate students.

His work uniquely combines civil engineering, intelligent transportation systems, and mental health advocacy.

Research Interests 🔬

Haowei Zhang’s research interests lie in structural health monitoring, computer vision-based WIM systems, deep learning, machine learning applications in civil engineering, and non-contact vehicle weight identification. His work focuses on developing innovative solutions for monitoring the integrity of concrete structures and enhancing safety through advanced image processing and data analysis.

Awards 🏆

International Exhibition of Inventions of Geneva – Silver Prize (2024)
Honor of Individual Academic Innovation – Southeast University (2023)
First-Class Academic Scholarship – Southeast University (2021)
Outstanding Undergraduate Student of Liaoning Province (2021)
National Scholarship (2020)

Publications Top Notes 📄

Automatic crack detection on concrete and asphalt surfaces using semantic segmentation network with hierarchical Transformer, Engineering Structures, 2023 Cited by: 45. link

Non-contact vehicle weight identification method based on explainable machine learning models and computer vision, Journal of Civil Structural Health Monitoring, 2023 Cited by: 20. link

Fully decouple convolutional network for damage detection of rebars in RC beams, Engineering Structures, 2023 Cited by: 25. link

A machine learning and game theory-based approach for predicting creep behavior of recycled aggregate concrete, Case Studies in Construction Materials, 2022 Cited by: 35. link