Muhammad Hafiz Hassan | Materials and Technology in Architecture | Research Excellence Award

Published on by Architecture Engineers

Dr. Muhammad Hafiz Hassan | Materials and Technology in Architecture | Research Excellence Award

Senior Lecturer | Universiti Sains Malaysia | Malaysia

Dr. Muhammad Hafiz bin Hassan is a Senior Lecturer at the School of Mechanical Engineering, Universiti Sains Malaysia, specializing in advanced manufacturing, composite machining, CNC processes, coating technologies, and the structural integrity of composite–metal systems. He has held impactful roles including Senior Lecturer, Application Specialist at Gandtrack Asia, and Material and Process Engineer at Spirit Aero Systems, while also serving as a research advisor, technical consultant, and collaborator for multiple engineering and industrial partners. His research focuses on single-shot drilling of CFRP/metal stacks, customized twist-drill geometry, DLC and nanocomposite coatings, polymer–MOF systems, machining optimization, and thermal–mechanical performance evaluation. He has led and participated in national grants, community-driven engineering initiatives, and postgraduate supervision in machining, materials engineering, and composite systems. His achievements include multiple international gold medals, best paper awards, invited and keynote speaker engagements, and recognition for innovative engineering solutions, strengthened by his credentials as a Professional Engineer (BEM) and Professional Technologist (MBOT), as well as active roles in academic, industrial, and vocational advisory committees. His research impact includes 458 citations, 47 publications, and an h-index of 10.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. Khan M.A., Halil A.M., Abidin M.S.Z., Hassan M.H., Ab Rahman A.A. Influence of laser surface texturing on adhesive bonding: a comprehensive review on surface morphology and strength enhancement. Optics & Laser Technology, 2025.

2. Hamidi M.N., Abdullah J., Mahmud A.S., Hassan M.H., Zainoddin A.Y. Influence of thermoplastic polyurethane (TPU) and printing parameters on the thermal and mechanical performance of polylactic acid (PLA)/thermoplastic polyurethane (TPU) polymer. Polymer Testing, 2025.

3. Rusdi M.S., Rosli M.S.A.M., Manap A.H.A., Hassan M.H., Seman S.A.H.A. A mini review on elucidating wire lifting defects due to Au₅Al₂ formation in LED thermosonic bonding. International Journal of Nanoelectronics and Materials (IJNeaM), 2025.

4. Hamidi M.N., Abdullah J., Mahmud A.S., Hassan M.H., Zainoddin A.Y. Thermal characteristic of melt blend polylactic acid (PLA)/thermoplastic polyurethane (TPU) with different blend ratio. International Conference on Advancement in Materials, Manufacturing, 2024.

5. Khan M.A., Halil A.M., Abidin M.S.Z., Hassan M.H., Ab Rahman A.A. Influence of laser surface texturing on the surface morphology and wettability of metals and non-metals: a review. Materials Today Chemistry, 2024.

Dr. Muhammad Hafiz bin Hassan advances scientific and industrial innovation through cutting-edge research in composite machining, advanced manufacturing, and coating technologies. His work enhances machining efficiency, structural reliability, and material performance across aerospace and engineering sectors. By translating research into practical industrial and community solutions, he contributes meaningfully to technological progress and societal development.

Zhexu Xi | Materials and Technology in Architecture | Research Excellence Award

Published on by Architecture Engineers

Dr. Zhexu Xi | Materials and Technology in Architecture | Research Excellence Award

Assistant Researcher | University of Oxford | United Kingdom

Dr. Zhexu Xi is an Assistant Researcher at the Inorganic Chemistry Laboratory of the University of Oxford, an invited Visiting Professor at the Hong Kong Institute of Technology, and a Guest Professor with the North American Artificial Intelligence Agency, specializing in inorganic nanoscience, interfacial functional nanomaterials, and AI-assisted materials design. His professional experience spans leading projects on two-dimensional transition-metal clusters for electrocatalysis, magnetic nanoparticle platforms for microfluidic enrichment, and ultrafast carrier dynamics in quantum-dot heterostructures, along with advancing AI-driven prediction frameworks for nanomaterials and contributing to climate-adaptive permeable pavement research. He has published more than thirty peer-reviewed papers across SCI journals and major WoS-indexed conferences, authored patents and book chapters, and delivered interdisciplinary contributions integrating nanoscience, materials chemistry, machine learning, and environmental engineering. Dr. Xi has received distinctions including the Emerging Scientist Award and a Best Paper Award nomination, and he serves as Youth Editorial Board Member of J. Mater. Sci., invited editor for MC Pharm. Sci., annual fellow of J. Water Res., peer reviewer for leading journals such as Nat. Commun. and ACS Appl. Mater. Interfaces, and guest editor for multiple special issues across SCI journals and international conferences, while also contributing to academic leadership through conference chair roles and professional memberships supporting innovation in materials chemistry and AI-driven science. His research impact includes 106 citations, 11 publications, and an h-index of 3.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. Z. Xi, Revisiting the Marcus Inverted Regime: Modulation Strategies for Photogenerated Ultrafast Carrier Transfer from Semiconducting Quantum Dots to Metal Oxides. RSC Adv., 2025, 15, 26897–26918.

2. G. Jin, C. Liu, Z. Xi, H. Sha, Y. Liu, J. Huang, Adaptive dual-view wavenet for urban spatial–temporal event prediction. Inf. Sci., 2022, 588, 315–330.

3. G. Jin, Z. Xi, H. Sha, Y. Feng, J. Huang, Deep multi-view graph-based network for citywide ride-hailing demand prediction. Neurocomputing, 2022, 510, 79–94.

4. R. Kang, H. Li, Z. Xi, S. Ringgard, A. Baatrup, K. Rickers, M. Sun, D.Q.S. Le, et al., Surgical repair of annulus defect with biomimetic multilamellar nano/microfibrous scaffold in a porcine model. J. Tissue Eng. Regen. Med., 2018, 12(1), 164–174.

5. G. Jin, Z. Xi, H. Sha, Y. Feng, J. Huang, Deep multi-view spatiotemporal virtual graph neural network for significant citywide ride-hailing demand prediction. arXiv preprint, 2020, arXiv:2007.15189.

Dr. Xi’s work advances the scientific understanding of nanomaterial interfaces and ultrafast charge dynamics while integrating AI-driven modelling to accelerate material discovery, supporting innovations that strengthen clean energy technologies and sustainable urban systems.