Alireza Toloukian | Building Construction Technology | Editorial Board Member

Published on by Architecture Engineers

Assist. Prof. Dr. Alireza Toloukian | Building Construction Technology | Editorial Board Member

Professor | Iran University of Science and Technology | Iran

Dr. Ali Reza Tolou Kian, Assistant Professor of Rail Structure and Track Engineering at the Iran University of Science and Technology, is a specialist in railway track mechanics whose expertise encompasses ballast behavior, sleeper performance, rail corrugation detection, vibration attenuation, and structural connections. His professional background includes university-level teaching, research leadership, and prior experience assisting in construction project management, supported by advanced skills in experimental modal analysis, geotechnical and structural testing, and numerical modeling using FEM-based platforms. Dr. Tolou Kian has made substantial contributions to railway engineering through studies on sand-contaminated ballast, dynamic sleeper behavior, tire-derived aggregate applications, geogrid-reinforced ballast, and large-scale direct shear performance, resulting in numerous publications in high-impact international journals. He has supervised several graduate theses focused on rail corrugation monitoring, structural health assessment, ballast contamination effects, and vibration control, demonstrating strong academic mentorship. His professional activities include membership in the Tehran Construction Engineering Organization, reviewing for multiple international journals and conferences, and contributing to the design and development of specialized laboratory equipment. His research impact includes 310 citations, 13 publications, and an h-index of 10.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

Sadeghi J., Toloukian A., Zarei M.A., Khani N., Improvement of ballast behavior by inclusion of tire-derived aggregates with optimum size. Constr. Build. Mater., 2025, 458, 139530.

Sadeghi J., Kian A.R.T., Ghiasinejad H., Moqaddam M.F., Motevalli S., Effectiveness of geogrid reinforcement in improvement of mechanical behavior of sand-contaminated ballast. Geotext. Geomembr., 2020, 48(6), 768–779.

Tolou Kian A.R., Sadeghi J., Zakeri J.A., Large-scale direct shear tests on sand-contaminated ballast. Geotech. Eng., 2018, 171(5), 451–461.

Sadeghi J., Tolou Kian A.R., Shater Khabbazi A., Improvement of mechanical properties of railway track concrete sleepers using steel fibers. J. Mater. Civ. Eng., 2016, 28(11), 04016131.

Tolou Kian A.R., Sadeghi J., Zakeri J.A., Influences of railway ballast sand contamination on loading pattern of pre-stressed concrete sleeper. Constr. Build. Mater., 2020, 233.

Dr. Ali Reza Tolou Kian’s research advances the safety, resilience, and sustainability of railway infrastructure through innovative improvements in ballast behavior, sleeper performance, and track vibration mitigation. His work bridges scientific rigor with industry needs, delivering practical solutions that enhance railway durability, reduce maintenance costs, and support modern transportation development. He envisions railway systems that are smarter, more efficient, and engineered through data-driven experimentation and advanced material technologies.

Hussien M.Hassan | AI and Automation in Architecture | Best Researcher Award

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Dr. Hussien M.Hassan | AI and Automation in Architecture | Best Researcher Award

Associate Professor | Port Said University | Egypt

Dr. Hussien M. Hassan is an Associate Professor at the Faculty of Engineering, Port Said University, specializing in Naval Architecture and Marine Hydrodynamics. With a Ph.D. in Ship Hydrodynamics, he has developed extensive expertise in Computational Fluid Dynamics (CFD), artificial intelligence applications in ship design, and green marine technologies. His research primarily focuses on hydrodynamic optimization, sustainable ship geometry, marine bio-mimetics, and the integration of AI for energy-efficient maritime systems. Dr. Hassan has led and contributed to numerous funded research projects, including initiatives on smart solar desalination and innovative ventilation systems for climate resilience. His scholarly output includes several high-impact publications in international journals such as Marine Systems & Ocean Technology and Journal of Ocean Engineering and Marine Energy. Beyond academia, he has demonstrated entrepreneurial leadership as CEO of multiple marine and engineering ventures. He is also the author of a technical book on Artcam software and has delivered seminars on emerging maritime technologies. Recognized for his contributions to marine innovation and education, Dr. Hassan actively engages with global research communities, serving as a reviewer and collaborator in multidisciplinary engineering forums. His research impact includes 5 citations, 3 publications, and an h-index of 2.

Profiles: Scopus | Google Scholar

Featured Publications

1. Hassan H.M., Elsakka M.M., Refaat A., Zhang H., Yin Z., Ahmed A., A comparative study on the hydrodynamic performance of traditional and closed-loop marine propellers. Marine Systems & Ocean Technology, 2025, 20(3), 34.

2. Mosaad M.A., Gafaary M.M., Yehia W., Hassan H.M., On the design of X-bow for ship energy efficiency. Influence of EEDI on Ship Design & Operation, London, UK, 2017, 22(11).

3. Hassan H.M., Elsakka M.M., Refaat A., Amer A.E., Rizk R.Y., Optimal design of container ships geometry based on artificial intelligence techniques to reduce greenhouse gases emissions. International Work-Conference on Bioinformatics and Biomedical Engineering, 2023, 3.

4. Hassan H.M., Elsakka M.M., Moustafa M.M., On the comparative hydrodynamic analysis of conventional and innovative closed-loop marine propellers, 2024, 2.

5. Mosaad M., Improving ship wave resistance by optimal bulb configuration. SYLWAN, 2020, 164(11), 1–14.

Dr. Hussien M. Hassan’s work advances sustainable maritime innovation by integrating artificial intelligence and hydrodynamic optimization to enhance ship energy efficiency and reduce environmental impact. His research contributes to the global shift toward greener marine technologies, fostering progress in both academic and industrial applications of smart ship design.

Shixun Wu | AI and Automation in Architecture | Best Researcher Award

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Dr. Shixun Wu | AI and Automation in Architecture | Best Researcher Award

Vice Professor | Chongqing Jiaotong University | China

Dr. Shixun Wu, Vice Professor at the College of information Science and Engineering and Vice Dean of the Department of Communication Engineering at Chongqing Jiaotong University, is a specialist in wireless communication, wireless localization, and machine learning. With advanced training in applied mathematics and a doctorate in electrical and computer engineering, he has contributed extensively to intelligent transportation systems, cooperative mobile localization, Wi-Fi fingerprinting, secrecy communication, and RFID identification protocols. His work includes impactful publications in leading journals and collaborative projects that advance high precision positioning, reinforcement learning based communication strategies, and secure wireless systems. Dr. Wu has held key academic and leadership roles that support program development, research coordination, and the cultivation of emerging scholars. His professional recognition includes contributions to competitive research initiatives, involvement in editorial and review activities, and active participation in scholarly communities and technical organizations. His record reflects sustained excellence in advancing communication technologies and intelligent networked systems, positioning him as a distinguished candidate for this award. His research impact includes 380 citations, 38 publications, and an h-index of 11.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. Zhang H., Xu K., Huang D., He D., Wu S., Xian G., Hybrid decision-making for intelligent high-speed train operation using boundary constraint and pre-evaluation reinforcement learning. IEEE Trans. Intell. Transp. Syst., 2024, 25(11), 17979-17992.
2. Wu S., Wang S., Xu K., Wang H., Hybrid TOA/AOA cooperative mobile localization in 4G cellular networks. IEIE Trans. Smart Process. Comput., 2013, 2(2), 77-85.
3. Wu S., Zeng X., Zhang M., Cumanan K., Waraiet A., Chu Z., Xu K., LCVAE-CNN: Indoor Wi-Fi Fingerprinting CNN positioning method based on LCVAE. IEEE Internet Things J., 2025, Accepted.
4. Zhang M., Ding X., Tang Y., Wu S., Xu K., Star-RIS assisted secrecy communication with deep reinforcement learning. IEEE Trans. Green Commun. Netw., 2024, Accepted.
5. Yang X., Wu B., Wu S., Liu X., Zhao W.G.W., Time slot detection-based M-ary tree anticollision identification protocol for RFID tags in the Internet of Things. Wirel. Commun. Mob. Comput., 2021, Article ID 6638936.

Dr. Shixun Wu’s research advances precise wireless localization, intelligent communication systems, and machine learning-driven network optimization, strengthening the foundations of next-generation connected technologies. His contributions support safer transportation, more reliable indoor positioning, and secure communication frameworks that benefit both industry and society. He envisions scalable intelligent networks that enhance global digital infrastructure and drive innovation across smart mobility and IoT systems.