Santhosh S | Sustainable Architecture | Research Excellence Award

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Dr. Santhosh S | Sustainable Architecture | Research Excellence Award

Assistant Professor | Adhiparasakthi College of Engineering | India

Dr. S. Santhosh is an Assistant Professor in Civil Engineering at Adhiparasakthi College of Engineering, specializing in structural engineering, sustainable construction materials, geotechnical engineering, transportation systems, and environmental infrastructure. With extensive academic and administrative experience, he has served in roles including Head of Department, coordinator for academic quality initiatives, conference organizer, and member of university level question setting committees, contributing significantly to institutional development and student advancement. His research focuses on advanced concrete technologies, sustainable materials, lightweight and geopolymer concrete, AI-driven modelling, and smart infrastructure solutions, supported by publications in Scopus- and SCI indexed journals and presentations at prominent conferences. He has authored multiple technical books, guided numerous undergraduate scholars, and secured several Indian and international design patents related to construction devices, safety systems, and engineering innovations. He holds professional memberships in recognized engineering bodies and certifications in advanced civil engineering software and computing tools, complemented by recognition through teaching and research awards. His research impact includes 2 citations, 5 publications, and an h-index of 1.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. Santhosh S., Jagan P., Priyanga J., Analysis of mechanical properties on 3E-materials with blend concrete. Int. J. Civil Eng. Technol., 2018.

2. Santhosh S., Arivalagan S., Investigation of M-Sand concrete mix with mineral admixtures as partial replacement of cement. Int. J. Civil Eng. Technol., 2018.

3. Santhosh S., Raghunathapandian P., Thanaraj M.S., Jebastina N., Triple waste aggregates integration for sustainable self-compacting geopolymer concrete: A hybrid synergy. Waste Biomass Valorization, 2025, Accepted.

4. Santhosh S., Srivastava R., Subbiah M., Maddila L.C., Malla C., Begum M.B., Nanoelectronic sensors for real-time health and environmental monitoring. IEEE Int. Conf. Intelligent Technologies (CONIT), 2025.

5. Santhosh S., Arivalagan S., Utilization of oil palm shell in lightweight reinforced concrete. Eur. Chem. Bull., 2023.

Dr. S. Santhosh’s work advances sustainable construction through innovative materials, AI-driven modelling, and environmentally responsible engineering solutions, supporting the transition toward greener infrastructure. His contributions strengthen industry practices, enhance structural performance, and promote scalable, low-carbon technologies for future-ready civil engineering.

Monika Szopińska-Mularz | Sustainable Architecture | Research Excellence Award

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Dr. Monika Szopińska-Mularz | Sustainable Architecture | Research Excellence Award

Assistant Professor | Rzeszow University of Technology | Poland

Monika Szopińska-Mularz is a lecturer in architecture at Rzeszów University of Technology and a Chartered Architect whose expertise centers on adaptive reuse, sustainable urban regeneration, and controlled environment agriculture. With academic and professional experience spanning architectural practice, design studio leadership, research supervision, and project coordination, she has contributed to diverse architectural projects in healthcare, housing, office design, and the revitalization of urban structures. Her research advances innovative strategies for repurposing modern movement car-parking structures into productive urban assets, reflected in her numerous publications in international journals and a monograph on adaptive reuse for urban food provision. She serves as the principal investigator of an international research consortium developing decision-support tools for urban food-production infrastructures and actively participates in professional and academic committees. Her scholarship integrates research-for-design and research-by-design methodologies, supported by extensive case studies, interviews, and design scenario development. She is a member of the Polish Architects’ Association, the Cluster for Sustainable Cities, and the UK Urban AgriTech collective, and she has contributed to editorial and review activities through her involvement in academic conferences and collaborative publications. Her work has been recognized through distinctions such as the Polityka Science Award finalist honor and international design competition recognition, underscoring her impact on sustainable architectural innovation. Her research impact includes 25 citations, 14 publications, and an h-index of 3.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. Szopińska-Mularz M., Prokop A., Wikiera M., Bukowy W., Forsman F., Adaptive reuse of urban structures as a driver of sustainable development goals: a systematic literature review. Sustainability, 2025.

2. Szopińska-Mularz M., Lehmann S., Urban farming in inner-city multi-storey car-parking structures: adaptive reuse potential. Future Cities Environ., 2019.

3. Szopińska-Mularz M., Lehmann S., Balancing increased urban density with green spaces: the marketing of new housing estates in Poland. Buildings, 2023.

4. Szopińska-Mularz M., Adaptive reuse of modern movement car parking structures for controlled environment agriculture: results from an interview study for the innovative design process in cities. City Cult. Soc., 2022.

5. Szopińska-Mularz M., Adaptive Reuse for Urban Food Provision. Cities and Nature, Springer International Publishing, 2022.

Her work advances scientific understanding of adaptive reuse by integrating architectural innovation with sustainable urban food systems, offering evidence-based frameworks that strengthen urban resilience. Through research-driven design methodologies, she provides pathways for cities to repurpose underused infrastructures into productive assets that enhance environmental, social, and economic sustainability.

Christopher Amoah | Sustainable Construction | Research Excellence Award

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Dr. Christopher Amoah | Sustainable Construction | Research Excellence Award

Senior Lecturer | University of the Free State | South Africa

Christopher Amoah is a Senior Lecturer in the Department of Quantity Surveying and Construction Management at the University of the Free State, specialising in construction management, sustainable housing, project management and public procurement. With extensive professional experience as a construction project manager, valuer and consultant, he has led major projects, supervised multidisciplinary teams and contributed to departmental leadership through policy development, programme coordination and accreditation activities. His research focuses on sustainable housing delivery, infrastructure management, procurement systems, construction risk and technology adoption, reflected in numerous peer-reviewed publications, book chapters, conference papers and successful postgraduate supervisions. He actively collaborates with scholars across Africa, serves as an external examiner and moderator for several universities, and undertakes significant editorial and peer-review duties for international journals and conferences. His scholarly contributions have earned recognitions including an NRF C2 rating, institutional research excellence awards, conference commendations and a best paper award at a global congress, supported by service on editorial boards, accreditation panels and academic committees. His research impact includes 459 citations, 54 publications and an h-index of 11.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. A.S. Mohammed, C. Amoah, I. Bala Abdulai, A. Timothy Oluwafemi, J. Abbas, Examining gender disparities in pre-service teachers’ satisfaction levels across educational facilities. Facilities, 2025, 43(5/6), 320–346.

2. C. Amoah, L. Le Roux, Students’ challenges with online remote teaching and learning in South Africa. Int. J. Constr. Educ. Res., 2025, 21(4), 533–553.

3. A.S. Mohammed, C. Amoah, J. Abbas, S. Naayif, Facilities managers vs. mosque management committees: evaluating the need for professional facilities management in mosque operations. Facilities, 2025, 43(5/6), 363–396.

4. C. Amoah, F. Simpeh, Implementation challenges of COVID-19 safety measures at construction sites in South Africa. J. Facilities Manag., 19(1), 111–128.

5. J. du Plessis, C. Amoah, Factors hindering the use of unmanned aerial vehicles for construction project monitoring. Discover Appl. Sci., 2025, 7(7), 782.

Christopher Amoah’s work advances sustainable construction practices, improves public procurement systems, and strengthens infrastructure management frameworks that directly support societal well-being and equitable development. His research provides evidence-based solutions that enhance housing quality. He envisions a future where sustainable, resilient and socially responsive infrastructure drives global progress and inclusive growth.

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

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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.

Sudhakar K | AI and Automation in Architecture | Research Excellence Award

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Dr. Sudhakar K | AI and Automation in Architecture | Research Excellence Award

Associate Professor | Nitte Meenakshi Institute of Technology | India

Dr. K. Sudhakar is an Associate Professor at Nitte Meenakshi Institute of Technology, specializing in Computer Science and Engineering with expertise in machine learning, artificial intelligence, the Internet of Things, and cloud security. He has held key academic leadership roles across reputed institutions, heading CSE departments, coordinating accreditation processes, guiding numerous student projects, and contributing to academic quality enhancement. His research encompasses intelligent systems, IoT and cloud security frameworks, deep learning models, and brain–computer interface applications, resulting in a robust publication record that includes journal articles, IEEE proceedings, international conferences, books, and book chapters. He has advanced technological innovation through multiple patents published and granted across India, the United Kingdom, and Germany. His academic contributions extend to serving as a session chair, program chair, and resource person for conferences, FDPs, and training programs, reflecting his active engagement in scholarly and professional communities. He holds memberships in recognized professional bodies and has earned several awards for excellence in research and education, alongside numerous certifications in emerging technologies. His research impact includes research citations, documents, and h-index that reflect his continual contribution and scholarly influence: 17 citations, 20 publications, and an h-index of 2.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. Sudhakar K., Niveditha S., Sumaiya N., Divyashree K., Geethanjali S.G., Revolutionizing communication protocols through IoT-enabled devices managed by brain–computer interfaces. Concepts and Applications of Brain-Computer Interfaces, 2025, pp. 63–78.

2. Lakshmi M., Sudhakar K., Manjunath P., Mazumder D., Tamilselvi B., Optimizing device performance with BCIs: a user-centric approach to brain data privacy. Concepts and Applications of Brain-Computer Interfaces, 2025, pp. 227–242.

3. Binu C.T., Kumar S.S., Rubini P., Sudhakar K., Enhancing cloud security through machine learning-based threat prevention and monitoring: the development and evaluation of the PBPM framework. Journal Publication, 2024, 19.

4. Sudhakar K.N., Shanthi M.B., Deepfake: an endanger to cyber security. International Conference on Sustainable Computing and Smart Systems, 2023, 17.

5. Ezhilarasu P., Prakash J., Krishnaraj N., Satheesh Kumar D., Sudhakar K., A novel approach to classify nondeterministic finite automata based on more than two loops and its position. SSRG International Journal of Computer Science and Engineering, 2014, 15.

Dr. K. Sudhakar’s research advances intelligent systems, IoT security, and machine learning frameworks that strengthen digital safety, enhance autonomous technologies, and support data-driven innovation. His contributions bridge academic research and real-world applications, enabling secure, scalable, and human-centric technological solutions for industry and society. He aims to drive impactful innovation that shapes resilient and intelligent digital ecosystems globally.

 

Mazyar Taghavi | AI for Urban Planning | Research Excellence Award

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Mr. Mazyar Taghavi | AI for Urban Planning | Research Excellence Award

Iran University of Science and Technology | Iran

Mazyar Taghavi is a researcher in applied mathematics, artificial intelligence, and multi-agent reinforcement learning, affiliated with the Iran University of Science and Technology and Payame Noor University. With dual graduate degrees in applied mathematics and artificial intelligence, he has developed expertise at the intersection of optimization, quantum-inspired computation, intelligent robotics, and autonomous multi-agent systems. His professional experience includes certified research and teaching assistant roles, contributions to national research projects in optimization, optimal control, and AI for social good, and active participation in collaborative scientific initiatives. His research focuses on advanced mathematical modeling, deep and multi-agent reinforcement learning, quantum and neuromorphic computing, and optimal control, resulting in publications across Springer, IEEE, Elsevier, and other scholarly platforms, covering areas such as quantum-inspired MARL, UAV coordination, connected autonomous vehicles, swarm intelligence, and stochastic decision-making. He has delivered keynote speeches and contributed to academic dissemination through invited talks, supported by recognitions that include certified academic roles, society memberships, editorial and peer-review activities, and participation in advanced scientific training programs. His research impact includes 1 citation, 2 documents, and an h-index of 1.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. Taghavi M., Vahidi J., Quantum-inspired multi-agent reinforcement learning for exploration–exploitation optimization in UAV-assisted 6G network deployment. Quantum Mach. Intell., 7(2), 111.
2. Taghavi M., Farnoosh R., Quantum computing and neuromorphic computing for safe, reliable, and explainable multi-agent reinforcement learning: optimal control in autonomous intelligent agents. Iran J. Comput. Sci., 8(3), 1–17.
3. Taghavi M., Farnoosh R., Latent variable modeling in multi-agent reinforcement learning via expectation–maximization for UAV-based wildlife protection. J. Artif. Intell. Mach. Learn. (JAIM), 3(2).
4. Taghavi M., Vahidi J., Q-CMAPO: A quantum-classical framework for balancing exploration and exploitation in multi-agent reinforcement learning. Res. Square, rs-7111581/v1.
5. Taghavi M., Vahidi J., MARL-CC: A mathematical framework for multi-agent reinforcement learning in connected autonomous vehicles: addressing nonlinearity, partial observability, and credit assignment for optimal control.

Mazyar Taghavi’s work advances the scientific foundations of multi-agent reinforcement learning by integrating mathematical modeling, quantum-inspired optimization, and intelligent autonomous systems. His research supports safer, robotics, and smart infrastructures, contributing to technological innovation with real-world impact. He envisions developing intelligent, reliable, and explainable AI systems that drive next-generation autonomy across science, society, and industry.