Se Hyun Park | AI and Automation in Architecture | Best Researcher Award

Published on by Architecture Engineers

Best Researcher Award

 Se Hyun Park,
Chung-Ang University

Se Hyun Park
Affiliation Chung-Ang University
Country South Korea
Scopus ID 8901190100
Documents 154
Citations 2,214
h-index 23
Subject Area AI-Driven Building Control
Event Architecture Engineers Awards
ORCID 0000-0001-7152-5283

Se Hyun Park is a researcher at Chung-Ang University whose scholarly activities focus on AI-driven building control, intelligent building systems, and sustainable engineering technologies. His publication record, citation performance, and measurable research impact demonstrate sustained academic productivity and contributions to interdisciplinary architectural engineering research.[1]

Abstract

This article summarizes the academic profile of Se Hyun Park, highlighting research productivity, publication metrics, scholarly influence, and contributions to AI-driven building control. The assessment is based on publicly available academic indicators and publication databases to evaluate suitability for professional research recognition.[1]

Keywords

Artificial Intelligence, Building Control, Smart Buildings, Sustainable Architecture, HVAC Optimization, Energy Efficiency, Intelligent Systems, Architectural Engineering, Building Automation, Research Excellence.[2]

Introduction

Se Hyun Park has established an academic profile through research addressing intelligent building technologies and AI-based control strategies. His work supports sustainable architectural engineering by improving operational efficiency, indoor environmental quality, and energy management while contributing to interdisciplinary scientific advancement through peer-reviewed publications and collaborative research initiatives.[1][3]

Research Profile

Affiliated with Chung-Ang University, Se Hyun Park has authored 154 indexed publications with more than 2,214 citations and an h-index of 23. His research emphasizes AI-driven building control, smart energy systems, and sustainable engineering, demonstrating consistent scholarly productivity across multidisciplinary architectural engineering domains.[1][2]

Research Contributions

His research has advanced intelligent control algorithms, predictive building management, and energy optimization techniques. These contributions enhance building performance, reduce operational energy consumption, and support environmentally sustainable infrastructure through the integration of artificial intelligence with modern architectural engineering practices and digital automation technologies.[2][3]

Publications

Se Hyun Park has produced an extensive portfolio of peer-reviewed journal articles and conference publications covering intelligent buildings, HVAC optimization, building automation, and energy-efficient systems. His publications reflect sustained research activity and have received considerable scholarly attention within engineering and sustainability research communities.[1][4]

Research Impact

Citation metrics indicate that his research has influenced studies in building intelligence, energy conservation, and smart infrastructure. The combination of publication volume, citation performance, and interdisciplinary collaboration demonstrates measurable academic visibility and continuing relevance within international architectural engineering research communities.[1][2]

Award Suitability

Based on documented scholarly achievements, publication record, citation impact, and sustained contributions to AI-driven building control, Se Hyun Park demonstrates characteristics commonly considered during evaluations for research excellence awards. These measurable academic accomplishments support recognition within the Architecture Engineers Awards framework.[1][2]

Conclusion

Se Hyun Park’s academic profile reflects sustained research productivity, significant scholarly influence, and continued contributions to intelligent building technologies. His publication metrics and interdisciplinary research achievements provide objective evidence of scientific impact, supporting recognition through professional academic award programs and international engineering communities.[1][2]

References

  1. Elsevier. (n.d.). Scopus author details: Se Hyun Park, Author ID 8901190100. Scopus.

    https://www.scopus.com/authid/detail.uri?authorId=8901190100

  2. ORCID. (n.d.). ORCID record for Se Hyun Park.

    https://orcid.org/0000-0001-7152-5283

  3. Building and Environment. Example article related to intelligent building control.

    https://doi.org/10.1016/j.buildenv.2019.106417

  4. Architecture Engineers Awards. Official Event Website.

    https://architectureengineers.com/

Agnieszka Leśniak | AI and Automation in Architecture | Innovative Research Award

Published on by Architecture Engineers

Innovative Research Award

Agnieszka Leśniak
Affiliation Cracow University of Technology
Country Poland
Scopus ID 36708054800
Documents 73
Citations 1257
h-index 20
Subject Area Predicting Renovation Risk in Existing Buildings Using Multilayer Perceptrons: Correlation-Based Feature Screening and Model Architecture Comparison
Event Architecture Engineers Awards
ORCID 0000-0002-4811-5574

Agnieszka Leśniak is affiliated with the Cracow University of Technology, Poland, and has established a research profile in construction engineering, renovation management, and artificial intelligence applications for the built environment. Her scholarly record demonstrates sustained contributions to risk prediction, project management, and data-driven decision-making in architecture and civil engineering.[1]

Abstract

This article summarizes the academic profile of Agnieszka Leśniak, highlighting research activities in construction engineering, renovation risk assessment, project management, and machine learning applications for existing buildings. Her publication record and citation metrics indicate sustained scholarly engagement and measurable influence within architecture and engineering research communities.[1][2]

Keywords

Renovation Risk, Building Engineering, Artificial Intelligence, Multilayer Perceptron, Construction Management, Existing Buildings, Machine Learning, Architecture Engineering, Predictive Analytics, Project Risk Assessment.[2]

3. Introduction

Agnieszka Leśniak conducts interdisciplinary research connecting construction engineering with predictive analytics and artificial intelligence. Her work addresses renovation planning, project uncertainty, and decision-support methodologies that improve engineering management. These studies contribute practical knowledge for sustainable building maintenance and evidence-based infrastructure planning within modern architectural practice.[1][3]

4. Research Profile

Her research profile emphasizes construction project management, renovation risk evaluation, artificial intelligence, and data-driven engineering solutions. Supported by numerous peer-reviewed publications, her scholarly activities demonstrate consistent engagement with innovative methodologies that enhance planning accuracy, resource allocation, and operational efficiency in architecture and civil engineering projects.[1][2]

5. Research Contributions

Leśniak has contributed to predictive modeling techniques for renovation projects by integrating multilayer perceptrons and feature selection approaches. Her investigations improve risk identification, decision reliability, and analytical accuracy while supporting engineers in evaluating complex renovation scenarios through systematic computational methodologies and engineering assessment frameworks.[2][3]

6. Publications

With seventy-three indexed publications, the researcher has developed a substantial body of literature addressing construction management, renovation engineering, project risk, and intelligent prediction systems. These publications have been disseminated through reputable scientific journals, supporting continued academic discussion and technological advancement within engineering disciplines.[1][3]

7. Research Impact

The research portfolio has accumulated more than one thousand citations with a documented h-index of twenty, indicating sustained scholarly recognition. These measurable indicators reflect continuing influence on construction engineering research, particularly in predictive modeling, renovation management, and evidence-based project decision-support methodologies.[1][2]

8. Award Suitability

The documented publication record, citation performance, interdisciplinary research focus, and practical engineering relevance demonstrate characteristics commonly considered for academic recognition. Contributions toward predictive renovation risk analysis and intelligent construction management align with the objectives of professional architecture and engineering research awards.[1][2]

9. Conclusion

Agnieszka Leśniak has established an academically recognized profile through consistent contributions to construction engineering and predictive analytics. Her work integrates engineering knowledge with artificial intelligence to address practical renovation challenges while advancing scientific understanding, supporting future innovation, and strengthening evidence-based engineering research.[1][3]

11. References

  1. Elsevier. (n.d.). Scopus Author Details: Agnieszka Leśniak, Author ID 36708054800. Scopus.https://www.scopus.com/authid/detail.uri?authorId=36708054800
  2. ORCID. (n.d.). Agnieszka Leśniak ORCID Record.https://orcid.org/0000-0002-4811-5574
  3. Leśniak, A. (2023). Predicting Renovation Risk in Existing Buildings Using Multilayer Perceptrons: Correlation-Based Feature Screening and Model Architecture Comparison.DOI:
    https://doi.org/10.3390/buildings13102627

Peng Wang | AI and Automation in Architecture | Editorial Board Member

Published on by Architecture Engineers

Dr. Peng Wang | AI and Automation in Architecture | Editorial Board Member

Researcher | Inspur Group Co.,Ltd | China

Peng Wang is a computer architecture researcher serving as a doctoral researcher at the Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, specializing in GPU rendering optimization, compiler optimization, and microarchitecture-independent performance analysis. He has contributed to multiple high-impact research projects, including the development of RayBench and RenderBench benchmark suites, GPU microarchitecture-independent characteristic profiling tools, and LLVM-based RISC-V vectorization optimizations, demonstrating strong technical leadership in benchmarking, compiler engineering, and heterogeneous computing systems. His research outputs include publications in recognized journals such as Electronics, IEEE Access, and other peer-reviewed venues, along with several patents covering GPU performance optimization, cloud game automation, and feature-analysis methodologies. He has actively supported the scientific community through peer-review service for reputable journals and international conferences, reflecting his growing influence in the fields of computer architecture and intelligent systems. His combined expertise in software-hardware co-design, GPU architecture analysis, and compiler technologies positions him as an emerging leader dedicated to advancing high-performance computing research and innovation.

Profile: ORCID

Featured Publications

1. Wang P., Qu H.L., Latency-Aware and Auto-Migrating Page Tables for ARM NUMA Servers. Electronics, 2025, 14(8), 1685.

2. Wang P., Yu Z.B., LLVM RISC-V RV32X Graphics Extension Support and Characteristics Analysis of Graphics Programs. IEEE Access, 2023, 3291920.

3. Wang P., Yu Z., RenderBench: The CPU Rendering Benchmark Suite Based on Microarchitecture-Independent Characteristics. Electronics, 2023, 12(19), 4153.

4. Wang P., Yu Z., RayBench: An Advanced NVIDIA-Centric GPU Rendering Benchmark Suite for Optimal Performance Analysis. Electronics, 2023, 12(19), 4124.

5. Wang P., Chen Y., Xing M.J., Method for Supporting RISC-V Custom Extension Instructions Based on LLVM. Comput. Syst. Appl., 2021, 31(11), Article 8347.

Peng Wang’s work advances high-performance computing by delivering optimized GPU and CPU rendering benchmark suites, compiler enhancements, and microarchitecture-independent performance tools that strengthen the reliability and efficiency of modern computing systems.He aims to drive global innovation through scalable, energy-efficient, and architecture-aware computing solutions that empower future heterogeneous computing technologies.

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

Published on by Architecture Engineers

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.

Anandakumar Srinivasan | Materials and Technology in Architecture | Best Researcher Award

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Assoc. Prof. Dr. Anandakumar Srinivasan | Materials and Technology in Architecture | Best Researcher Award

Associate Professor | Anna University | India

Dr. S. Anandakumar Srinivasan is an Associate Professor in the Department of Chemistry at Anna University, India, specializing in surface science, nano-hybrid coatings, bio-based polymers, and corrosion-resistant materials. With a doctorate in Polymer Chemistry and Material Science and postdoctoral research in the UK and Portugal, he has over two decades of academic and research experience including leadership roles such as Assistant Director at the Centre for Entrepreneur Development. His research focuses on developing eco-friendly polymer coatings and bio-composite films for industrial and environmental applications. He has authored over 75 peer-reviewed publications in renowned journals such as Progress in Organic Coatings, Journal of Polymer Research, and High Performance Polymers, along with eight books and multiple international patents on biodegradable barrier materials and surface treatments. He has successfully executed numerous projects funded by DST, DRDO, and Anna University and served on editorial boards of leading polymer science journals. His contributions have been recognized with prestigious honors including the IAAM Scientist Medal (Sweden), Technology Innovation Award, Active Researcher Award from Anna University, and the Royal Society Visiting Fellowship (UK). A member of the Society for Polymer Science and American Nano Society, Dr. Anandakumar continues to advance sustainable material innovation through his research on bio-based coatings, nanocomposites, and green manufacturing technologies for industrial and environmental impact. His research impact includes 1,243 citations, 50 publications, and an h-index of 19.

Profiles: Scopus | ORCID | Google Scholar

1. Anandakumar S., Shree Meenakshi K., Facile fabrication of polyaniline–MXene bilayer coatings for enhanced corrosion protection and self-healing on steel substrates. Prog. Org. Coat., 2026, Accepted.

2. Rajiv G., Ashick Naina Mohamed, Rajeswari G.R., Anandakumar S., Development of a partially bio-based sustainable polyurethane coating from non-edible mahua oil. Constr. Build. Mater., 2025, 1, [Article in press].

3. Rajiv G., Jeswin Anto L., Mathumitha K., Anandakumar S., Synergistic effects of biobased PLA and Garnet waste towards enhanced corrosion resistance of epoxy coating. J. Mol. Struct., 2025, 1, [Article in press].

4. Duraibabu D., Mohammed S.A., Suresh Kumar S.M., Anandakumar S., Advanced fabrication and characterization of AMMT nano clay reinforced tri-functional epoxy nanocomposites for superior thermal and mechanical properties. J. Polym. Res., 2024, [Article in press].

5. Dhanapal D., Srinivasan A.K., Rajarathinam M., Muthukaruppan A., Evaluation of augmented thermal, thermo-mechanical, mechanical properties of nano alumina reinforced TGDDM epoxy nanocomposites. High Perform. Polym., 2023, 35, 313–323.

Dr. S. Anandakumar Srinivasan’s pioneering research in sustainable polymer coatings and nano-hybrid composites advances the global shift toward eco-friendly materials by replacing petroleum-based systems with biodegradable, high-performance alternatives. His innovations contribute to corrosion protection, waste valorization, and green manufacturing, driving progress in sustainable industrial technologies and environmental preservation.