PhD Candidate at Harbin Institute of Technology, China.
Bowen Duan is a Ph.D. candidate in Civil Engineering at the School of Environment, Harbin Institute of Technology, under the mentorship of Prof. Jinliang Gao. His research is centered on water distribution networks, particularly the optimization of modeling techniques and advanced leakage detection methodologies. Through integrating data-driven methods and optimization algorithms, he aims to address critical urban water management challenges such as low modeling precision and complex leakage identification. His research output includes journal and international conference publications that reflect both scientific rigor and real-world application. Duan’s recent work has been featured in Energies, emphasizing the relevance of his research to pressing environmental infrastructure issues. He demonstrates a promising trajectory as a future leader in sustainable water management.
🌍 Professional Profile:
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ORCID
🏆 Suitability for the Best Researcher Award :
Bowen Duan stands out as a highly suitable candidate for the Best Researcher Award due to his impactful research in optimizing water distribution networks—an area critical to sustainable urban development. His application of advanced algorithms for leakage detection significantly improves operational efficiency in real-world water systems. Publishing in top-tier journals and presenting at international conferences, he has shown remarkable academic maturity and innovation. His contributions bridge theoretical advancements and practical utility, reflecting both depth and foresight. Despite being at an early stage in his career, his interdisciplinary approach, commitment to solving complex engineering problems, and drive for impactful outcomes underscore his potential to contribute meaningfully to environmental engineering and resource sustainability on a global scale.
🎓 Education :
Bowen Duan is currently pursuing a Ph.D. in Civil Engineering at the School of Environment, Harbin Institute of Technology (HIT), one of China’s leading institutions for environmental and engineering sciences. Under the guidance of Prof. Jinliang Gao, his academic focus includes water system modeling, hydraulic simulations, and smart detection technologies. His graduate training emphasizes multidisciplinary learning, combining civil engineering fundamentals with advanced data analytics, systems optimization, and environmental sustainability principles. He has also engaged in national and international academic discourse through conferences and collaborative work. Bowen’s educational background demonstrates strong technical grounding, critical thinking, and a forward-looking perspective essential for tackling complex challenges in water infrastructure and management systems.
🏢 Work Experience :
Bowen Duan has acquired valuable research experience through active engagement in multiple water management projects during his Ph.D. studies at Harbin Institute of Technology. His work involves hydraulic modeling, smart sensing, leakage detection, and intervention strategy analysis in water distribution networks. He has published in peer-reviewed journals and presented at renowned conferences such as the Computing and Control for the Water Industry Conference (CCWI 2023, UK), indicating early international exposure. His ability to combine field data with computational techniques highlights practical problem-solving skills. Bowen is also familiar with simulation software, data acquisition systems, and algorithmic design. His research is informed by both theoretical inquiry and applied engineering, making him a capable young scholar with a growing industry-relevant portfolio.
🔹 Awards and Honors
While specific awards and honors are yet to be disclosed, Bowen Duan has gained notable academic recognition through conference acceptances and journal publications, including in the international journal Energies. His participation in the prestigious 19th Computing and Control for the Water Industry (CCWI) Conference in the UK in 2023 reflects peer recognition of his research relevance and quality. These achievements in a competitive academic environment indicate his rising status in the field of environmental and civil engineering. As a doctoral researcher, he continues to build a record of excellence that could soon be accompanied by formal honors, research grants, or innovation awards. His current trajectory and impactful work strongly suggest a promising candidate for future accolades.
🔬 Research Focus :
Bowen Duan’s research centers on optimizing water distribution networks by enhancing hydraulic modeling precision and leakage detection. His innovative approach combines traditional civil engineering knowledge with modern computational tools—such as data-driven optimization, spatial pressure correlation, and real-time monitoring—to develop more responsive and accurate detection systems. His work tackles key problems including system complexity, modeling inefficiencies, and slow leak identification in urban water supply systems. He has investigated behavioral influences on water-saving in public buildings and contributed insights on psychological interventions. Through international conference presentations and journal articles, Bowen advances both theoretical frameworks and practical applications that enhance urban resilience, sustainability, and water conservation efforts. His contributions position him at the intersection of engineering, data science, and sustainability.
📘 Energy-Efficient Management of Urban Water Distribution Networks Under Hydraulic Anomalies: A Review of Technologies and Challenges
📅 Year: 2025 | 🧪 Journal: Energies | ✍️ Authors: Bowen Duan, Jinliang Gao, Huizhe Cao, Shiyuan Hu
🔗 DOI: 10.3390/en18112877 | 🧷 Publisher: MDPI
📝 Evaluating the Dynamic Psychological and Behavioral Changes of Water-Saving in Public Buildings Under Effective Interventions
📅 Year: 2024 | 📄 Type: Preprint | ✍️ Authors: Bowen Duan, Jinliang Gao, Wenyan Wu, Wenjuan Guo, Jinghui Wang, Shanshan Zhang, Chao Wen, Yuan Tian, Chang Shen
🔗 DOI: 10.22541/essoar.171535804.44094305/v1 | 🧷 Platform: ESSOAr