Assoc. Prof. Dr. Sihan Huang | Smart manufacturing
| Best Researcher Award
Associate Professor at Beijing Institute of Technology, China.
Dr. Sihan Huang is an Associate Professor at the Beijing Institute of Technology, specializing in intelligent manufacturing systems and digital twin technologies. With a Ph.D. in Mechanical Engineering and a B.S. in Industrial Engineering from the same institution, she has rapidly advanced in academia, supported by postdoctoral experience and international research exposure at the University of Michigan. Dr. Huang has published extensively in top-tier journals, contributing innovative research on reconfigurable manufacturing systems, human-robot collaboration, and smart factories. Her work bridges cutting-edge technologies like blockchain, machine learning, and Industry 5.0, making her a prominent figure in smart manufacturing. Her scientific vision and impactful research output make her a strong candidate for the Best Researcher Award.
🌍 Professional Profile:
🏆 Suitability for the Best Researcher Award :
Dr. Sihan Huang received both her undergraduate and doctoral education from the prestigious Beijing Institute of Technology. She earned her Bachelor of Science in Industrial Engineering in 2014, where she laid a solid foundation in systems design and optimization. She continued her academic journey at the same institution, obtaining a Ph.D. in Mechanical Engineering in 2020. During her Ph.D., she was selected for an international visiting scholar program at the University of Michigan, Ann Arbor (2017–2019), where she deepened her expertise in intelligent systems and global research methods. Her education reflects a strong integration of industrial systems thinking and cutting-edge research methodology, setting the stage for her impactful academic and scientific career.
🏢 Work Experience :
Dr. Sihan Huang has cultivated an impressive academic and research trajectory. Since 2022, she has served as an Associate Professor at the Beijing Institute of Technology, leading research in digital manufacturing systems. From 2020 to 2022, she conducted postdoctoral research at the same institution, contributing to national projects and high-impact research. Notably, she was a visiting Ph.D. researcher at the University of Michigan, Ann Arbor (2017–2019), where she engaged in international collaborative studies on smart manufacturing and digital twin systems. Her academic roles have encompassed mentoring, publishing, and leading interdisciplinary projects. This blend of domestic and global experience underpins her scholarly leadership and reinforces her standing as a promising researcher in intelligent manufacturing.
🏅Awards and Honors
Dr. Sihan Huang has earned recognition through high-impact publications and global research engagements. While specific award titles are not listed in the current profile, her early promotion to Associate Professor and her invitation to conduct research at the University of Michigan indicate strong academic recognition and institutional trust. Her articles in top-tier journals such as Journal of Manufacturing Systems and International Journal of Production Research reflect peer acknowledgment and international impact. Her contributions to the evolving fields of Industry 5.0, human-robot collaboration, and blockchain-integrated systems position her for numerous competitive research honors. Her growing citation base and consistent scholarly output signify her as an emerging leader and a strong contender for distinguished research awards.
🔬 Research Focus :
📘 Industry 5.0 and Society 5.0—Comparison, complementation and co-evolution
📅 Year: 2022 | 📚 Journal of Manufacturing Systems, 64: 424–428
🔍 Cited by: 616
🔐 Blockchain-based data management for digital twin of product
📅 Year: 2020 | 📚 Journal of Manufacturing Systems, 54: 361–371
🔍 Cited by: 310
⚙️ Reconfiguration schemes evaluation based on preference ranking of key characteristics of reconfigurable manufacturing systems
📅 Year: 2017 | 📚 International Journal of Advanced Manufacturing Technology, 89: 2231–2249
🔍 Cited by: 92
🧪 Toward digital validation for rapid product development based on digital twin: a framework
📅 Year: 2022 | 📚 International Journal of Advanced Manufacturing Technology, 1–15
🔍 Cited by: 84
🤖 Dynamic reconfiguration optimization of intelligent manufacturing system with human-robot collaboration based on digital twin
📅 Year: 2022 | 📚 Journal of Manufacturing Systems, 65: 330–338
🔍 Cited by: 69
🏗️ Building blocks for digital twin of reconfigurable machine tools from design perspective
📅 Year: 2022 | 📚 International Journal of Production Research, 60(3): 942–956
🔍 Cited by: 48