Xiaodong Feng | Robotics | Best Researcher Award

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Prof. Xiaodong Feng | Robotics | Best Researcher Award

Prof. Xiaodong Feng at Shaoxing University, China

Feng Xiaodong, born in June 1987, is an Associate Professor at the School of Civil Engineering, Shaoxing University of Arts and Sciences. Recognized as one of the first leading talents in Zhejiang Province’s 5246 Talent Project and a young talent under Shaoxing’s Special Branch Plan, he specializes in structural engineering. With an international academic footprint and a strong background in intelligent structural systems, Dr. Feng has led numerous national-level projects and published extensively in high-impact journals. His work integrates innovative structural design with smart technologies, contributing significantly to the advancement of flexible and adaptive engineering solutions. 🌉📚🤖

Publication Profile

Scopus

Academic Background

Feng Xiaodong completed his undergraduate studies in Civil Engineering at Central South University (2006–2010), followed by a master’s in Solid Mechanics (2010–2012) and a Ph.D. in Structural Engineering (2012–2016), under Professor Guo Shaohua. He then pursued postdoctoral research at Zhejiang University (2018–2020) with Professor Luo Yaozhi. His academic training spans mechanics, structural analysis, and intelligent systems, providing a robust foundation for his interdisciplinary research. 📘🎓🔬

Professional Experience

Dr. Feng began his academic career at Shaoxing University of Arts and Sciences in 2016 as a Lecturer, advancing to Associate Professor and Laboratory Director in 2021. He also served as a visiting scholar at Kyoto University, Japan (2022–2023). Throughout his career, he has led key research initiatives, mentored students, and collaborated with both academic and industrial partners on advanced structural systems. His experience bridges practical engineering applications and cutting-edge research. 🏢👨‍🏫🌍

Awards and Honors

Feng Xiaodong has received multiple prestigious awards, including two First Prizes and two Second Prizes from the China Steel Structure Association for technological innovation and scientific progress in large-span structures. He also received honors from the Invention and Entrepreneurship Award and Zhejiang Province. These accolades recognize his contributions to the development, design, and digital construction of complex spatial structures, as well as intelligent construction technologies. His pioneering work in structural mechanics and smart infrastructure has earned both national and regional acclaim. 🏆🏗️

Research Focus

Dr. Feng’s research revolves around flexible, movable, and intelligent structures, integrating AI and machine learning for structural design and health monitoring. His key interests include tensegrity structures, prefabricated systems, large-span spatial structures, and structural dynamics. He also focuses on collaborative structural-material design and building industrialization. His interdisciplinary approach combines theoretical innovation with practical applications, aimed at advancing the construction industry’s automation and intelligence. 🤖🧠🏗️📊

Publication Top Notes

📄 Vibration control and robustness analysis of tensegrity structures via fuzzy dynamic sliding mode control method
🗓️ Year: 2024 | 📚 Journal: Structures | 📊 Cited by: 3

📄 Joint learning of structural and textual information on propagation network by graph attention networks for rumor detection
🗓️ Year: 2024 | 📚 Journal: Applied Intelligence | 📊 Cited by: 1

📄 Structural-topic aware deep neural networks for information cascade prediction
🗓️ Year: 2024 | 📚 Journal: PeerJ Computer Science | 📊 Cited by: 1

Conclusion

Dr. Feng Xiaodong, an Associate Professor at Shaoxing University of Arts and Sciences, is a nationally recognized expert in Structural Engineering, specializing in intelligent structures, AI-integrated design, and prefabricated construction technologies. With over 20 peer-reviewed publications in leading journals such as Soft Robotics, Structures, and Structural Control & Health Monitoring, he demonstrates consistent research excellence. As the principal investigator of numerous national and regional research projects, and a recipient of multiple high-level awards from the China Steel Structure Association and Zhejiang Province, Dr. Feng has shown both academic leadership and practical innovation. His international exposure as a Visiting Scholar at Kyoto University and his role in training future engineers across disciplines further underscore his qualifications. Dr. Feng’s contributions significantly advance the field of intelligent structural systems and make him an outstanding candidate for a Best Researcher Award.

 

 

Behnaz Sohani | Robotics | Best Researcher Award

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Dr. Behnaz Sohani | Robotics | Best Researcher Award

Assistant professor, Loughborough University, United Kingdom

Dr. Behnaz Sohani is an accomplished academic and researcher in Robotics and Biomedical Engineering, specializing in object and scene recognition, assistive robotics, rehabilitation systems, and healthcare robotics. She currently serves as a Co-Director of the Biorobotics and Healthcare/Medical Technologies (BMTec) Laboratory and as a Lecturer in Robotics at the University of Lincoln. With over 16 years of experience in education, research, and administration, Dr. Sohani is passionate about advancing technology and improving healthcare through innovative robotics solutions. 🚀🤖📚

Profile

  • Scopus
  • ORCID
  • Google Scholar

    Strengths for the Award

    1. Community-Oriented Research: Dr. Behnaz Sohani’s work in robotics and biomedical engineering has a clear impact on community health and well-being. Her research focuses on developing assistive and healthcare robotics, which directly benefits individuals with medical conditions and those needing rehabilitation. The development of medical imaging devices and intelligent robots aligns well with the award’s focus on community impact.
    2. Innovative Contributions: Dr. Sohani has been involved in groundbreaking projects, such as designing imaging devices for early detection of brain strokes and cancers. Her use of AI and advanced technologies in healthcare demonstrates innovation that addresses significant community health challenges.
    3. Leadership and Collaboration: As the Co-Director of the Biorobotics and Healthcare/Medical Technologies Laboratory, she has shown strong leadership in driving impactful research projects. Her ability to collaborate with both academic and industrial partners, including medical professionals, enhances the relevance and application of her research.
    4. Educational Impact: Dr. Sohani’s role as a lecturer and mentor at the University of Lincoln contributes to shaping the next generation of engineers and researchers. Her teaching covers a broad spectrum of robotics and biomedical engineering topics, ensuring that her knowledge and passion are shared with students who can continue to drive community-oriented innovations.
    5. Grants and Recognition: Securing significant grants, such as those from the Royal Society and European Regional Development Fund, underscores her ability to attract funding for projects with high community impact. Her successful grant applications reflect recognition and validation from the research community and funding bodies.

    Areas for Improvement

    1. Broader Community Engagement: While Dr. Sohani’s work is impactful within academic and healthcare circles, increasing outreach to broader community stakeholders could enhance the visibility and accessibility of her innovations. Engaging more directly with community organizations or public health initiatives could amplify her research’s community impact.
    2. Communication of Impact: Dr. Sohani’s CV highlights numerous achievements and research outputs but could benefit from more explicit examples of how her work has directly improved or benefited community members. Providing case studies or testimonials could better illustrate the tangible benefits of her research.
    3. Public Awareness: Increasing public awareness about the practical applications of her research could further strengthen the case for the award. This could involve more public engagement activities, such as workshops, seminars, or media outreach, to showcase how her technologies are being used in real-world scenarios.

       

      Education

      Dr. Sohani earned her PhD in Robotics and Biomedical Engineering from London South Bank University (2017-2021). Her doctoral research focused on medical imaging for diagnostic applications, particularly in detecting brain abnormalities using microwave imaging. 🧠🎓

      Experience

      Dr. Sohani has held various academic and research positions. Since January 2021, she has been a Lecturer in Robotics and Biomedical Engineering and the Lead and Director of the BMTec Laboratory at the University of Lincoln. Her roles include generating research income, publishing research outputs, and delivering high-quality teaching programs. Previously, she served as a Postdoctoral Research Fellow at London South Bank University, where she designed medical devices augmented by AI. 📊🧪👩‍🏫

      Research Interests

      Dr. Sohani’s research interests encompass robotics and biomedical engineering, with a focus on assistive robotics, healthcare robotics, path planning, real-time control, computer vision, signal processing, and AI technologies. She is dedicated to advancing the early detection and management of medical conditions and addressing critical healthcare challenges through innovative robotic solutions. 🤖🩺🔍

      Awards

      Dr. Sohani has received several prestigious awards and grants, including successful grant applications to the Royal Society (£70K), being the principal investigator on three research projects funded by the European Regional Development Fund (ERDF), and her PhD funding from the European Union’s Horizon research & innovation program under the Marie Sklodowska-Curie Grant Agreement. 🏆🎓💼

       Publications

      1. “Revolutionizing Demand Response Management: Empowering Consumers through Power Aggregator and Right of Flexibility.” Energies 17.6: 1419, (2024). Cited by 3 articles
      2. Aliyu, M. et al. “An artificial neural network model for the prediction of entrained droplet fraction in annular gas-liquid two-phase flow in vertical pipes.” International Journal of Multiphase Flow 164 (2023): 104452. Cited by 2 articles
      3. Nnadi, S. et al. “Development, Experimental, and Numerical Characterisation of Novel Flexible Strain Sensors for Soft Robotics Applications”, Robotics, 13(7), 103, (2024). Cited by 5 articles
      4. Webber, M., et al. “A techno-economic review of direct air capture of moisture processes: sustainable versus energy-intensive methods.” International Journal of Environmental Science and Technology: 1-35, (2024). Cited by 7 article
      5. Sohani, B. et al. “Developing a Comprehensive Model for the Prevention of Tension Neck Syndrome: A Focus on Musculoskeletal Disorder Prevention Strategies.” Advanced Robotics and Automation (WRC SARA), Beijing, China, pp. 541-548. IEEE, (2023). Cited by 4 articles

       

Heung-Shik Lee | Robotics | Best Researcher Award

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Prof. Heung-Shik Lee | Robotics | Best Researcher Award

Professor, Joongbu University, South Korea

Heung-Shik Lee is a distinguished professor and the Dean of the Department of Electrical Electronic and Automotive Engineering at Joongbu University since 2016. 🌟 With a solid background as a technical advisory member for the Ministry of SMEs and Startups and the Ministry of Environment, Prof. Lee has made significant contributions to the field. Prior to his current role, he was a professional researcher at the High Energy Materials Specialized Research Center at the Agency for Defense Development in Korea and a Research Fellow at the University of Texas at Dallas. 🌐

Profile

Strengths for the Award:

  1. Innovative Research Focus: Prof. Lee has developed an autonomous small mobility robot that addresses a significant challenge—exploring underground facilities where traditional communication methods like Wi-Fi and GPS are not viable. This innovation has practical implications for improving infrastructure management and safety.
  2. Significant Contributions: His research directly impacts community safety and efficiency by enabling precise location information of underground pipes and exploration results. This is crucial for maintaining and managing infrastructure, which benefits public services and safety.
  3. Professional Expertise: Prof. Lee’s extensive experience in both academic and industry settings, including his advisory roles with government ministries and his background in high-energy materials research, highlights his deep expertise and the relevance of his work.
  4. Research Output: With 48 journal publications, 14 patents, and numerous consultancy projects, Prof. Lee demonstrates a high level of productivity and impact in his field. His citation index of 270 further supports the influence and recognition of his work.
  5. Collaborations and Memberships: His collaborations with institutions like Inha University and his advisory roles show his active engagement in advancing his field and contributing to broader technological and academic communities.

Areas for Improvement:

  1. Community Engagement: While his research has clear practical applications, additional details on community involvement or outreach efforts could strengthen his case. Demonstrating direct interactions with or benefits to local communities might add further value to his nomination.
  2. Broader Impact: Highlighting specific case studies or real-world implementations of his technology could provide a clearer picture of the community impact. Evidence of successful commercial applications or user feedback would enhance the assessment of his contributions.
  3. Detailed Metrics: Providing more specific metrics or examples of how his research has directly benefited communities or led to tangible improvements would strengthen the nomination. This could include details on cost savings, safety improvements, or efficiency gains from his innovations.

Education

Prof. Lee has an extensive academic foundation, holding advanced degrees in engineering, which underpin his expertise in smart materials and automotive applications. 📚

Experience

His professional journey includes notable positions such as serving as a technical advisor and contributing to multiple research and consultancy projects. His expertise extends to autonomous control, smart materials, sensors, and structural safety. 🚀

Research Interests

Prof. Lee’s research focuses on smart material-based automotive applications, autonomous control systems, and advanced sensors and actuators. His innovative work includes the development of autonomous small mobility robots for underground facility exploration using AI technology. 🤖

Awards

Prof. Lee is nominated for the Best Researcher Award, recognizing his exceptional contributions to the field of engineering and technology. 🏆

Publications

Mask R-CNN-Based Stone Detection and Segmentation for Underground Pipeline Exploration Robots

An Inverse Perspective Mapping-Based Approach for Generating Panoramic Images of Pipe Inner Surfaces

Analysis of Used Cars Price Determinant Factors Using IPA | IPA

Multiple IMU sensor fusion using resolution refinement method to reduce quantization error