Prof. Xing Huang Innovative Leadership | Best Researcher Award

Prof. Xing Huang – Innovative Leadership | Best Researcher Award

🧑‍🏫Prof Xing Huang, Northwestern Polytechnical University, China 

🔗 Professional Profiles

🎓 Education

  • Nov 2016 – Oct 2017: Visiting PhD in Computer Science, Department of Electrical and Computer Engineering, Duke University, USA 🇺🇸
  • Sep 2013 – Jun 2018: PhD in Intelligent Information Processing, College of Physics and Information Engineering, Fuzhou University, China 🇨🇳
  • Sep 2009 – Jun 2013: Bachelor in Computer Science and Technology, College of Mathematics and Computer Science, Fuzhou University, China 🇨🇳

👨‍🔬 Employment

  • Dec 2022 – Present: Full Professor, School of Computer Science, Northwestern Polytechnical University, China 🇨🇳
  • Aug 2022 – Nov 2022: Postdoctoral Research Fellow, Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong 🇭🇰
  • Dec 2020 – Apr 2022: Humboldt Research Fellow, Postdoctoral Research Fellow, Department of Electrical and Computer Engineering, Technical University of Munich, Germany 🇩🇪
  • Dec 2019 – Nov 2020: TUFF Fellow, Postdoctoral Research Fellow, Department of Electrical and Computer Engineering, Technical University of Munich, Germany 🇩🇪
  • Sep 2018 – Oct 2019: MOST Fellow, Postdoctoral Research Fellow, Department of Computer Science, National Tsing Hua University, Taiwan 🇹🇼

💡 Research Topics

  • 🧩 Electronic Design Automation
  • 🧬 Microfluidic Biochips and VLSI Circuits
  • 🤖 Artificial Intelligence and Machine Learning
  • 📊 Algorithm Design and Analysis
  • 🖥️ Computer-Aided Design

📞 Contact Information

Publication Top Noted

Paper Title : Hdr-nerf: High dynamic range neural radiance fields

    • Authors: Xin Huang, Qi Zhang, Ying Feng, Hongdong Li, Xuan Wang, Qing Wang
    • Journal: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition
    • Year: 2022
    • Citations : 110

Paper Title : AIM 2020: Scene relighting and illumination estimation challenge

    • Authors: Majed El Helou, Ruofan Zhou, Sabine Süsstrunk, Radu Timofte, Mahmoud Afifi, Michael S Brown, Kele Xu, Hengxing Cai, Yuzhong Liu, Li-Wen Wang, Zhi-Song Liu, Chu-Tak Li, Sourya Dipta Das, Nisarg A Shah, Akashdeep Jassal, Tongtong Zhao, Shanshan Zhao, Sabari Nathan, M Parisa Beham, R Suganya, Qing Wang, Zhongyun Hu, Xin Huang, Yaning Li, Maitreya Suin, Kuldeep Purohit, AN Rajagopalan, Densen Puthussery, PS Hrishikesh, Melvin Kuriakose, C Victor Jiji, Yu Zhu, Liping Dong, Zhuolong Jiang, Chenghua Li, Cong Leng, Jian Cheng 
    • Journal: Computer Vision–ECCV 2020 Workshops: Glasgow, UK, August 23–28, 2020, Proceedings, Part III 16
       Year: 2020
    • Citations:  47

Paper Title : Humannorm: Learning normal diffusion model for high-quality and realistic 3d human generation

    • Authors: Xin Huang, Ruizhi Shao, Qi Zhang, Hongwen Zhang, Ying Feng, Yebin Liu, Qing Wan 
    • Journal: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition 
    • Year: 2024
    • Citations:  26

Paper Title : Local implicit ray function for generalizable radiance field representation

    • Authors: Xin Huang, Qi Zhang, Ying Feng, Xiaoyu Li, Xuan Wang, Qing Wang  
    • Journal: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition
    • Year: 2023
    • Citations: 21

Paper Title : SA-AE for any-to-any relighting

    • Authors: Zhongyun Hu, Xin Huang, Yaning Li, Qing Wang
    • Journal:
      European Conference on Computer Vision
    • Year: 2020
    • Citations: 8

Prof Li Liu | Innovative Leadership | Best Researcher Award | 2831

Prof. Li Liu-Innovative Leadership-Best Researcher Award

Prof Li Liu, Soochow University, China

🔗 Professional Profiles

📚 Dr. Li Liu – Associate Professor at Soochow University

Li Liu is an associate professor in the School of Computer Science and Technology at Soochow University, China. He earned his Ph.D. in Computer Science from Rutgers, The State University of New Jersey, in 2018. Dr. Liu teaches courses in Software Engineering, Machine Learning, Data Visualization, Discrete Mathematics, and Stochastic Process. His research interests are focused on Pattern Recognition, Machine Learning, Computer Vision, and Scientific Visualization. With over 20 journal publications, his research has been supported by the National Science Foundation of China and the Jiangsu Provincial Natural Science General Program.

🧠 Research and Innovations

Completed/Ongoing Research Projects:

  • 2021.1-2023.12: Research on Activity Representation and Recognition for Time-Varying Volume Data Visualization, funded by the National Science Foundation of China (62002253).
  • 2021.1-2022.12: Research on Feature Extraction Method of Fuzzy Clustering for Scientific Visualization, funded by the Jiangsu Provincial Natural Science General Program (20KJB520027).

📈 Citation Index

  • About 100

🔬 Patents

  • Published/Under Process: 3

📝 Journals Published (SCI, Scopus, etc.):

  • ACM Computing Surveys
  • Pattern Recognition
  • Computer Graphics Forum
  • IEEE Computer Graphics and Applications
  • Journal of Visualization
  • IEEE Access

🌐 Collaborations

  • Rutgers University
  • Central South University of China
  • Nanjing University

👥 Professional Memberships

  • China Computer Federation (CCF)
  • Jiangsu Computer Society (JSCS)
  • Jiangsu Artificial Intelligence Society (JSAI)

🔍 Areas of Research

  • Pattern Recognition
  • Machine Learning
  • Scientific Visualization

🌟 Contributions

Dr. Liu has proposed new theories and methods for scientific visualization, machine learning, and pattern recognition. He has expanded the knowledge system and application scope of Lie group theory and dynamic fuzzy logics. His efforts have helped researchers better understand the basics and the state-of-the-art in these fields.

Publication Top Noted

A Lie group semi-supervised FCM clustering method for image segmentation

    • Authors: Haocheng Sun, Li Liu, Fanzhang Li
    • Journal: Pattern Recognition
    • Year: 2024

A Lie group kernel learning method for medical image classification

    • Authors: Li Liu, Haocheng Sun, Fanzhang Li
    • Journal: Pattern Recognition
    • Year: 2023

A Survey on Dynamic Fuzzy Machine Learning

    • Authors: Li Liu, Fanzhang Li
    • Journal: ACM Computing Surveys
    • Year: 2023

Multi-Stage Meta-Learning for Few-Shot with Lie Group Network Constraint

    • Authors: Li Liu
    • Journal: Entropy
    • Year: 2020

Visualizing Acoustic Imaging of Hydrothermal Plumes on the Seafloor

    • Authors: Not specified
    • Journal: Not specified
    • Year: 2020

Abdulrahman Bahrami-Innovative Leadership-Best Innovation Award 

Abdulrahman Bahrami-Innovative Leadership-Best Innovation Award 

Hamedan University of medical sciences-Iran 

Author Profile 

Early Academic Pursuits

Abdulrahman Bahrami's academic journey began with a strong focus on Occupational Health. He obtained his Associated degree in Occupational Health from Tehran University in 1982-1984, followed by a B.Sc. in the Faculty of Safety and Occupational Health. Subsequently, he pursued an M.Sc. in Occupational Health at Tarbiat Modares University in Iran. His academic pursuits culminated in a Ph.D. in Occupational Health from Brunel University, England, where he specialized in chemical pollution.

Professional Endeavors

Dr. Bahrami has held various scientific and executive positions throughout his career. Starting as an Assistant Professor in Occupational Health at Hamadan University of Medical Sciences in 1996, he progressed to become an Associate Professor in 2001 and achieved the rank of Professor in 2008. His leadership roles include serving as the Dean of Excellence Center for Occupational Health and Head of Occupational Health Department at Hamadan University.

He also held significant national roles, such as being the Deputy of the Center for Environmental and Occupational Health at the Iranian Ministry of Health and Medical Education from 2010 to 2014. Dr. Bahrami's dedication extended to representing the Ministry of Health in the Chemical Safety Commission of the Ministry of Foreign Affairs and being a member of the Stockholm Convention Monitoring.

Contributions and Research Focus

Dr. Bahrami's research interests revolve around trace residue analysis of chemical compounds in air and biological samples using micro extraction methods. His notable contributions include developing novel methods based on microextraction by packed sorbent, needle trap extraction, and utilizing materials like Metal-Organic Frameworks (MOFs) and nanotubes. His research has practical applications in determining chemical pollutants and toxins, contributing to the field of analytical toxicology.

As a thesis supervisor for Ph.D. and M.Sc. candidates, he guided numerous students in innovative research projects, addressing issues such as air quality, occupational exposure, and biological monitoring.

Accolades and Recognition

While specific accolades and recognition details are not provided, Dr. Bahrami's extensive contributions to the field of Occupational Health and his role in leadership positions suggest a level of acknowledgment within the academic and professional community.

Impact and Influence

Dr. Bahrami's impact is evident through his leadership in establishing and heading the Excellence Center for Occupational Health. His research has practical implications for assessing and controlling exposure to hazardous substances in various occupational settings. Additionally, his involvement in national boards and commissions indicates his influence in shaping occupational health policies and guidelines in Iran.

Legacy and Future Contributions

With a career spanning teaching, research, and leadership, Dr. Abdulrahman Bahrami has left a lasting legacy in the field of Occupational Health. His focus on innovative research methods and commitment to educating future generations of scientists suggests a continued contribution to the advancement of occupational health and safety practices in Iran and beyond. Dr. Bahrami's future contributions are likely to involve further research, mentorship, and advocacy for occupational health and safety measures.

Notable Publications