Prof Dr. Weixu liu | Big Data Award | Best Researcher Award

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Prof Dr. Weixu liu |Β Big Data Award |Β Best Researcher Award

Prof Dr. Weixu liu, Anhui Medical University, China

Associate Professor Weixu Liu of Anhui Medical University’s Department of Computer Science earned his Ph.D. from Zhejiang University in 2022. Specializing in big data analysis, machine learning, non-destructive evaluation, and structural health monitoring, Dr. Liu has published over 20 peer-reviewed articles and holds numerous patents and software copyrights. A senior member of the China Instrument and Control Society and the Chinese Society for Vibration Engineering, he has been recognized with multiple teaching awards, including a third-class prize in Anhui Province. His leadership in significant projects, such as the Anhui Provincial Outstanding Young Talent Project, and his involvement in national key R&D plans underscore his impactful contributions to the field of computer science and engineering.

Professional Profile:

Scopus

Suitability for the Research for Best Researcher Award

Assoc. Prof. Dr. Weixu Liu is a highly suitable candidate for the Research for Best Researcher Award due to his significant contributions to the fields of big data analysis, machine learning, non-destructive evaluation, and structural health monitoring. His academic achievements, extensive research activities, and innovative contributions highlight his excellence in research and development.

πŸŽ“ Academic Expertise

Associate Professor, Department of Computer Science, Anhui Medical University πŸŽ“
Weixu Liu is an accomplished Associate Professor, Deputy Director, and Master Supervisor at Anhui Medical University’s Department of Computer Science. He earned his Ph.D. from Zhejiang University in 2022.

Research Interests and Contributions

Dr. Liu’s research focuses on big data analysis, machine learning, non-destructive evaluation, and structural health monitoring. He has published over 20 peer-reviewed journal articles and holds more than ten national invention patents, twenty utility model patents, and ten national computer software copyrights. His work has been supported by various government and corporate grants.

Professional Achievements

Dr. Liu is a senior member of the China Instrument and Control Society and a member of the Chinese Society for Vibration Engineering. He has received multiple awards for his teaching achievements, including a third-class prize in Anhui Province. He has led several significant projects, including Anhui Provincial Outstanding Young Talent Project and various municipal and national science and technology projects.

Innovations and Impact

Dr. Liu’s research has resulted in substantial scientific and technological advancements, including a conversion of achievements worth 500,000 RMB. His involvement in national key R&D plans and extensive project experience highlights his significant role in advancing the field of computer science and engineering.

Publication Top Notes:

  • Title: Multi-Feature Integration and Machine Learning for Guided Wave Structural Health Monitoring: Application to Switch Rail Foot
    • Citations: 20
    • Year: 2021
  • Title: Numerical Investigation of Locating and Identifying Pipeline Reflectors Based on Guided-Wave Circumferential Scanning and Phase Characteristics
    • Year: 2020
    • Open Access: Yes
  • Title: Sprouting Potato Recognition Based on Deep Neural Network GoogLeNet
    • Citations: 5
    • Year: 2018
  • Title: Phase Characteristic Analysis and Experimental Study on the Guided Wave Reflected from Expressway Guardrail Posts
    • Citations: 3
    • Year: 2017
  • Title: Numerical Simulation and Experimental Investigation on Ultrasonic Guided Waves in Multilayered Pipes Based on SAFE
    • Citations: 14
    • Year: 2014

 

 

Prof. Jianfeng Guo | Big Data Analysis in Innovation | Best Researcher Award

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Prof. Jianfeng Guo | Big Data Analysis in Innovation | Best Researcher Award

Prof. Jianfeng Guo, University of Chinese Academy of Sciences, China

Prof. Jianfeng Guo is a distinguished professor at the Energy and Environmental Policy Research Center of the Institute of Policy and Management, Chinese Academy of Sciences (CAS), where he has been a key figure since 2010 and has served as a professor since 2018. He earned his Ph.D. in Mechanical Engineering and Automation from Zhejiang University in 2007 and completed postdoctoral research at Tsinghua University. Jianfeng’s research spans Energy and Environmental Policy, Big Data Analysis, Technology Foresight, Decision Support Systems, and Knowledge Management. He has led over 60 significant projects, including collaborations with Baidu Big Data Lab and Ant Financial Services Group, and has published more than 90 papers and holds multiple patents and software copyrights. His international experience includes visits to top institutions and collaborations with global software companies.

🌍 Professional Profile

Scopus

πŸŽ“ Education

Jianfeng Guo earned his Ph.D. in Mechanical Engineering and Automation from Zhejiang University in December 2007. He completed postdoctoral research at the CIMS Engineering Research Center of Tsinghua University from January 2008 to December 2009. He was a Senior Visiting Scholar at NEC China Research Institute from August 2009 to March 2010.

πŸ”¬ Research Interests

Jianfeng specializes in Energy and Environmental Policy, Big Data Analysis, Technology Foresight, Decision Support Systems, and Knowledge Management.

🏒 Current Position

Since March 2010, Jianfeng has been with the Energy and Environmental Policy Research Center of the Institute of Policy and Management, Chinese Academy of Sciences (CAS), where he has served as a professor since 2018. He is also the Director of the Research Department for Think Tank Construction at the Institutes of Science and Development, CAS.

🌐 Notable Projects & Collaborations

Jianfeng has led over 60 projects, including NSFC projects, national programs, and enterprise-commissioned projects. He has collaborated with Baidu Big Data Lab and Ant Financial Services Group, contributing to advancements in big data and financial security.

πŸ“ Publications & Patents

He has published more than 90 papers, including over 60 in international journals, and holds 4 invention patents and 15 computer software copyrights.

🌍 International Experience

Jianfeng has visited prestigious institutions such as the University of Oldenburg, Imperial College, and Cambridge University, and worked with international software companies like ASCORA and TIE.

Publication Top Notes:

  • Title: Graph-based algorithm for exploring collaboration mechanisms and hidden patterns among top scholars
    • Cited by: 1
    • Year: 2024
  • Title: A framework of cloud-edge collaborated digital twin for flexible job shop scheduling with conflict-free routing
    • Cited by: 3
    • Year: 2024
  • Title: Simulation research on the evolution pathway planning of energy supply and demand in China under the dual carbon targets
    • Cited by: 2
    • Year: 2023
  • Title: Electric vehicle adoption and local PM2.5 reduction: Evidence from China
    • Cited by: 7
    • Year: 2023
  • Title: Pathways for municipalities to achieve carbon emission peak and carbon neutrality: A study based on the LEAP model
    • Cited by: 53
    • Year: 2023

 

 

 

Dr. Kittichai Lavangnananda | Data Science Awards | Best Researcher Award

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Dr. Kittichai Lavangnananda | Data Science Awards | Best Researcher Award

Dr. Kittichai Lavangnananda, University of Luxembourg, Thailand

Dr. Kittichai Lavangnananda holds a Ph.D. in Artificial Intelligence from Cardiff University, UK (1996), an M.Sc. in Computer Science from The University of Wales Cardiff, UK (1987), and a B.Sc. in Computer Science from The University of Hull, UK (1985). He currently serves as an Associate Professor at King Mongkut’s University of Technology Thonburi (KMUTT), where he also holds administrative positions as Associate Dean on Research, International Relations, and Academic Quality Assurance, and Head of Software Technology Division. His research interests include Computational Intelligence, Data Science, Evolutionary Computation, Machine Learning, Deep Learning, and Urban Planning. Kittichai has extensive international collaboration and experience in academia and technology development. πŸ€–

Professional Profile:

Scopus

πŸŽ“ Qualification:

Dr. Kittichai Lavangnananda is an accomplished academic with a Ph.D. in Artificial Intelligence from Cardiff University, UK (1996), complemented by an M.Sc. in Computer Science from The University of Wales Cardiff (1987), and a B.Sc. in Computer Science from The University of Hull, UK (1985). Currently serving as an Associate Professor at King Mongkut’s University of Technology Thonburi (KMUTT), he holds pivotal administrative roles including Associate Dean for Research, International Relations, and Academic Quality Assurance. Dr. Lavangnananda also heads the Software Technology Division, contributing significantly to the fields of Computational Intelligence, Data Science, Evolutionary Computation, Machine Learning, Deep Learning, and Urban Planning through his research and leadership.

πŸ‘¨β€πŸ« Teaching Experience:

Dr. Kittichai Lavangnananda is an Associate Professor at King Mongkut’s University of Technology Thonburi (KMUTT), where he serves as the Associate Dean of Research, International Relations, and Academic Quality Assurance, and Head of the Software Technology Division. With a Ph.D. in Artificial Intelligence from Cardiff University, UK, and extensive international experience, his teaching spans key areas including Artificial Intelligence, Data Structures and Algorithms, Human-Computer Interaction, Qualitative & Model-based Reasoning, and Object-oriented programming. He brings a wealth of knowledge and practical insight to his educational role, fostering a deep understanding of complex computational concepts among his students.

πŸ”¬ Research Interests:

Dr. Kittichai Lavangnananda, Ph.D., is an Associate Professor at King Mongkut’s University of Technology Thonburi (KMUTT), where he serves as Associate Dean of Research, International Relations, and Academic Quality Assurance, and Head of the Software Technology Division. His research interests encompass Computational Intelligence, Data Science, Evolutionary Computation, Machine Learning, Deep Learning, Meta-heuristics, and Multi-Objective Optimization. With a strong background in Artificial Intelligence and extensive experience in academia and technology development, Dr. Lavangnananda contributes significantly to advancing knowledge in these fields through research, teaching, and collaborative projects both nationally and internationally.

Publication Top Notes:

  • Title: Scheduling Deep Learning Training in GPU Cluster Using the Model-Similarity-Based Policy
    • Publication Year: 2023
  • Title: Implementation of Predictive Model for Diarrhea among Afghanistan Children Based on Medical and Non-Medical Attributes
    • Publication Year: 2022
  • Title: Implementing Predictive Model for Child Mortality in Afghanistan
    • Publication Year: 2022
    • Citations: 2
  • Title: Optimization of Carsharing Fleet Placement in Round-Trip Carsharing Service
    • Publication Year: 2021
    • Citations: 7
  • Title: Application of Machine Learning in Assignment of Child Delivery Service in Afghanistan
    • Publication Year: 2021
    • Citations: 3

 

 

Mr. Yan hui Wu | Machine Learning Awards | Best Researcher Award

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Mr. Yan hui Wu | Machine Learning Awards | Best Researcher Award

Mr. Yan hui Wu , Hebei University of Engineering , China

Yanhui Wu is a Senior Engineer at the School of Mining and Surveying Engineering, Hebei University of Engineering. He completed his Ph.D. in Geophysical Exploration and Information Technology at the China University of Mining and Technology (Beijing) in 2023. He also holds an M.Sc. in the same field from the China University of Geosciences (Beijing) and a B.Sc. in Computer Science and Technology from Hebei University of Technology. Wu’s career includes nearly a decade at the Geological Geophysical Center, Hebei Coal Science Research Institute, Jizhong Energy Group, where he served as a Senior Engineer. He has participated in significant research projects, including the Ministry of Science and Technology’s National Key R&D Program on dynamic intelligent detection technology for hidden disaster geological factors in coal mines. Wu’s research has been published in several renowned journals, with notable works on seismic multiattribute machine learning, fault evaluation, and collapse column prediction in coal strata.

Professional Profile:

Orcid

Β πŸŽ“Education:

Yanhui Wu holds a Ph.D. in Geophysical Exploration and Information Technology from the China University of Mining and Technology (Beijing), which he completed in June 2023. He also earned an M.Sc. in the same field from the China University of Geosciences (Beijing) in June 2010. Additionally, Wu has a B.Sc. in Computer Science and Technology from Hebei University of Technology, which he obtained in June 2007.

 🏒Work Experience:

Yanhui Wu currently serves as a Senior Engineer at the School of Mining and Surveying Engineering, Hebei University of Engineering. Prior to this role, he held a Senior Engineer position at the Geological Geophysical Center of Hebei Coal Science Research Institute, part of the Jizhong Energy Group, from August 2010 to July 2019.

Publication Top Notes:

  • Application of seismic multiattribute machine learning to determine coal strata thickness
    • Published Year: 2021
    • Journal: Journal of Geophysics and Engineering
    • Cited by: 834-844
  • Quantitative Evaluation of Faults by Combined Channel Wave Seismic Transmission-Reflection Detection Method
    • Published Year: 2022
    • Journal: Minerals
    • Cited by: 1022-1032
  • Precise prediction of the collapse column based on channel wave spectral disparity characteristics and velocity tomography imaging
    • Published Year: 2022
    • Journal: Journal of Geophysics and Engineering
    • Cited by: 326-335
  • Application research of combined detection of transmission and reflection slot waves for small structuresβ€”Taking Longquan Mining Area in Shanxi as an example
    • Published Year: 2021
    • Journal: Progress in Geophysics
    • Cited by: 1325-1332

Prof. Hong bin Xia | Recommender system | Best Researcher Award

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Prof. Hong bin Xia | Recommender system | Best Researcher Award

Prof. Hong bin Xia | Jiangnan University | China

Prof. Hongbin Xia, a distinguished professor at Jiangnan University πŸŽ“, excels in natural language processing, personalized recommendation systems, network optimization, and digital media technology, including digital twins and 3D virtual simulation. He teaches Software Engineering and Human-Computer Interaction Technology πŸ“š. Dr. Xia has authored over 40 academic papers in prestigious journals and conferences πŸ“ and led numerous national and enterprise research projects, securing significant funding. His accolades include multiple Science and Technology Awards πŸ† and notable teaching honors. As a mentor, he has guided students to remarkable successes in competitions and received several Excellent Instructor awards πŸ‘¨β€πŸ«. Prof. Xia actively participates in professional committees and provides technical consultancy, further showcasing his expertise and commitment to advancing his field πŸ“ˆ.

🌐 Professional Profile:

Scopus

🏫 Academic Position

Professor, Jiangnan University
Dr. Hongbin Xia holds a prominent position as a professor at Jiangnan University, where he imparts knowledge and fosters innovation in the fields of natural language processing, personalized recommendation systems, network optimization, and digital media technology, including digital twins and 3D virtual simulation.

πŸ“š Courses Taught

  • Software Engineering
  • Human-Computer Interaction Technology

πŸ“ Research Contributions

Dr. Xia has an impressive portfolio of over 40 academic papers published in esteemed journals and conferences such as “Complex & Intelligent Systems,” “Systems Engineering and Electronic Technology,” “Pattern Recognition and Artificial Intelligence,” and the “Journal of Chinese Information Technology.” His work includes more than 10 SCI/EI indexed publications.

πŸ”¬ Research and Projects

  • National Key R&D Projects: Presided over sub-projects and participated in the 2030 national science and technology major project, achieving significant results.
  • Enterprise Projects: Led over 30 projects, receiving more than 8 million yuan and utilizing over 5.5 million yuan for personal research.

πŸ† Awards and Honors

  • Science and Technology Awards: Special Award and First Prize of Science and Technology from the China Federation of Commerce, Ministry of Education’s Science and Technology Achievement Award, and the Science and Technology Innovation Award from the China Light Industry Federation.
  • Teaching Awards: Jiangsu Provincial Teaching Achievement Award (Second Prize, 2018), Best Teaching Award of Jiangnan University, Huawei Teaching Award (2022), and “Teacher of Pillars” by the Ministry of Education-Huawei Intelligent Base.

πŸ‘¨β€πŸ« Student Mentorship

Dr. Xia has guided students to remarkable achievements, including:

  • Bronze Medal at the ACM International Collegiate Programming Competition (ICPC)
  • First and Second Prizes in the national finals of digital media science and technology works
  • Excellent Instructor awards

πŸ“ˆ Professional Activities

  • Committee Memberships: Member of the Jiangsu Provincial Network and Distributed Computing Special Committee and the Jiangsu Provincial Characteristic Software Talent Training Special Committee.
  • Technical Consultancy: Provided expertise to the Wuxi Municipal Health Commission (2009-2020), Hengli Co., Ltd. (2016-2018), and Jiangsu Hualywood Investment Co., Ltd. (2021-present).
  • Journal Reviewer and Expert Evaluator: Reviewer for journals like “Complex & Intelligent Systems” and “Pattern Recognition and Artificial Intelligence,” and an expert in the fifth round of discipline evaluation (computer science and technology) by the Ministry of Education.

Publication Top Notes:

  • CMC-MMR: multi-modal recommendation model with cross-modal correction
    • Year: 2024
    • Journal: Journal of Intelligent Information Systems
  • Social Recommendation Model Based on Self-Supervised Graph Masked Neural NetworksΒ 
    • Year: 2023
    • Journal: Moshi Shibie yu Rengong Zhineng/Pattern Recognition and Artificial Intelligence
  • Unexpected interest recommender system with graph neural network
    • Year: 2023
    • Journal: Complex and Intelligent Systems
  • Multi-feature Fusion Based Short Session Recommendation Model | ε€šη‰ΉεΎθžεˆηŸ­δΌšθ―ζŽ¨θζ¨‘εž‹
    • Year: 2023
    • Journal: Moshi Shibie yu Rengong Zhineng/Pattern Recognition and Artificial Intelligence
  • Local and Global Feature Fusion Network Model for Aspect-Based Sentiment Analysis
    • Year: 2023
    • Journal: Journal of Frontiers of Computer Science and Technology