Jing An | Artificial Intelligence | Best Researcher Award

Dr. Jing An | Artificial Intelligence | Best Researcher Award

Yancheng Institute of Technology, China

๐Ÿ‘จโ€๐ŸŽ“Professional Profile

Scopus Profile

๐Ÿ‘จโ€๐Ÿซ Summary

Dr. Jing An is a distinguished professor and master tutor at Yancheng Institute of Technology, China. He specializes in intelligent manufacturing engineering, industrial big data fault diagnosis, and residual life prediction. With numerous patents and software copyrights, Dr. An has published over 20 SCI/EI indexed papers and contributed to key academic texts. His pioneering research in artificial intelligence-based fault diagnosis has earned him prestigious awards, including first-place recognition in the China Commerce Federation Science and Technology Award .

๐ŸŽ“ Education

Dr. An holds a Ph.D. in Computer Science from Hohai University (2021) and a Masterโ€™s degree in Computer Science from Harbin University of Science and Technology (2006). His academic foundation has strongly influenced his research in AI and fault diagnosis.

๐Ÿ’ผ Professional Experience

Having joined Yancheng Institute of Technology in 2006, Dr. An is also the Vice President of Science and Technology for Jiangsu Province’s “Double Innovation Plan.” He has led numerous provincial-level projects, and his expertise has extended to more than 10 industry partnerships ๐Ÿš€.

๐Ÿ“š Academic Citations

Dr. An has authored over 20 peer-reviewed papers in prestigious journals such as IEEE Access and Mathematical Problems in Engineering. His impactful research on AI-based fault diagnosis methods is frequently cited within the academic community .

๐Ÿ”ง Technical Skills

Dr. An is skilled in AI-based fault diagnosis, deep learning, machine learning, and industrial big data analytics. He has expertise in Convolutional Neural Networks (CNNs) and intelligent manufacturing systems, focusing on improving machinery reliability and efficiency .

๐Ÿง‘โ€๐Ÿซ Teaching Experience

Dr. An has been recognized as an outstanding teacher twice at Yancheng Institute of Technology. He teaches courses in intelligent manufacturing engineering and industrial big data fault diagnosis, preparing students to advance in the field of AI and data science .

๐Ÿ” Research Interests

Dr. Anโ€™s research is focused on developing intelligent systems for fault diagnosis in rotating machinery, predictive maintenance, and the application of deep learning techniques in industrial big data. His work aims to enhance manufacturing processes and equipment reliability .

๐Ÿ“–Top Noted Publications

Hybrid Mechanism and Data-Driven Approach for Predicting Fatigue Life of MEMS Devices by Physics-Informed Neural Networks

Authors: Cheng, J., Lu, J., Liu, B., An, J., Shen, A.

Journal: Fatigue and Fracture of Engineering Materials and Structures

Year: 2024

Bearing Intelligent Fault Diagnosis Based on Convolutional Neural Networks

Authors: An, J., An, P.

Journal: International Journal of Circuits, Systems and Signal Processing

Year: 2022

Deep Clustering Bearing Fault Diagnosis Method Based on Local Manifold Learning of an Autoencoded Embedding

Authors: An, J., Ai, P., Liu, C., Xu, S., Liu, D.

Journal: IEEE Access

Year: 2021

Deep Domain Adaptation Model for Bearing Fault Diagnosis with Riemann Metric Correlation Alignment

Authors: An, J., Ai, P.

Journal: Mathematical Problems in Engineering

Year: 2020

Deep Domain Adaptation Model for Bearing Fault Diagnosis with Domain Alignment and Discriminative Feature Learning

Authors: An, J., Ai, P., Liu, D.

Journal: Shock and Vibration

Year: 2020

Haixia Mao | Data Science | Best Researcher Award

Dr. Haixia Mao | Data Science | Best Researcher Award

Shenzhen Polytechnic University, China

๐Ÿ‘จโ€๐ŸŽ“Professional Profile

Scopus Profile

๐Ÿ‘ฉโ€๐Ÿซ Summary

Dr. Haixia Mao is an Associate Professor at the School of Automobile and Transportation at Shenzhen Polytechnic University, China. She holds a Ph.D. in Geographic Information System (GIS) and Remote Sensing from the Hong Kong Polytechnic University. Her research focuses on GIS-T, big data analytics, and analyzing urban mobility patterns, using spatial-temporal data from transportation systems to improve urban planning and human behavior modeling.

๐ŸŽ“ Education

Dr. Mao earned her Ph.D. in GIS and Remote Sensing from the Hong Kong Polytechnic University in 2010. She also completed her M.S. in GIS at Wuhan University in 2004 and her B.S. in Photogrammetry and Remote Sensing from Wuhan University.

๐Ÿ’ผ Professional Experience

Dr. Mao currently serves as an Associate Professor at Shenzhen Polytechnic University (since 2012), where she has contributed to the development of transportation-related GIS courses. Previously, she worked as a Postdoctoral Researcher at the Hong Kong Polytechnic University from 2014 to 2016, furthering her expertise in urban computing and GIS.

๐Ÿ“š Research Interests

Her research encompasses GIS-T (Geographic Information Systems for Transportation), big data analytics, remote sensing, deep learning, and urban planning. She investigates the mobility patterns of citizens through traffic data (including taxis, buses, and metro) and leverages spatial-temporal data to enhance urban infrastructure and predict human behavior.

๐Ÿ… Academic Contributions

Dr. Mao has authored over 20 peer-reviewed journal articles and conference papers. She has also been awarded a patent for a caching system with a new cache placement method. She has received research grants for spatial-temporal data analytics in transportation and has actively contributed to major projects in urban computing.

๐Ÿ’ป Technical Skills

Dr. Maoโ€™s technical expertise spans GIS, remote sensing, big data analytics, deep learning, and spatial-temporal data analysis. She integrates these advanced techniques to solve complex transportation and urban planning challenges.

๐Ÿ“š Teaching Experience

Dr. Mao has taught several courses since 2012 at Shenzhen Polytechnic University, including GIS for Transportation, Traffic Engineering Cartography, and Traffic Information Processing. She has a long-standing dedication to educating future professionals in the field of urban planning and transportation technology.

 

๐Ÿ“–Top Noted Publications

Multiple sclerosis lesions segmentation based on 3D voxel enhancement and 3D alpha matting

Authors: Sun, Y., Zhang, Y., Wang, X., Zeng, Z., Mao, H.
Journal: Chinese Journal of Medical Physics
Year: 2022

Customer attractiveness evaluation and classification of urban commercial centers by crowd intelligence

Authors: Mao, H., Fan, X., Guan, J., Wang, Y., Xu, C.
Journal: Computers in Human Behavior
Year: 2019

ย When Taxi Meets Bus: Night bus stop planning over large-scale traffic data

Authors: Xiao, L., Fan, X., Mao, H., Lu, P., Luo, S.
Conference: Proceedings – 2016 7th International Conference on Cloud Computing and Big Data, CCBD 2016
Year: 2017

Characterizing On-Bus WiFi passenger behaviors by approximate search and cluster analysis

Authors: Jiang, M., Fan, X., Zhang, F., Mao, H., Liu, R.
Conference: Proceedings – 2016 7th International Conference on Cloud Computing and Big Data, CCBD 2016
Year: 2017

Efficient visibility analysis for massive observers

Authors: Wang, W., Tang, B., Fan, X., Yang, H., Zhu, M.
Conference: Procedia Computer Science
Year: 2017

Web access patterns enhancing data access performance of cooperative caching in IMANETs

Authors: Fan, X., Cao, J., Mao, H., Zhao, Y., Xu, C.
Conference: Proceedings – IEEE International Conference on Mobile Data Management
Year: 2016

Shubing Dai | Algorithm Development | Best Researcher Award

Prof. Shubing Dai | Algorithm Development | Best Researcher Award

Prof. Shubing Dai at Northwest A&F University, China

Professional Profile๐Ÿ‘จโ€๐ŸŽ“

๐Ÿ‘จโ€๐Ÿซ Summary

Prof. Shubing Dai is an Associate Professor at Northwest A&F University, specializing in Hydraulic Engineering. With a background in Hydraulics and River Dynamics, he has published over 20 research papers and actively participated in over 20 research projects. His work primarily focuses on urban flood management, hydraulic structures, and water flow dynamics. He is also an active member of key professional organizations, including the China Society for Hydroelectric Engineering and the International Association for Hydro-Environment Engineering and Research (IAHR).

๐ŸŽ“ Education

Prof. Dai began his academic career at Northwest A&F University, where he earned his Bachelor’s (2008โ€“2012) and Master’s (2012โ€“2015) degrees in Hydraulic and Hydroelectric Engineering. He then pursued a Ph.D. in Hydraulics and River Dynamics at Dalian University of Technology (2016โ€“2021). Additionally, he worked as a visiting scholar at the University of La Coruรฑa in Spain (2024).

๐Ÿ’ผ Professional Experience

Prof. Dai has extensive professional experience, both in academia and industry. He currently serves as an Associate Professor at Northwest A&F University and the Department Secretary of the Hydraulic Engineering Department. He also previously worked as an Assistant Engineer at the Changjiang Survey, Planning, and Design Institute (2015โ€“2016), contributing to several major hydropower and hydraulic engineering projects.

๐Ÿ“š Academic Contributions

Prof. Dai is an active contributor to the academic community, serving as a reviewer for several leading journals such as Journal of Hydrology and Physics of Fluids. He also serves as an editorial board member for an international journal. His research focuses on water resources, hydraulic structures, and flow dynamics, with over 20 published papers and several high-impact research projects.

๐Ÿ”ง Technical Skills

Prof. Dai has developed a range of technical skills, including:

  • Hydraulic Engineering: Focus on energy dissipation and optimization of flood discharge systems.
  • Urban Flooding & Drainage: Expertise in urban drainage system design, stormwater management, and flood mitigation.
  • Flow Dynamics: Proficient in Computational Fluid Dynamics (CFD) and non-steady flow simulations for hydraulic applications.
  • Hydropower Engineering: In-depth research on dam-break flood modeling, hydraulic structures, and their interactions with water flow.

๐Ÿ‘ฉโ€๐Ÿซ Teaching Experience

As a dedicated educator, Prof. Dai mentors master’s students and teaches courses on fluid dynamics, hydraulic modeling, and water resource management. He is also responsible for the administration of the Water Resources and Hydroelectric Engineering department at Northwest A&F University, playing a key role in curriculum development and academic planning.

๐Ÿ”ฌ Research Interests

Prof. Daiโ€™s research interests are focused on:

  • Hydraulic Engineering: Research on energy dissipation in hydraulic structures and optimization of flood discharge processes.
  • Flood Disaster Management: Urban flood management, drainage systems, and dam-break flood evolution.
  • Non-steady Flow & Hydrodynamics: Investigating the dynamics of free-surface flows, wave behavior, and non-constant flow conditions in hydraulic systems.

๐Ÿ” Research Projects

Prof. Dai leads and participates in several important research projects, such as:

  • City Flood and Drainage Systems Simulation (2022โ€“2025)
  • Optimization of Urban Drainage Under Extreme Rainfall Conditions (2023โ€“2025)
  • Dam-Break Flood Evolution and Structural Interaction Studies (2024โ€“2026)
    He is also involved in national and regional projects on hydraulic structure optimization, flood forecasting, and water resource management.

 

๐Ÿ“–Top Noted Publications

Numerical study of roll wave development for non-uniform initial conditions using steep slope shallow water equations

Authors: Dai, S., Liu, X., Zhang, K., Liu, H., Jin, S.
Journal: Physics of Fluids
Year: 2024

Discharge coefficients formulae of grate inlets of complicated conditions for urban floods simulation and urban drainage systems design

Authors: Dai, S., Hou, J., Jin, S., Hou, J., Liu, G.
Journal: Journal of Hydrology
Year: 2023

Land Degradation Caused by Construction Activity: Investigation, Cause and Control Measures

Authors: Dai, S., Ma, Y., Zhang, K.
Journal: International Journal of Environmental Research and Public Health
Year: 2022

Numerical investigations of unsteady critical flow conditions over an obstacle using three models

Authors: Dai, S., Jin, S.
Journal: Physics of Fluids
Year: 2022

Interception efficiency of grate inlets for sustainable urban drainage systems design under different road slopes and approaching discharges

Authors: Dai, S., Jin, S., Qian, C., Ma, Y., Liang, C.
Journal: Urban Water Journal
Year: 2021

Razia Sulthana Abdul Kareem – building customised new deep learning algorithms – Best Researcher Awardย 

Dr Razia Sulthana Abdul Kareem - building customised new deep learning algorithms - Best Researcher Awardย 

University of Greenwich - United Kingdomย 

Author Profile

Early Academic Pursuits

Dr. Razia Sulthana Abdul Kareem embarked on her academic journey with a Bachelor of Technology in Information Technology, where she showcased exemplary prowess by earning the title of GOLD MEDALIST. She further fortified her academic credentials with a Master of Engineering in Computer Science and Engineering, once again securing the prestigious GOLD MEDALIST accolade. Her pursuit of knowledge didn't stop there; she pursued an MBA in Systems, underscoring her interdisciplinary approach to technology. Driven by a passion for research, she culminated her academic endeavors with a Doctorate in Computer Science and Engineering.

Professional Endeavors

Dr. Razia's professional trajectory spans over 11 years, primarily devoted to imparting knowledge as a Senior Lecturer in Computer Science. She has a knack for delivering interdisciplinary courses tailored for undergraduate and postgraduate students. Her academic stints extend across geographies, including India, Dubai, and the UK, reflecting her global academic footprint.

Contributions and Research Focus

Specializing in Machine Learning and Deep Learning algorithms, Dr. Razia's research endeavors resonate with contemporary challenges. She has ardently delved into the realms of Computational Intelligence, Artificial Intelligence, and Neural Computing. A significant pivot in her research journey involves aligning her work with the United Nations' Sustainable Development Goals, particularly targeting poverty alleviation through agricultural innovation. Collaborative projects with the Natural Resources Institute at the University of Greenwich underscore her commitment to real-world impact, focusing on agricultural challenges like weed identification and fungal infection detection.

Accolades and Recognition

Dr. Razia's academic and research prowess has garnered her several accolades, including the "Best Teacher Award" for pivotal courses like Data Structure and Algorithms, Machine Learning, and Data Analytics. Her initiative in launching the Machine Learning course at Birla Institute of Technology, Dubai, stands testament to her pedagogical innovations, earning her the "Best Faculty Award." Additionally, she has been recognized as the "Best Student Counselor" in both India and Dubai, emphasizing her holistic contribution to academia.

Impact and Influence

With an H-index of 7 and a cumulative impact factor of approximately 24 over the last three years, Dr. Razia's scholarly contributions resonate globally. Her research publications in renowned indices like SCI, SCIE, Scopus, and Web of Science underscore her scholarly impact. Furthermore, her collaborations, totaling 10 joint publications and projects, reflect her expansive academic network and influence.

Legacy and Future Contributions

Dr. Razia Sulthana Abdul Kareem's legacy is characterized by a relentless pursuit of academic excellence, interdisciplinary research, and impactful contributions to society. Her future endeavors are poised to expand upon her existing research frameworks, leveraging AI and machine learning to address pressing environmental and societal challenges. As she continues to mentor the next generation of scholars and innovators, her legacy will undoubtedly transcend academic boundaries, leaving an indelible mark on the realms of Computer Science and Artificial Intelligence.

Notable Publicationย 

Pushpa-Medical Image Processing, Biomedical Engineering-Best Researcher Award

Author Profile

Google Scholar

Early Academic Pursuits

Mrs. Pushpa B embarked on her academic journey with a Bachelor's in Electronics and Instrumentation from St. Peterโ€™s Engineering College, affiliated with Anna University, in 2007. Her dedication to the field was evident as she secured a commendable 73%. Building upon this foundation, she pursued an M.Tech in Electronics and Control from SRM University, Chennai, where she achieved a CGPA of 6.99 in 2010. The continuous academic excellence led her to undertake an MBA in Health Service Management from Anna University in 2023. Currently, she is on the verge of completing her Ph.D. in Medical Image Processing & Artificial Intelligence from Annamalai University, with her thesis submitted.

Professional Endeavors

With an illustrious academic background, Mrs. Pushpa B transitioned into academia, where she has made significant contributions. She held the position of Assistant Professor in various esteemed institutions such as B.S. Abdur Rahman Crescent Institute of Science and Technology and Velammal Institute of Technology. During her tenure, she shouldered numerous responsibilities, including curriculum development, university department audit coordination, and acting as a placement coordinator.

Contributions and Research Focus

Mrs. Pushpa B's expertise spans across diverse fields, including Analog Electronic Circuits, Digital Signal Processing, Machine Learning, and more. Her research primarily revolves around Medical Image Processing, Artificial Intelligence, and Bio-medical Instrumentation. Notably, she has undertaken projects like "Detection of Startle Type Epilepsy using Machine Learning Technique" at Global Medical Hospital, Chennai. Her research is widely recognized, with numerous international and national publications and conference presentations to her credit.

Accolades and Recognition

Mrs. Pushpa B's contributions to the academic and research communities have garnered her several accolades. She has published patents, notably one on "Intelligent estimation of liver fat and its stages by using DICOM." Furthermore, her publications in renowned journals like Technology and Health Care and Measurement Sensors, among others, testify to her expertise and recognition in her field.

Impact and Influence

Mrs. Pushpa B's influence extends beyond her academic and research endeavors. She has organized workshops, training programs, and conferences that have facilitated knowledge dissemination and skill enhancement for students, faculty, and industry professionals alike. Her expertise as a reviewer for esteemed platforms like Taylor & FrancisOnline, Elsevier, and IEEE Xplore further amplifies her impact in the scholarly community.

Legacy and Future Contributions

As a dedicated academician and researcher, Mrs. Pushpa B's legacy is marked by her commitment to advancing knowledge in her specialized domains. Her future contributions are anticipated to further bridge the gap between technology and healthcare, particularly in leveraging AI and machine learning techniques for enhanced medical diagnostics and treatments. With her relentless pursuit of excellence, she is poised to inspire future generations of researchers and academicians in the realms of Medical Image Processing and Artificial Intelligence.

In conclusion, Mrs. Pushpa B's academic pursuits, professional endeavors, and contributions to the field of Medical Image Processing and Artificial Intelligence stand as a testament to her passion, expertise, and commitment. Her multifaceted accomplishments underscore her potential to drive significant advancements and make lasting contributions to academia and healthcare.

NOTABLE PUBLICATION