Vaishnavee Rathod | Analysis | Best Researcher Award

Published on by Young Scientists Awards

Ms. Vaishnavee Rathod | Analysis | Best Researcher Award

Research Scholar, Department of Computer Science Engineering SVNIT SURAT INDIA India

Vaishnavee Vijay Rathod is a Ph.D. candidate at SVNIT Surat, focusing on remote sensing and deep learning. She has earned her B.E., M.Tech., and is currently pursuing her Ph.D., with a specialized focus on satellite imaging, machine learning, and image processing. Vaishnavee has published multiple papers in renowned journals and conferences, contributing significantly to the fields of medical image analysis, remote sensing, and AI-based systems. She has also received recognition for her work, including the Best Paper Award at an international conference in 2020. Her innovative research on vehicle detection using computer vision and AI has gained attention in smart city development.

 

Publication Profile

Scopus Scholar

🎓 Education

Vaishnavee completed her B.E. in Electronics and Telecommunication in 2018 from Thakur College of Engineering and her M.Tech. in Electronics and Digital Image Processing from GHRIET Nagpur in 2020. She is currently pursuing a Ph.D. in Satellite Imaging and Deep Learning at SVNIT Surat, specializing in deep learning-driven satellite image classification. Throughout her academic journey, she has achieved distinction and published several research papers in prominent conferences and journals.

💼 Experience

Vaishnavee has significant experience as a research scholar in deep learning and image processing. Her Ph.D. research includes the development of models for satellite image analysis and AI-based vehicle detection systems using UAV data. She has contributed to over 10 publications, including SCI-indexed journals and prestigious conferences. Additionally, Vaishnavee has been a recipient of several project funding awards, including SSIP 2.0 funding for her “RoadMitra” AI-based system project, showcasing her expertise in smart city technologies.

🏆 Awards & Honors

Vaishnavee has been recognized for her research contributions, including the “Best Paper Award” at the International Conference on Engineering Systems Design and Optimization in 2020. She has received various honors, including funding under SSIP 2.0 for her smart city project “RoadMitra,” aimed at detecting road issues using UAVs. Additionally, she has won awards for her research excellence and has received numerous accolades for her participation in international conferences and workshops.

🔬 Research Focus

Vaishnavee’s research focuses on the intersection of satellite imaging, remote sensing, and deep learning. She works on developing deep learning models for efficient satellite image classification and vehicle detection systems using UAV technology. Her work also extends to image enhancement, biomedical image processing, and AI applications in smart city infrastructure. Vaishnavee’s research contributes to the development of innovative solutions for urban challenges, including road crack detection, traffic analysis, and the enhancement of healthcare technologies using AI.

Publication Top Notes

  • Title: Deep learning-driven UAV vision for automated road crack detection and classification
    • Authors: Rathod, V.V., Rana, D.P., Mehta, R.G.
    • Journal: Nondestructive Testing and Evaluation (2024)
    • Citations: 0
    • Status: Article in Press

 

  • Title: Road Crack Detection and Classification Using UAV and Deep Transfer Learning Optimization
    • Authors: Rathod, V., Rana, D., Mehta, R.
    • Journal: Journal of the Indian Society of Remote Sensing (2024)
    • Citations: 0
    • Status: Article in Press

 

  • Title: A computer vision approach to vehicle detection, classification, and tracking from UAV data for Indian traffic analysis
    • Authors: Rathod, V.V., Rana, D.P., Mehta, R.G., Nath, V.
    • Journal: IETE Journal of Research (2024)
    • Citations: 0
    • Status: Article in Press

 

  • Title: An Extensive Review of Deep Learning Driven Remote Sensing Image Classification Models
    • Authors: Rathod, V.V., Rana, D.P., Mehta, R.G.
    • Conference: Proceedings of the 2022 3rd International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT 2022)
    • Citations: 4

 

Ming Xu | Spatio-Temporal Data Mining | Best Researcher Award

Published on by Young Scientists Awards

Assoc Prof Dr. Ming Xu | Spatio-Temporal Data Mining |Best Researcher Award

👨‍🏫Profile Summary

Ming Xu is an accomplished Associate Professor at Liaoning Technical University, specializing in computer science, particularly in transportation systems. With a Ph.D. from Beijing University of Posts and Telecommunications and a wealth of academic and research experience, Dr. Xu has made significant contributions to the field. He has authored numerous publications in prestigious journals and has been recognized with awards such as the World Artificial Intelligence Conference Youth Outstanding Paper Award. Dr. Xu’s expertise lies in learning to rank nodes in road networks, anomaly detection, traffic signal control, and traffic flow prediction using advanced data mining and deep learning techniques

🌐 Professional Profiles

 

  1. Orcid  Profile

📚Education 

PhD in Computer Science Beijing University of Posts and Telecommunications Duration: September 2010 – July 2015.  Master in Computer Science Shenyang Ligong University Duration: September 2005 – April 2008. Bachelor in Computer Science Liaoning Technical University Duration: September 1999 – 2003

👨‍💼Professional Service

  • Guest editor of special issue of Journal of Advanced Transportation (SCI)
  • Reviewer of IEEE Trans. on ITS\Physica A\ITSC

🏆 Awards

  • World Artificial Intelligence Conference Youth Outstanding Paper Award (2020)

🎓Academic experience

Associate Professor Software College, Liaoning Technical University Duration: October 2020 – Present. Postdoctoral position Tsinghua University Duration: February 2016 – February 2019

 

📚Top Noted Publication

    1. Title: MGL2Rank: Learning to Rank the Importance of Nodes in Road Networks Based on Multi-Graph Fusion
      • Authors: Ming Xu, Jing Zhang
      • Journal: Information Sciences
      • Status: In press
      • DOI: 10.1016/j.ins.2024.120472

     

    1. Title: Discovery of Critical Nodes in Road Networks through Mining from Vehicle Trajectories
      • Authors: Ming Xu, Jianping Wu, Mengqi Liu, Yunpeng Xiao, Haohan Wang, Dongmei Hu
      • Journal: IEEE Transactions on Intelligent Transportation Systems
      • Year: 2018
      • Volume: 20
      • Issue: 2
      • Pages: 583-593
      • Award: World Artificial Intelligence Conference Youth Outstanding Paper Award
      • Links: Award, Report

     

    1. Title: Anomaly Detection in Road Networks using Sliding-Window Tensor Factorization
      • Authors: Ming Xu, Jianping Wu, Haohan Wang, Mengxin Cao
      • Journal: IEEE Transactions on Intelligent Transportation Systems
      • Year: 2019
      • Volume: 20
      • Issue: 12
      • Pages: 4704-4713

     

    1. Title: Network-wide Traffic Signal Control based on Discovery of Critical Nodes and Deep Reinforcement Learning
      • Authors: Ming Xu, Jianping Wu, Ling Huang, Rui Zhou, Tian Wang, Dongmei Hu
      • Journal: Journal of Intelligent Transportation Systems
      • Year: 2020
      • Volume: 24
      • Issue: 1
      • Pages: 1-10

     

    1. Title: Traffic Flow Prediction with Rainfall Impact Using A Deep Learning Method
      • Authors: Yuhan Jia, Jianping Wu, Ming Xu
      • Journal: Journal of Advanced Transportation
      • Year: 2017

     

    1. Title: Charging Pile Siting Recommendations via the Fusion of Points of Interest and Vehicle Trajectories
      • Authors: Yuan Kong, Jianping Wu, Ming Xu, Kezhen Hu
      • Journal: China Communications
      • Year: 2017
      • Volume: 14
      • Issue: 11
      • Pages: 29-38

     

    1. Title: Rumor propagation dynamic model based on evolutionary game and anti-rumor
      • Authors: Yunpeng Xiao, Diqiang Chen, Shihong Wei, Qian Li, Haohan Wang, Ming Xu
      • Journal: Nonlinear Dynamics
      • Year: 2019
      • Volume: 95
      • Pages: 523-539

     

    1. Title: Leveraging longitudinal driving behaviour data with data mining techniques for driving style analysis
      • Authors: Geqi Qi, Yiman Du, Jianping Wu, Ming Xu
      • Journal: IET intelligent transport systems
      • Year: 2015
      • Volume: 9
      • Issue: 8
      • Pages: 792-801

     

    1. Title: Emission pattern mining based on taxi trajectory data in Beijing
      • Authors: Tingting Li, Jianping Wu, Anrong Dang, Lyuchao Liao, Ming Xu
      • Journal: Journal of cleaner production
      • Year: 2019
      • Volume: 206
      • Pages: 688-700

     

    1. Title: 3-HBP: A three-level hidden Bayesian link prediction model in social networks
      • Authors: Yunpeng Xiao, Xixi Li, Haohan Wang, Ming Xu, Yanbing Liu
      • Journal: IEEE Transactions on Computational Social Systems
      • Year: 2018
      • Volume: 5
      • Issue: 2
      • Pages: 430-443