ABDULLAH INCEKARA | Geomatics Engineering | Best Researcher Award

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Assist. Prof. Dr. ABDULLAH INCEKARA | Geomatics Engineering | Best Researcher Award

Assistant Professor, TOKAT GAZIOSMANPASA UNIVERSITY

Abdullah Harun Incekara is an Assistant Professor at Tokat Gaziosmanpasa University in the Department of Geomatics Engineering. He holds a Ph.D. in Geomatics Engineering from Istanbul Technical University, where his research focused on improving the quality of historical aerial photographs. His expertise spans lidar-based mapping, remote sensing, photogrammetry, and UAV technology. Abdullah has published extensively in international journals and conferences, contributing to advancements in geospatial technologies. His work bridges the gap between theoretical research and practical applications in geomatics, particularly in the areas of shoreline extraction and the enhancement of spatial quality using super-resolution techniques.

Profile

Scholar

Orcid

🎓 Education

Ph.D. in Geomatics Engineering, Istanbul Technical University (2018-2024), GPA: 3.79/4.00 M.Sc. in Geomatics Engineering, Istanbul Technical University (2016-2018), GPA: 3.75/4.00 B.Sc. in Geomatics Engineering, Istanbul Technical University (2011-2016), GPA: 3.26/4.00 Abdullah completed his Ph.D. and M.Sc. studies at Istanbul Technical University, focusing on innovative applications in geomatics, with particular interest in the enhancement of aerial photographs and shoreline mapping through advanced computational techniques. His solid academic background underpins his research contributions to geospatial data analysis and engineering.

💼 Experience

Assistant Professor, Department of Geomatics Engineering, Tokat Gaziosmanpasa University (2024–present) Research Assistant, Department of Geomatics Engineering, Tokat Gaziosmanpasa University (2017–2024) Abdullah Harun Incekara has an extensive academic career, progressing from a Research Assistant to Assistant Professor at Tokat Gaziosmanpasa University. His professional focus has been on geomatics, incorporating geospatial technologies like UAVs and lidar in applied and research projects. His contributions to the department include mentoring students and advancing the study of spatial data quality, including enhancing historical imaging techniques.

🏆 Awards & Honors

Best Paper Award, International Conference on Remote Sensing (2017) Outstanding Research Award, Tokat Gaziosmanpasa University (2021) Early Career Excellence Award, Istanbul Technical University (2019) Abdullah has received multiple recognitions for his academic excellence and research contributions. Notably, his innovative work in geomatics has earned him several accolades, including awards for outstanding research and best paper presentations in international conferences, reinforcing his status in the field.

🔬 Research Focus

Abdullah’s research primarily focuses on geomatics engineering, emphasizing remote sensing, UAV-based photogrammetry, and historical aerial photograph enhancement. His Ph.D. work on super-resolution techniques for spatial data quality has led to significant findings that improve the usability of historical imagery. His publications also explore the environmental impact assessments using satellite imagery and the application of geomatics in urban planning and agriculture. His ongoing research aims to bridge gaps in geospatial technology applications, making them more efficient and accurate for real-world solutions.

Conclusion 

Abdullah Harun Incekara is a highly deserving candidate for the Best Researcher Award due to his exceptional academic background, strong research contributions, and innovative approach to Geomatics Engineering. His work in remote sensing and environmental monitoring exemplifies cutting-edge scientific exploration. With continued global collaborations and diversification in research topics, Incekara has the potential to further establish himself as a leader in the geospatial sciences field.

Publication

Title: Investigating the utility potential of low-cost unmanned aerial vehicles in the temporal monitoring of a landfill
Authors: AH Incekara, A Delen, DZ Seker, C Goksel
Year: 2019
Citations: 37

 

Title: Qualifying the LIDAR-derived intensity image as an infrared band in NDWI-based shoreline extraction
Authors: AH Incekara, DZ Seker, B Bayram
Year: 2018
Citations: 21

 

Title: Interpreting Temperature Based Discontinuity and Roughness of Rock Surfaces by Using Photogrammetric Technique
Authors: AH İncekara, DZ Şeker, CS Tezcan, E Bozkurtoglu, C Gazioğlu
Year: 2017
Citations: 12

 

Title: Comparative analyses of the point cloud produced by using close-range photogrammetry and terrestrial laser scanning for rock surface
Authors: AH Incekara, DZ Seker
Year: 2018
Citations: 11

 

Title: Rolling shutter effect on the accuracy of photogrammetric product produced by low-cost UAV
Authors: AH İncekara, DZ Seker
Year: 2021
Citations: 9

 

Title: Investigating the suitability of mirrorless cameras in terrestrial photogrammetric applications
Authors: AH Incekara, DZ Seker, A Delen, A Acar
Year: 2017
Citations: 7

 

Title: Using unmanned aerial vehicles for open mining areas: Current applications and future potentials
Authors: AH Incekara, O Yildirim, T Susam, DZ Seker
Year: 2016
Citations: 4

 

Title: Minimizing the Limitations in Improving Historical Aerial Photographs with Super-Resolution Technique
Authors: AH Incekara, U Alganci, O Arslan, DZ Seker
Year: 2024
Citations: 1

 

Title: The potential contribution of remotely sensed images for GreenMetric ranking
Authors: AH İncekara, EY Basaran, DZ Seker
Year: 2022
Citations: 1

 

Title: USING SATELLITE IMAGERIES AND ORTHOPHOTO TO QUANTIFY ENVIRONMENTAL IMPACT OF MINING ACTIVITIES IN FOREST AREA
Authors: AH Incekara, A Delen, DZ Seker, FB Sanli, T Susam
Year: 2019
Citations: 1

 

Title: Combination of UAV Based Digital Surface Model with 3D Model Of ITU Bicycle House Produced by Close-Range Photogrammetry
Authors: Y Albeni, B Sariturk, ME Atik, O Ozturk, Z Duran, DZ Seker, B Bayram, …
Year: 2018
Citations: 1

Michael | Geological Remote Sensing | Best Researcher Award

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Mr. Michael | Geological Remote Sensing | Best Researcher Award

University of Electronic Science and Technology of China,  China

Michael Appiah-Twum, a geoscientist, combines Artificial Intelligence and Machine Learning with advanced remote sensing to revolutionize natural resources and environmental management. He specializes in geospatial data analysis for geological surveys, mineral exploration, petroleum exploration, and environmental monitoring. With a solid foundation in geology, geophysics, and geochemistry, Michael integrates cutting-edge AI technologies for sustainable development. Currently pursuing a Ph.D. in Information and Communication Engineering at the University of Electronic Science and Technology of China, he excels in developing innovative AI-driven solutions for geological interpretation and resource management.

Profile

Orcid

Scholar

🎓 Education

Ph.D. in Information and Communication Engineering: University of Electronic Science and Technology of China (2020-Present); GPA: 3.52/4.0. Thesis: Deep Learning-based Multisource Geological Interpretation. M.Sc. in Information and Communication Engineering: University of Electronic Science and Technology of China (2020); GPA: 3.51/4.0. Thesis: Remote Sensing and Geological Survey of Gold Deposits. B.Sc. in Earth Science: University for Development Studies, Ghana (2014). Thesis: Atlas of Laterite and Exploration Implications.

🧑‍🏫 Experience

Researcher: Yangtze Delta Region Institute, UESTC (2022–Present) – Conducting AI/ML research for geological data analysis and mineral exploration. Course Instructor: UESTC (2023) – Designed curricula and taught Remote Sensing in Resources and Environment. Teaching Assistant: UESTC (2022–2023) – Conducted tutorials, guided projects, and mentored students in Remote Sensing. VIP Member: UESTC Green Club (2018–2020) – Advocated sustainable agriculture and environmental awareness. Electoral Official: Electoral Commission of Ghana (2015) – Managed polling operations during elections.

🏆 Awards and Honors

Top Ranked Ph.D. Student: University of Electronic Science and Technology of China (2020-Present). Graduate Student Member: IEEE Geoscience and Remote Sensing Society. Top Ranked M.Sc. Student: UESTC, Chengdu (2020). Research Excellence: Developed advanced geological interpretation models using AI/ML. Leadership Recognition: UESTC Green Club VIP for promoting sustainability and environmental stewardship.

🔬 Research Focus

Geological Surveys: Using remote sensing for mineral and petroleum exploration. AI/ML Applications: Implementing deep learning for geological and environmental data interpretation. Geospatial Analysis: Advanced modeling for resource exploration and sustainable development. Hydrology and Regolith: Focused on soil mechanics and hydrogeology for environmental management. Remote Sensing Integration: Leveraging UAVs and satellite imagery for accurate geoscientific data visualization.

Conclusion 

Michael Appiah-Twum is undoubtedly a strong contender for the Best Researcher Award, given his exceptional research in remote sensing, AI/ML applications, and resource management. His technical proficiency, leadership in academic settings, and dedication to sustainability make him a highly deserving candidate. With minor improvements in interdisciplinary collaboration and global outreach, his impact on the geoscience field could expand even further, contributing to more innovative and sustainable solutions in the industry.

📚Publications 

  1. Spatial distribution and trace element geochemistry of laterites in Kunche area: Implication for gold exploration targets in NW, Ghana
    Authors: E.D. Sunkari, M. Appiah-Twum, A. Lermi
    Journal: Journal of African Earth Sciences, 158, 103519 (2019)
    Citations: 34

 

  1. Data Centric Blockchain-Based Evaluation Approach to Analyze E-Commerce Reviews Using Machine and Deep Learning Techniques
    Authors: E.M. Acheampong, S. Zhou, Y. Liao, P. Atandoh, D. Addo, E. Antwi-Boasiako, et al.
    Conference: 2023 20th International Computer Conference on Wavelet Active Media
    Citations: 1

 

  1. Enhanced Word Embedding with CNN Using Word Order Information for Sentiment Analysis
    Authors: P. Atandoh, Z. Fengli, P.A. Hakeem, E.M. Acheampong, D. Addo, et al.
    Conference: 2023 20th International Computer Conference on Wavelet Active Media
    Citations: 1

 

  1. Assessing Landsat-9 in Identifying Lithology Using a Hybrid Metric-Learning and SVM Method Against Baseline Algorithms: A Case Study of the West African Craton
    Authors: M. Appiah-Twum, H. Jia, W. Xu
    Conference: IGARSS 2023 – IEEE International Geoscience and Remote Sensing Symposium
    Citations: 1

 

  1. Using Laterite Geochemistry for Exploration of Orogenic Gold Deposits in the Wa-Lawra Belt, NW Ghana: Kunche in Perspective
    Authors: E.D. Sunkari, M. Appiah-Twum, A. Lermi
    Journal: Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, 7(3), 1137 (2018)
    Citations: 1

 

  1. DenseViT: A Hybrid CNN-Vision Transformer Model for an Improved Multisensor Lithological Classification
    Authors: M. Appiah-Twum, W. Xu, E.M. Acheampong
    Conference: IGARSS 2024 – IEEE International Geoscience and Remote Sensing Symposium (2024)

 

  1. An Attention-Based LSTM Lithological Classification Using Multisensor Datasets
    Authors: M. Appiah-Twum, W. Xu
    Conference: IGARSS 2024 – IEEE International Geoscience and Remote Sensing Symposium (2024)

 

  1. Lithological Classification Using Densely Connected Convolution Network on Landsat-9 and Aster Datasets in a Semi-Arid Environment
    Authors: M. Appiah-Twum, X. Wenbo, C.B. Mawuli, P. Atandoh
    Conference: 2023 20th International Computer Conference on Wavelet Active Media (2023

 

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

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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