Dr. Nabil Bachagha | Remote Sensing | Best Researcher Award

Published on by Computer Scientists Awards

Dr. Nabil Bachagha | Remote Sensing | Best Researcher Award

University of Leeds | United Kingdom

Dr. Nabil Bachagha is a distinguished Research Fellow and global expert in remote sensing, GIS, and deep learning, with significant contributions to digital heritage preservation and archaeological landscape documentation. His interdisciplinary research integrates advanced geospatial technologies, including UAV photogrammetry, terrestrial 3D laser scanning, and machine learning models, to enhance the detection, classification, and conservation of archaeological and cultural heritage sites. A UK Global Talent Visa holder under the Exceptional Talent Route, Dr. Bachagha’s work bridges technology and heritage, focusing on data-driven approaches to protect endangered sites and reconstruct ancient civilizations through digital innovation. His expertise spans ENVI, ArcGIS, QGIS, and Earth Engine applications, combined with proficiency in Python, R, MATLAB, and JavaScript for geospatial analytics and automated system development. With over 430 citations from 374 documents in Scopus (h-index: 6) and 675 citations in Google Scholar (h-index: 8, i10-index: 7), Dr. Bachagha’s research demonstrates strong academic influence and global recognition. His projects, such as the “One Belt, One Road Heritage Protection” and “Endangered Wooden Architecture Programme,” exemplify his commitment to integrating AI, remote sensing, and geospatial intelligence in cultural heritage management.

Profile

Scopus | ORCID | Google Scholar

Featured Publications

Bachagha, N., Wang, X., Lasaponara, R., Luo, L., & Khatteli, H. (2020). Remote sensing and GIS techniques for reconstructing the military fort system of Roman boundary (Tunisia section) and identifying archaeological sites. Remote Sensing of Environment.

Bachagha, N., Luo, L., Wang, X., Masini, N., Tababi, M., Khatteli, H., & Lasaponara, R. (2020). Mapping the Roman water supply system of the Wadi el Melah Valley in Gafsa, Tunisia, using remote sensing. Sustainability.

Luo, L., Wang, X., Guo, H., Lasaponara, R., Zong, X., Masini, N., & Bachagha, N. (2019). Airborne and spaceborne remote sensing for archaeological and cultural heritage applications: A review of the century (1907–2017). Remote Sensing of Environment.

Bachagha, N., Xu, W., Luo, X., Brahmi, M., Wang, X., Souei, F., & Lasaponara, R. (2022). On the discovery of a Roman fortified site in Gafsa, southern Tunisia, based on high-resolution X-band satellite radar data. Remote Sensing.

Bachagha, N., Tababi, M., Selim, G., Shao, W., Xue, Y., Li, W., Bennour, A., Luo, L., Lasaponara, R., & Lao, Y. (2025). Facilitating archaeological discoveries through deep learning and space-based observations: A case study in southern Tunisia. Nature Communications.

Lingling Li | Remote sensing | Best Researcher Award

Published on by Computer Scientists Awards

Dr. Lingling Li | Remote sensing | Best Researcher Award 

Associate professor, Xidian University, China

🎓 Dr. Lingling Li is an Associate Professor at the School of Artificial Intelligence, Xidian University, China. She specializes in deep learning, sparse representation, quantum evolutionary optimization learning theory, and complex image interpretation. She has founded her own research group focusing on the interpretation and understanding of remote sensing images and has supervised numerous master’s and Ph.D. students. Dr. Li has secured prestigious national-level grants, exceeding 1,000,000 RMB, to support her innovative research projects. 🌟

Publication Profile

ORCID

Strengths for the Award:

  1. Significant Research Contributions: Lingling Li has a strong record of impactful research in the fields of deep learning, image processing, and remote sensing. Her publications in prestigious journals, such as IEEE TIP and Neurocomputing, reflect her deep expertise in advanced topics like deep contourlet networks, human-object interaction detection, and quantum evolutionary learning.
  2. Leadership in Research: As the founder of her own research group on interpretation and understanding of remote sensing images at Xidian University, she has successfully supervised numerous students (16 masters, 6 Ph.D.). This shows her ability to mentor the next generation of researchers, which is a key indicator of her leadership in academia.
  3. Awarded Prestigious Grants: She has received multiple prestigious national and institutional research grants totaling over 1,000,000 RMB, which demonstrates her ability to attract funding and lead high-impact research projects, such as the National Natural Science Foundation and National Key Laboratory of Science and Technology for National Defense.
  4. Global Academic Exposure: Her experience as a visiting scholar at the University of the Basque Country and her role as a reviewer for top-tier conferences and journals underline her recognition and influence in the global academic community.

Areas for Improvement:

  1. Broader International Collaboration: While Lingling Li has an impressive research record, increasing her international research collaborations beyond China and Spain could further elevate her impact. This could enhance her visibility and influence in broader global networks.
  2. Diversification of Research Topics: Her research is heavily concentrated on deep learning and image processing. Expanding into adjacent areas, such as AI ethics, sustainable AI, or interdisciplinary applications of AI, could further diversify her research portfolio.

Education:

🎓 Dr. Li earned her Ph.D. in Intelligent Information Processing from Xidian University, China (2017). She also holds a Bachelor’s degree in Electronic Information Engineering from the same university (2011). From 2013 to 2014, she was a visiting scholar at the University of the Basque Country in Spain, enhancing her global research perspective. 🌍

Experience:

👩‍🏫 Since 2020, Dr. Li has served as an Associate Professor at the School of Artificial Intelligence, Xidian University. Prior to this, she was a Lecturer at the same institution. She has supervised 16 master’s students and co-supervised 6 Ph.D. students, establishing herself as a leader in AI and remote sensing image interpretation. 💼

Research Focus:

🔍 Dr. Li’s research revolves around deep learning, quantum evolutionary optimization, and multi-scale geometric analysis. She works on complex image interpretation and target recognition, contributing to advancements in AI-powered remote sensing. Her research addresses pressing issues in multi-objective learning and large-scale remote sensing image retrieval. 🚀

Awards and Honours:

🏆 Dr. Li has received multiple national-level funding grants, including projects funded by the National Natural Science Foundation of China and Xidian University. Her research accomplishments are well-recognized in the academic community. 💡

Publications Top Notes:

📚 Dr. Li has contributed to top-tier journals and conferences, collaborating with renowned researchers. Some of her most notable works include:

“Region NMS-based deep network for Gigapixel Level Pedestrian Detection with Two-Step Cropping” – Neurocomputing, 2021 Cited by: 45

“Deep multi-level fusion network for multi-source image pixel-wise classification” – Knowl. Based Syst., 2021 Cited by: 50

IPGN: Interactiveness Proposal Graph Network for Human-Object Interaction Detection” – IEEE Trans. Image Process., 2021 Cited by: 78

“C-CNN: Contourlet Convolutional Neural Networks” – IEEE Trans. Neural Networks Learn. Syst., 2021 Cited by: 120

“Multi-Scale Progressive Attention Network for Video Question Answering” – ACL/IJCNLP, 2021 Cited by: 34

Conclusion:

Lingling Li is a highly deserving candidate for the Best Researcher Award. Her significant contributions to AI and deep learning, coupled with her leadership in research and mentorship, place her in an excellent position. With further expansion of her international collaborations and diversification of research, she could become a more influential figure on the global stage.