Associate Professor | Zhejiang University of Technology |China

Yinglong Li demonstrates strong academic and research excellence, supported by a solid portfolio of publications, patents, and externally funded projects. His 22 SCI/Scopus-indexed journal papers, more than 140 Web of Science citations, and a steadily increasing h-index reflect both productivity and growing scholarly influence. His contributions are further validated through documented outputs such as two published textbooks (ISBN: 9787302557425, 9787115415400), ten patents, and verified academic profiles including Google Scholar and institutional webpages. Strengths include his ability to integrate privacy protection, deep learning, and computer vision into practical AI solutions, as evidenced by consultancy projects with industry partners in marine systems and smart security. His research has consistently translated into deployable, high-impact technologies, demonstrating maturity in innovation and applied problem-solving. Areas for improvement include expanding international collaborations, enhancing cross-disciplinary engagement with emerging domains such as trustworthy AI governance, and increasing participation in editorial boards or leadership roles in prestigious conferences, which would further elevate his global visibility. Moving forward, his research has strong potential to contribute significantly to privacy-preserving intelligent systems, multimodal vision architectures, and secure data ecosystems for smart cities. With a well-documented research track record, growing citation metrics, and scalable research themes aligned with global technological needs, he is positioned for continued advancement and wider impact in the AI research community.

Citation Metrics (Google Scholar)

240180

120

Citations
234

h-index
8

i10-index
6

Citations
h-index
i10-index

Mr. Petar Donev - Remote Sensing - Best Researcher Award

Hohai University - China

Author Profile

SCOPUS

ORCID

🌟 Early academic pursuits

Petar Donev's academic journey began with a deep interest in geodesy and geosciences. he earned his bachelor’s degree in geodesy from ss. “cyril and methodius” university in skopje, north macedonia, completing a thesis on analyzing lidar data using open-source gis software. his dedication to understanding cartographic systems and digital geospatial data laid the groundwork for his future contributions. furthering his academic growth, he pursued a master’s degree in cartography and gis at hohai university, china, where his research focused on estimating and mapping forest above-ground biomass using lidar data and multispectral satellite imagery. his educational foundation culminated in his ongoing doctoral studies at hohai university, where he specializes in mapping forest agb using multisource data in mountainous regions.

📚 Professional endeavors

Petar began his career in geodesy as a surveying technician, contributing to land and building surveys. later, as a geodetic engineer at the agency for real estate and cadaster in north macedonia, he worked on creating digital cadastral maps using advanced software. his teaching skills were honed at sggs “zdravko cvetkovski” high school, where he imparted knowledge on geoscience. his academic journey also includes a pedagogical certification from ss. “cyril and methodius” university, reflecting his commitment to both geodesy and education.

🌍 Contributions and research focus

petar’s research primarily revolves around mapping forest above-ground biomass using innovative technologies like lidar and multispectral satellite imagery. his Remote Sensing doctoral work explores agb mapping in mountainous regions, reflecting his focus on sustainable land management and environmental conservation. his expertise extends to leveraging gis tools for hydrology and forest dynamics, bridging the gap between geospatial technology and ecological insights.

🏆 Accolades and recognition

petar's academic and professional journey is marked by his achievements in geodesy and gis. earning a master’s degree and progressing to a doctoral candidate at Remote Sensing prestigious institutions like hohai university highlights his dedication and excellence. his successful completion of a mini-mba program from ibmi, berlin, underscores his multidisciplinary approach and leadership aspirations.

🌟 Impact and influence

petar has contributed significantly to advancing geospatial research, particularly in the areas of agb mapping and digital cadastral systems. his work not only aids in sustainable forestry and land management but also demonstrates the practical applications of lidar and gis technologies in real-world scenarios. his teaching Remote Sensing experience further amplifies his influence, inspiring future professionals in geoscience and geodesy.

🔗 Legacy and future contributions

with a focus on integrating multisource data and advanced technologies, petar aims to refine methodologies for agb estimation and digital mapping. his research Remote Sensing promises to provide vital insights for environmental planning and disaster mitigation in mountainous and forested regions. as he continues to innovate, petar’s legacy will inspire the geospatial community to harness technology for sustainable development.

Notable Publications

Title: Cross-modal fusion approach with multispectral, LiDAR, and SAR data for forest canopy height mapping in mountainous region
Authors: Petar Donev, Hong Wang, Shuhong Qin, Xiuneng Li, Meng Zhang, Sisi Liu, Xin Wang
Journal: Physics and Chemistry of the Earth, Parts A/B/C
Title: Enhancing Landsat image-based aboveground biomass estimation of black locust with scale bias-corrected LiDAR AGB map and stratified sampling
Authors: Shuhong Qin, Hong Wang, Xiuneng Li, Jay Gao, Jiaxin Jin, Yongtao Li, Jinbo Lu, Pengyu Meng, Jing Sun, Zhenglin Song, et al.
Journal: Geo-spatial Information Science
Title: Estimating the Forest Above-Ground Biomass Based on Extracted LiDAR metrics and Predicted Diameter at Breast Height
Authors: Petar Donev, Hong Wang, Shuhong Qin, Pengyu Meng, Jinbo Lu
Journal: Journal of Geodesy and Geoinformation Science