Professor at Royal Institute of Technology, Sweden
Associate Professor Jingbin Liu is an accomplished geospatial scientist specializing in mobile mapping, 3D modeling, and robotics navigation. With a strong foundation in geomatics and over 15 years of international research experience, he has contributed significantly to both academic and applied aspects of geospatial technologies. Currently serving at KTH Royal Institute of Technology in Sweden, he previously held professorial and senior research roles in China and Finland. Liu has led over 15 major research projects and secured substantial external funding, indicating his strong leadership and innovation capacity. His scholarly output includes more than 100 peer-reviewed publications, over 5,300 citations, and an h-index of 37, reflecting his global impact. He is also known for successfully mentoring postdoctoral and doctoral researchers, many of whom have advanced to prominent academic and research positions. Liu’s work bridges the gap between research and real-world application, notably through patented technologies and industry collaborations.
Professional Profile
Education🎓
Jingbin Liu holds a distinguished academic background rooted in geomatics and satellite navigation. He earned his Ph.D. in Geomatics from Wuhan University’s School of Geodesy and Geomatics in 2008, with a dissertation focusing on regional ionospheric TEC prediction using GPS—rated as excellent. He also completed his Master of Science in Engineering at Wuhan University in 2004, with a thesis on simulating and verifying the Galileo satellite navigation system, also rated excellent. In 2016, Liu was granted a prestigious Docentship in Geospatial Information Technology, specifically in robotics navigation and 3D modeling, by Wuhan University’s State Key Laboratory of Surveying, Mapping and Remote Sensing. This academic journey reflects a blend of theoretical expertise and applied innovation, providing a solid foundation for his research and teaching. Liu’s education has equipped him with a rare combination of depth in geospatial sciences and a multidisciplinary approach to cutting-edge technological challenges.
Professional Experience📝
Jingbin Liu brings a wealth of global experience in academia and research. Since January 2025, he has been serving as an Associate Professor at KTH Royal Institute of Technology, Sweden. Prior to this, he held a full professorship at Wuhan University from 2016 to 2024 and was also a Visiting Professor at the Finnish Geospatial Research Institute (FGI). He previously worked as a Senior Researcher at FGI and the Academy of Finland’s Center of Excellence in Laser Scanning Research from 2008 to 2019. His career reflects a seamless integration of academic leadership and advanced research contributions across China, Finland, and Sweden. Liu has actively managed multidisciplinary teams and international collaborations, with a proven track record in securing competitive research funding and leading innovative projects. His professional journey exemplifies a robust commitment to advancing geospatial technologies through both theoretical advancements and real-world implementation.
Research Interest🔎
Associate Professor Jingbin Liu’s research interests lie at the intersection of geospatial information technology and intelligent systems. He specializes in mobile mapping, 3D modeling of built environments, robotics navigation, and indoor positioning. His work focuses on developing advanced algorithms and systems that enable accurate and efficient geospatial data acquisition, particularly in challenging environments such as underground infrastructure and urban interiors. Liu has also contributed to integrating LiDAR, GPS, and vision-based technologies to enhance positioning accuracy and environmental modeling. His interest extends to autonomous driving systems, infrastructure inspection robots, and wearable geolocation systems for worker safety. By addressing real-world geospatial challenges with state-of-the-art tools, Liu’s research supports the evolution of smart cities and intelligent navigation solutions. He is particularly invested in transforming traditional surveying and mapping practices through automation, AI integration, and cross-disciplinary innovation, thereby enhancing the operational efficiency and accuracy of geospatial data systems.
Award and Honor🏆
Jingbin Liu has received multiple prestigious awards and honors that recognize his contributions to geospatial research and technological innovation. In 2023, he was honored with the Science and Technology Progress Award by the Hubei Provincial Government, and in 2021, he received the Science and Technology Advancement Award from the China Satellite Navigation and Positioning Association. His excellence in applied research earned him the Best Paper Award at the IEEE UPINLBS Conference in 2019. Internationally, he won first place in the PerfLoc Indoor Positioning Competition held by NIST in the United States and the IPIN Indoor Positioning Competition in France, both in 2018. He was also awarded the First Prize for Scientific and Technological Progress by the China Society of Geodesy. These accolades reflect his leadership in positioning and navigation technologies and his significant impact on both academic and industrial sectors worldwide.
Research Skill🔬
Jingbin Liu possesses advanced research skills in geospatial computation, mobile mapping, and sensor fusion. He is proficient in integrating LiDAR, GNSS, visual-inertial odometry, and SLAM (Simultaneous Localization and Mapping) systems to develop high-precision navigation solutions. His expertise extends to robotics navigation in complex environments, such as underground pipelines, where he has led the development of intelligent inspection systems. Liu demonstrates strong capabilities in algorithm design for positioning, real-time data processing, and 3D environmental reconstruction. He also has experience with indoor positioning systems using WiFi, Bluetooth, and 3D modeling integration. Beyond technical skills, Liu excels in project leadership, proposal writing, and technology transfer—evidenced by his successful patent and partnerships with industry stakeholders. His mentoring ability, particularly in guiding postdocs and PhD students to success, highlights his academic training expertise. Altogether, his skills position him as a top-tier researcher in applied geospatial technology and spatial computing.
Conclusion💡
Associate Professor Jingbin Liu is highly suitable for the Best Researcher Award. His excellent academic record, consistent funding success, internationally recognized research, real-world technological innovation, and strong mentorship track make him a standout candidate. He exemplifies a researcher who bridges theory and application, academia and industry, and local and international contexts.
Publications Top Noted✍
-
Title: Is field-measured tree height as reliable as believed?
Authors: Y Wang, M Lehtomäki, X Liang, J Pyörälä, A Kukko, A Jaakkola, J Liu, …
Year: 2019
Citations: 330
-
Title: A review: Remote sensing sensors
Authors: L Zhu, J Suomalainen, J Liu, J Hyyppä, H Kaartinen, H Haggren
Year: 2018
Citations: 254
-
Title: A Hybrid Smartphone Indoor Positioning Solution for Mobile LBS
Authors: J Liu, R Chen, L Pei, R Guinness, H Kuusniemi
Year: 2012
Citations: 237
-
Title: Human Behavior Cognition Using Smartphone Sensors
Authors: L Pei, R Guinness, R Chen, J Liu, H Kuusniemi, Y Chen, L Chen, …
Year: 2013
Citations: 197
-
Title: International benchmarking of individual tree detection methods using airborne laser scanning
Authors: Y Wang, J Hyyppä, X Liang, H Kaartinen, X Yu, E Lindberg, J Holmgren, …
Year: 2016
Citations: 193
-
Title: Using Inquiry-based Bluetooth RSSI Probability Distributions for Indoor Positioning
Authors: L Pei, R Chen, J Liu, H Kuusniemi, T Tenhunen, Y Chen
Year: 2010
Citations: 181
-
Title: LiDAR Scan Matching Aided Inertial Navigation System in GNSS-Denied Environments
Authors: J Tang, Y Chen, X Niu, L Wang, L Chen, J Liu, C Shi, J Hyyppä
Year: 2015
Citations: 163
-
Title: Using LS-SVM Based Motion Recognition for Smartphone Indoor Wireless Positioning
Authors: L Pei, J Liu, R Guinness, Y Chen, H Kuusniemi, R Chen
Year: 2012
Citations: 163
-
Title: Accuracy of Kinematic Positioning Using GNSS under Forest Canopies
Authors: H Kaartinen, J Hyyppä, M Vastaranta, A Kukko, A Jaakkola, X Yu, …
Year: 2015
Citations: 159
-
Title: A Review of GNSS-based Dynamic Monitoring for Structural Health Monitoring
Authors: N Shen, L Chen, J Liu, L Wang, T Tao, D Wu, R Chen
Year: 2019
Citations: 140
-
Title: Spherical cap harmonic model for mapping and predicting regional TEC
Authors: J Liu, R Chen, Z Wang, H Zhang
Year: 2011
Citations: 138
-
Title: The Use of a Hand-Held Camera for Individual Tree 3D Mapping
Authors: X Liang, A Jaakkola, Y Wang, J Hyyppä, E Honkavaara, J Liu, …
Year: 2014
Citations: 137
-
Title: Forest Data Collection Using Terrestrial Image-Based Point Clouds
Authors: X Liang, Y Wang, A Jaakkola, A Kukko, H Kaartinen, J Hyyppä, …
Year: 2015
Citations: 132
-
Title: Inquiry-Based Bluetooth Indoor Positioning via RSSI Probability Distributions
Authors: L Pei, R Chen, J Liu, T Tenhunen, H Kuusniemi, Y Chen
Year: 2010
Citations: 112
-
Title: A Robust Indoor Positioning Method Based on Bluetooth Low Energy
Authors: B Huang, J Liu, W Sun, F Yang
Year: 2019
Citations: 93
-
Title: iParking: An Intelligent Indoor Location-Based Smartphone Parking Service
Authors: J Liu, R Chen, Y Chen, L Pei, L Chen
Year: 2012
Citations: 90
-
Title: A Survey of Simultaneous Localization and Mapping
Authors: B Huang, J Zhao, J Liu
Year: 2019
Citations: 88
-
Title: Close-Range Remote Sensing of Forests: Challenges and Opportunities
Authors: X Liang, A Kukko, I Balenović, N Saarinen, S Junttila, V Kankare, …
Year: 2022
Citations: 84
-
Title: M3VSNet: Unsupervised Multi-Metric Multi-View Stereo Network
Authors: B Huang, H Yi, C Huang, Y He, J Liu, X Liu
Year: 2021
Citations: 82
-
Title: A Survey of Applications with Combined BIM and 3D Laser Scanning
Authors: J Liu, D Xu, J Hyyppä, Y Liang
Year: 2021
Citations: 80