HAIFEI CHEN | Visual SLAM | Best Researcher Award

Assoc .Prof. Dr. HAIFEI CHEN | Visual SLAM | Best Researcher Award

Central South University of Forestry and Technology, China

Dr. Haifei Chen is an accomplished Associate Professor at the School of Mechanical and Intelligent Manufacturing, Central South University of Forestry and Technology. Born in August 1990 in Chenzhou, Hunan, he is a dedicated scholar in the field of robotics and intelligent control. With a strong academic background and robust research portfolio, he has led numerous national and provincial research projects focusing on teleoperation robotics, multi-agent coordination, SLAM, and networked control systems. His scholarly contributions include over 20 high-impact SCI-indexed journal articles and multiple patents. A recognized academic leader, Dr. Chen holds key roles in national research centers and professional societies and serves as a reviewer for top-tier IEEE journals. His research has significantly advanced space robotics and teleoperation technologies. Through innovation, leadership, and academic excellence, he has positioned himself as a promising and impactful researcher in the field of intelligent robotics.

Professional Profile 

Education🎓

Dr. Haifei Chen pursued his doctoral studies at the School of Astronautics, Northwestern Polytechnical University, beginning in September 2017. His Ph.D. specialization was in navigation, guidance, and control under the supervision of Professor Panfeng Huang, a prominent academician and expert affiliated with the National Distinguished Youth Fund and military science commissions. Dr. Chen’s doctoral research focused on time-delay modeling and compensation for space teleoperation systems, laying a strong theoretical foundation for his current work. Prior to his doctoral education, he had successfully cleared national English proficiency exams including CET-6 and achieved an IELTS score of 6.0, reflecting a solid command of the English language for academic communication. His educational experience has equipped him with expertise in robotics, control systems, and artificial intelligence, supporting his contributions to both theoretical research and engineering practice. His education forms the core of his academic identity and drives his research in intelligent robotic systems.

Professional Experience📝

Dr. Haifei Chen currently serves as an Associate Professor at the School of Mechanical and Intelligent Manufacturing, Central South University of Forestry and Technology, a position he has held since December 2023. Prior to this, he was a Lecturer at the School of Mechanical and Electrical Engineering at the same university from February 2022 to December 2023. His academic trajectory has been steadily progressive, with research and teaching roles focused on robotic teleoperation, intelligent control, and remote robotic systems. His leadership includes managing multiple funded projects, mentoring students, and contributing to institutional development as a discipline leader in forestry equipment and intelligent systems. He is also affiliated with key research centers, including the National Engineering Research Center for Economic Forest Harvesting Equipment. His experience bridges fundamental research and practical implementation, making him a vital contributor to the advancement of robotics in forestry and space technology domains.

Research Interest🔎

Dr. Haifei Chen’s research interests are deeply rooted in robotic teleoperation, intelligent control, and multi-agent system collaboration. His work explores the challenges of time-delay in remote control systems, particularly in space teleoperation, with the goal of enhancing the precision and reliability of robotic operations under communication constraints. He is also focused on visual SLAM (Simultaneous Localization and Mapping), predictive control, and networked control systems—all critical to the development of autonomous and semi-autonomous robotic platforms. His recent research involves developing teleoperation systems for agricultural and forestry robots, such as oil-tea camellia fruit picking, using advanced machine learning algorithms and sensor fusion techniques. Dr. Chen aims to bridge the gap between theoretical models and practical deployment by incorporating real-time data processing, human-robot interaction, and decision-making algorithms. These interests reflect a multidisciplinary approach, integrating robotics, AI, and control theory to create intelligent, adaptive, and scalable robotic systems.

Award and Honor🏆

Dr. Haifei Chen has earned recognition both as a researcher and a community contributor. He serves as an expert reviewer for the National Natural Science Foundation of China (NSFC), reflecting his authority in his research field. He is the Vice Director of the National Engineering Research Center for Economic Forest Harvesting Equipment and serves on the Youth Committee of the Chinese Society of Forestry and the Robotics Subcommittee. These positions highlight his leadership within the academic and scientific communities. Furthermore, Dr. Chen has served as a reviewer for several internationally renowned journals, including IEEE Transactions on Systems, Man and Cybernetics: Systems, IEEE Transactions on Mechatronics, IEEE RA-L, Acta Astronautica, and ISA Transactions. His contributions to academic peer review and research management are clear indicators of professional excellence. While individual awards are not specifically listed, his prestigious roles and responsibilities underscore his impact and growing recognition in the robotics field.

Research Skill🔬

Dr. Haifei Chen possesses a versatile and advanced set of research skills in robotics and intelligent systems. He is highly proficient in modeling and controlling time-delay in networked and remote robotic systems—skills critical for real-time space and teleoperation environments. He has strong command over predictive control algorithms, Smith predictors, and error loop correction methods. His expertise extends to multi-agent coordination, robot vision (including SLAM), and motion planning, where he integrates machine learning techniques such as CNNs, BiGRUs, and attention mechanisms for state prediction and decision-making. He is adept at developing algorithms that optimize robotic response in high-latency environments, such as relay communication-based space missions. In addition to algorithm design, he is experienced in real-time robotic system integration and experimental validation. With skills spanning simulation, hardware interfacing, and intelligent control, Dr. Chen brings a comprehensive and technically rigorous approach to research that bridges theoretical development and engineering implementation.

Conclusionđź’ˇ

Dr. Haifei Chen presents a compelling case as a young and dynamic researcher who combines technical depth, publication excellence, research leadership, and innovation in intelligent robotics and remote control systems. He shows a rare blend of academic rigor, engineering practice, and institutional responsibility.

With minor enhancements in international outreach and broader recognition, he is on a strong trajectory toward becoming a leading figure in his domain. He is not only suitable, but in fact, a competitive nominee for the Best Researcher Award.

Publications Top Noted✍

  • Title: Path Integral Policy Improvement and Dynamic Movement Primitives Fusion-Based Impedance Force Control With Error Loop Correction
    Authors: Mujie Liu, Haifei Chen, Lijun Li, Zhiqiang Ma, Yong Xu, Hui Zhang
    Year: 2025
    Citation: IEEE Transactions on Automation Science and Engineering, DOI: 10.1109/TASE.2025.3562677

  • Title: Mapping Noise Optimization of the Cartographer on the Premise of Comparative Experimental Analysis
    Authors: Xuefei Liu, Haifei Chen, Zicheng Gao, Meirong Chen, Lijun Li, Kai Liao
    Year: 2025
    Citation: Mechatronics, DOI: 10.1016/j.mechatronics.2024.103289

  • Title: Position Prediction for Space Teleoperation With SAO-CNN-BiGRU-Attention Algorithm
    Authors: Keli Wu, Haifei Chen, Lijun Li, Zhengxiong Liu, Haitao Chang
    Year: 2024
    Citation: IEEE Robotics and Automation Letters, DOI: 10.1109/LRA.2024.3498700

  • Title: Bilateral Synchronization Control of Networked Teleoperation Robot System
    Authors: Zhengxiong Liu, Haifei Chen, Panfeng Huang, Yang Yang
    Year: 2024
    Citation: International Journal of Robust and Nonlinear Control, DOI: 10.1002/rnc.7374

  • Title: Time-Delay Modeling and Simulation for Relay Communication-Based Space Telerobot System
    Authors: Haifei Chen, Zhengxiong Liu, Panfeng Huang, Zhian Kuang
    Year: 2022
    Citation: IEEE Transactions on Systems, Man, and Cybernetics: Systems, DOI: 10.1109/TSMC.2021.3090806

  • Title: Time-Delay Prediction–Based Smith Predictive Control for Space Teleoperation
    Authors: Haifei Chen, Zhengxiong Liu
    Year: 2021
    Citation: Journal of Guidance, Control, and Dynamics, DOI: 10.2514/1.G005714

Jingbin Liu | Sensor fusion | Best Researcher Award

Prof . Jingbin Liu | Sensor fusion | Best Researcher Award

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.

Conclusionđź’ˇ

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