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PhD in Engineering (Wuhan Tech University of Surveying and Mapping)
Research theme: Data Science
Research discipline: Computer Science
Research area
Dr Yanming Feng is a Professor in data science, networks and navigation with the School of Computer Science, Queensland University of Technology, Brisbane, Australia. He received PhD, MSc, and BSc degrees in satellite geodesy and spatial science from Wuhan Technical University of Surveying and Mapping (Wuhan University since 2000),Wuhan, China. His teaching subjects mainly include the computer science and electrical engineering areas including networks security, wireless mobile networks, research in IT practice, research methods for engineers and spacecraft dynamics and control. His active research areas include global navigation satellite systems (GNSS) algorithms, geodetic data analytics, satellite orbit determination and space debris monitoring, Internet of Things, precise positioning and deformation monitoring, vehicular networks and communications and machine learning applications. He published papers in the journals such as for geodesy, navigation, aerospace, sensors, remote sensing, vehicular networks, and intelligent transport systems. Prof Feng has supervised about 24 Higher Degree Research (HDR) students to completion. He has supervised and mentored post-doctoral fellows, research fellows funded by various awarded research projects since 2005. His research leaderships are highlighted by Chief Investigator roles within Cooperative Research Centre for Satellite Systems (CRCSS, 1999-2006) and 3 Australian Research Council (ARC) grants (2003 to 2007, 2015-2018) and Project Leader roles in Automotive CRC (2007-2013), CRC for Spatial Information (2007-2015) and Innovative Manufacturing CRC (2019 to 2022), and iMOVE CRC in 2020. Professor Feng served as the Editor-in-Chief for Journal of Global Positioning Systems from 2009 to 2013. He also served in the editorial board for the official journal “Engineering” of Chinese Academy of Engineering since 2019.
Yanming Feng worked for Wuhan Technical University of Surveying and Mapping as a Lecturer from 1990 to 1992. He joined Queensland University of Technology as a Post-Doctoral Fellow from 1992 to 1995, and Research Fellow from 1995 to 1999. He served the duties of Research Fellow and Sensor Research Fellow for the Cooperative Research Centre for Satellite Systems (CRCSS) from 1999 to 2006. He served QUT as Associate Professor in 2006 and as Professor since 2010.
For perspective research students and researchers
Professor Feng supervised PhD and research master students for research topics related to GNSS, spatial data analytics, Internet of Things, vehicle networks and safety, deformations, satellite orbit determination, space debris monitoring, machine learning and deep learning applications in the related research areas.
Potential research areas for future PhD students
- Fundamental GNSS data analytics and algorithms for millimetre precise positioning and millimetre geodesy
- Machine learning approaches for geodetic data analytics, time series analysis, deformation analysis, navigation error analysis
- Precise orbit determination and space debris monitoring
- Precision Internet of Things (PIOT) networks, offload computing and industry applications
- Vehicle to everything communications and positioning for road safety applications
- Internet of Thing systems for water data acquisition, analytics, and services
- Software-defined radio for satellite communications
- Monitoring landslides using satellite IoT and GNSS observations
Additional information
Yanming Feng has established engagement with government agencies and industry partners in the sectors including spatial information, geoscience, intelligent transportations, and mining and manufacturing. His real-world industry collaborations have focused on development of Internet of Things systems for GNSS-based automated deformation and landslide monitoring at millimeter position accuracy. He has also undertaken research collaborations for IoT solutions for water quality data acquisition and analytics and vehicle to everything communications for road safety.
Flood, pollution Drifter goes with the flow: https://www.qut.edu.au/research/article?id=133268
- Dasanayaka, N. & Feng, Y. (2022). Analysis of Vehicle Location Prediction Errors for Safety Applications in Cooperative-Intelligent Transportation Systems. IEEE Transactions on Intelligent Transportation Systems, 23(9), 15512–15521. https://eprints.qut.edu.au/233914
- Gao, W., Li, Z., Chen, Q., Jiang, W. & Feng, Y. (2022). Modelling and prediction of GNSS time series using GBDT, LSTM and SVM machine learning approaches. Journal of Geodesy, 96(10). https://eprints.qut.edu.au/237278
- Li, B., Huang, J., Feng, Y., Wang, F. & Sang, J. (2020). A Machine Learning-Based Approach for Improved Orbit Predictions of LEO Space Debris With Sparse Tracking Data From a Single Station. IEEE Transactions on Aerospace and Electronic Systems, 56(6), 4253–4268. https://eprints.qut.edu.au/209007
- Hasan, K., Feng, Y. & Tian, G. (2018). GNSS time synchronization in vehicular ad-hoc networks: benefits and feasibility. IEEE Transactions on Intelligent Transportation Systems, 19(12), 3915–3924. https://eprints.qut.edu.au/223438
- Lou, Y., Gong, X., Gu, S., Zheng, F. & Feng, Y. (2017). Assessment of code bias variations of BDS triple-frequency signals and their impacts on ambiguity resolution for long baselines. GPS Solutions, 21(1), 177–186. https://eprints.qut.edu.au/94739
- Li, B., Feng, Y., Gao, W. & Li, Z. (2015). Real-time kinematic positioning over long baselines using triple-frequency BeiDou signals. IEEE Transactions on Aerospace and Electronic Systems, 51(4), 3254–3269. https://eprints.qut.edu.au/94737
- Li, B., Shen, Y., Feng, Y., Gao, W. & Yang, L. (2014). GNSS ambiguity resolution with controllable failure rate for long baseline network RTK. Journal of Geodesy, 88(2), 99–112. https://eprints.qut.edu.au/69073
- Feng, Y., Shen, Y. & Li, B. (2010). Three carrier ambiguity resolution : distance-independent performance demonstrated using semi-generated triple frequency GPS signals. GPS Solutions, 14(2), 177–184. https://eprints.qut.edu.au/48955
- Feng, Y. & Li, B. (2010). Wide area real time kinematic decimetre positioning with multiple carrier GNSS signals. Science in China, Series D: Earth Sciences, 53(5), 731–740. https://eprints.qut.edu.au/77210
- Feng, Y., (2008). GNSS three carrier ambiguity resolution using ionosphere-reduced virtual signals. Journal of Geodesy, 82(12), 847–862. https://eprints.qut.edu.au/30747
- Title
- Advances in real-time Satellite Monitoring of flow in Rivers and Estuaries
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- LP150101172
- Start year
- 2016
- Keywords
- Predicting 3D soil settlement using precise GNSS data and machine learning
PhD, Associate Supervisor
Other supervisors: Professor Tommy Chan - Feasibility Studies of Utilizing Geostationary Satellites As Network and Satellite Controllers for Non-Geostationary Satellites
PhD, Principal Supervisor
Other supervisors: Professor Glen Tian - Positioning Errors Modelling and Prediction Using Machine Learning Approaches
PhD, Principal Supervisor
Other supervisors: Dr Charles Wang - Enhancing Electronic Health Record Storage and Processing: A Distributed Model Leveraging MYCAT
MPhil, Principal Supervisor
Other supervisors: Dr Jinglan Zhang
- Mobile Broadband Enabled Cooperative-ITS Approaches for Vulnerable Road User Safety (2022)
- GNSS Time Synchronisation in Co-Operative Vehicular Networks (2018)
- Development and Use of GPS-Based Technology to Study Dispersion in Shallow Water (2017)
- Geometry-Free Analysis Approaches for Noises and Hardware Biases in Triple-Frequency GNSS Signals (2017)
- Reliability Control of GNSS Carrier-phase Integer Ambiguity Resolution (2015)
- Achieving High Reliability for Ambiguity Resolutions with Multiple GNSS Constellations (2012)
- An Integrated Approach for Precise Road Reconstruction from Aerial Imagery and LiDAR Data (2011)
- Generation of Network-Based Differential Corrections for Regional GNSS Services (2007)
- Near-Real-Time GPS Sensing of Atmospheric Water Vapor (2005)
- Onboard Orbit Determination Using GPS Measurements for Low Earth Orbit Satellites (2005)