Li Haoqing

Prof. Dr. Haoqing Li

Assistant Professor of Computer Science and Engineering
School of Computer Science & Engineering
Constructor University Bremen gGmbH
Campus Ring 1 | 28759 Bremen | Germany
Fax number
+49 421 200-3103
Email Address
haoli@constructor.university
Office
Research I, Room 95
Research Interests

My research interests include Bayesian filtering, deep learning, and robust statistics, aiming to solve complex in challenging environment where standard methods fall shot. The current applications are mainly in GNSS signal processing and satellite image processing.

University Education
2023Ph.D., Electrical and Computer Engineering, Northeastern University
2018M.S., Electrical and Computer Engineering, Northeastern University
2016B.S., Electronic Information School, Wuhan University
Professional Experience
03/2026 – presentAssistant Professor, Constructor University, Germany
05/2023 – 05/2025Postdoctoral Associate, University of Calgary, Canada
09/2018 – 05/2023Research Assistant, Northeastern University, USA
Research Output
  • 14 journal publications and 16 peer-reviewed conference/workshop publications
  • 644 citations, h-index 15, i10-index 16
Funding

PI, Eyes High Match Funding Postdoctoral Fellowship, University of Calgary, 2023–2025, CAD 50,000

Awards

Dean’s Fellowship Award, Northeastern University, 2018

Teaching Experience
2024Guest Lecturer, Advanced GNSS Theory, University of Calgary
2019 – 2023Teaching Assistant, Fundamentals of Linear Systems and Digital Signal Processing, Northeastern University
Professional Service
  • Member, IEEE
  • Member, Institute of Navigation (ION)
  • TPC Member, IEEE PIMRC 2024
  • Reviewer for multiple journals including IEEE Transactions, Remote Sensing, Sensors, GPS Solution, and Navigation
Selected Publications
  • H. Li, J. Vil‘a-Valls, and P. Closas. “Robust Adaptive Nonlinear KF Under Hierarchically Gaussian Outliers,” IEEE Control Systems Letter, 10.1109/LCSYS.2025.3597306
  • H. Li, S. Tang, P. Wu, and P. Closas. “Robust Interference Mitigation Techniques for Direct Position Estimation,” IEEE Transactions on Aerospace and Electronic Systems, 2023. 10.1109/TAES.2023.3312350
  • H. Li, B. Duvvuri, R. Borsoi, T. Imbiriba, E. Beighley, D. Erdogmus, and P. Closas. “Online fusion of multi-resolution multispectral images with weakly supervised temporal dynamics,” ISPRS Journal of Photogrammetry and Remote Sensing, 196:471–489, 2023. https://doi.org/10.1016/j.isprsjprs.2023.01.012
  • H. Li, R. A. Borsoi, T. Imbiriba, P. Closas, J. C. Bermudez, and D. Erdogmus, “Model-based deep autoencoder networks for nonlinear hyperspectral unmixing,” IEEE Geoscience and Remote Sensing Letters, vol. 19, pp. 1–5, 2021. 10.1109/LGRS.2021.3075138
  • H. Li, P. Borhani-Darian, P. Wu, and P. Closas. “Deep neural network correlators for GNSS multipath mitigation,” IEEE Transactions on Aerospace and Electronic Systems, 2022. 10.1109/TAES.2022.3197098
  • H. Li, D. Medina, J. Vil‘a-Valls, and P. Closas, “Robust variational-based Kalman filter for outlier rejection with correlated measurements,” IEEE Transactions on Signal Processing, vol. 69, pp. 357–369, 2020. 10.1109/TSP.2020.3042944