Tianlong Jia

Tianlong Jia

Postdoctoral researcher at Karlsruhe Institute of Technology (KIT)

You can also find my papers in my Google Scholar.

Journal Papers

  1. Jia, T.*, Taormina, R., de Vries, R., Kapelan, Z., van Emmerik, T. H. M., Vriend, P., & Okkerman, I. (2025). A semi-supervised learning-based framework for quantifying litter fluxes in river systems. Water Research. [PDF] [Code] [中文解读]

  2. Jia, T., Yu, J., Sun, A., Wu, Y., Zhang, S., & Peng, Z.* (2025). Semi-supervised learning-based identification of the attachment between sludge and microparticles in wastewater treatment. Journal of Environmental Management. [PDF] [Code]

  3. Jia, T.*, de Vries, R., Kapelan, Z., van Emmerik, T. H. M., & Taormina, R. (2024). Detecting floating litter in freshwater bodies with semi-supervised deep learning. Water Research. [PDF] [Code] [中文解读]

  4. Jia, T., Peng, Z.*, Yu, J., Piaggio, A. L., Zhang, S., & de Kreuk, M. K. (2024). Detecting the interaction between microparticles and biomass in biological wastewater treatment process with Deep Learning method. Science of The Total Environment. [PDF] [Code]

  5. Jia, T.*, Vallendar, A., de Vries, R., Kapelan, Z., & Taormina, R. (2023). Advancing Deep Learning-based Detection of Floating Litter using a Novel Open Dataset. Frontiers In Water. [PDF] [Code]

  6. Jia, T.*, Kapelan, Z., de Vries, R., Vriend, P., Peereboom, E. C., Okkerman, I., & Taormina, R. (2023). Deep learning for detecting macroplastic litter in water bodies: A review. Water Research. [PDF]

  7. Jia, T., Qin, H.*, Yan, D., Zhang, Z., Liu, B., Li, C., Wang, J., & Zhou, J. (2019). Short-term multi-objective optimal operation of reservoirs to maximize the benefits of hydropower and navigation. Water. [PDF]

  8. Yildizli, T.*, Jia, T., Langeveld, J., & Taormina, R. (2026). Self-supervised learning for multi-label sewer defect classification. Automation in Construction. [PDF] [Code] [中文解读]

  9. van Emmerik, T. H. M.*, Janssen, T. W., Jia, T., Bui, T.-K. L., Taormina, R., Nguyen, H.-Q., & Schreyers, L. J. (2025). Plastic pollution and water hyacinths consistently co-occur in the lower Saigon river. Environmental Research: Water. [PDF] [Code]

  10. Chen, G.*, Wu, X., Hu, L., Chi, Y., Jia, T., & Luo, Y. (2025). Numerical Analysis of 3D Slope Stability in a Rainfall-Induced Landslide: Insights from Different Hydrological Conditions and Soil Layering. Water. [PDF]

  11. Wu, Y., Ma, X., Guo, G., Jia, T., Huang, Y., Liu, S.*, Fan, J., & Wu, X. (2024). Advancing Deep Learning-Based Acoustic Leak Detection Methods Towards Application for Water Distribution Systems from a Data-centric Perspective. Water Research. [PDF]

  12. Chen, G., Zhang, K.*, Wang, S., & Jia, T. (2023). PHyL v1.0: A parallel, flexible, and advanced software for hydrological and slope stability modeling at a regional scale. Environmental Modelling & Software. [PDF] [Code]


Conference papers or abstract

  1. Ehret, U., Loritz, R., Bondy, J., Demuth, N., Dolich, A., Hollborn, S., Jia, T., et al. ML-based Flood Forecasting for Small Catchments in Germany: The KI-HOPE-DE project, The 2025 Annual Meeting of the European Meteorological Society (EMS), Ljubljana, Slovenia, September 2025. [Abstract]

  2. Yildizli, T., Jia, T., Langeveld, J., & Taormina, R. Self-supervised learning approach for automatic sewer defect detection, 13th Urban Drainage Modelling Conference, Innsbruck, Austria, September, 2025.

  3. Jia, T., Taormina, R., de Vries, R., Kapelan, Z., van Emmerik, T. H. M., Vriend, P., & Okkerman, I. Quantifying Floating Litter Fluxes with a Semi-Supervised Learning-Based Framework, EGU25 (European Geosciences Union) Conference, Vienna, Austria, April 2025. [Abstract]

  4. Yildizli, T., Jia, T., Langeveld, J., & Taormina, R. Self-Supervised Learning Approach for Sewer Defect Detection, 6th International Conference on Water Economics, Statistics and Finance and 10th Leading Edge Conference for Strategic Asset Management (LESAM), Pafos, Cyprus, April, 2025. [Abstract]

  5. Yildizli, T., Jia, T., Langeveld, J., & Taormina, R. Self-supervised learning approach for automatic sewer defect detection, 16th International Conference on Urban Drainage 2024, Delft, the Netherlands, June 2024.

  6. Jia, T., de Vries, R., Kapelan, Z., & Taormina, R. Detecting Floating Macroplastic Litter with Semi-Supervised Deep Learning, EGU24 (European Geosciences Union) Conference, Vienna, Austria, April 2024. [Abstract]

  7. Jia, T., de Vries, R., Kapelan, Z., & Taormina, R. Detecting Floating Macroplastic litter with Semi-supervised Deep Learning, AGU23 (American Geophysical Union) Conference, San Francisco, CA, the United States, December 2023. [Abstract]

  8. Vallendar, A., Jia, T., de Vries, R., Kapelan, Z., & Taormina, R. An open source dataset for Deep Learning-based visual detection of floating macroplastic litter, EGU23 (European Geosciences Union) Conference, Vienna, Austria, April 2023. [Abstract]

  9. Jia, T., de Vries, R., Kapelan, Z., & Taormina, R. A robust deep learning methodology to detect floating macro-plastic litter in rivers, EGU22 (European Geosciences Union) Conference, Vienna, Austria, May 2022. [Abstract]

  10. Jia T., Zhou J.*, & Liu X. A daily power generation optimized operation method of hydropower stations with the navigation demands considered, 1st International Symposium on Water System Operations, Beijing, China, 2018 [Conference Paper]

*: corresponding author

Doctoral Thesis

Jia, T. (2025). Deep learning-based Methods for Detecting and Quantifying floating litter in Riverine Environments, Dissertation (TU Delft), Delft University of Technology.

Datasets