More information in personal website: https://tianlongjia.github.io/
Karlsruher Institut für Technologie (KIT)
Institut für Wasser und Umwelt
Bereich Hydrologie
Kaiserstraße 12
76131 Karlsruhe
More information in personal website: https://tianlongjia.github.io/
KI-HopE-De - AI-based flood prediction in small river basins in Germany (2025-current)
AI-based detecting and quantification of floating macroplastic litter in rivers and urban waterways in the Netherlands (2020-2025)
Optimal reservoir operation in the upper and middle reaches of the Yangtze River, China, considering power generation, flood control, and navigation demands (2017–2020)
My primary research interests are in emerging problems related to environment monitoring, smart water management, and artificial intelligence research, including:
Journal Papers
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.
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.
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.
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.
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.
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.
van Emmerik, T. H. M.*, Janssen, T. W., Jia, T., Bui, T.-K. L., Taormina, R., Nguyen, H.-Q., & Schreyers, L. J. (2024). Water hyacinths as riverine plastic pollution carriers. Biogeosciences (Pre-print).
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.
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.
Conference papers or abstract
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.
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.
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.
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.
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.
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.
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.
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.
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
Academic Conferences & forums
Professional Membership
Reviewer for Journals