Trantas, A., Mensio, M., Stasinos, S., Gribincea, S., Khan, T., Podareanu, D., & van der Veen, A. (2026). BioAnalyst: A foundation model for biodiversity. Ecological Informatics, 104066. DOI: https://doi.org/10.1016/j.ecoinf.2026.104066
Research Publications
Research publications by Taimur Khan on Earth observation, forest structure inference, biodiversity digital twins, remote sensing, AI, and ecological modelling.
Research Publications
Research
Selected papers, preprints, proceedings, and workshop contributions across remote sensing, biodiversity modelling, research software, and environmental data science.
17 entries
2026-2017 timeline
Earth AI focus
Herzschuh, U., Schild, L., Farkas, L., Caus, D., Xia, J., Weigel, T., Dammers, J., Demir, B., Golivets, M., Gupta, V., Hagen, O., Jansen, F., Khan, T., Kramer, A., Kühn, I., Mensio, M., Nieto-Lugilde, D., Persello, C., Rasti, B., … Zurell, D. (2026). Paleo-grounded biodiversity foundation models for long-horizon species distribution forecasting. Frontiers in Ecology and Evolution, 14. DOI: https://doi.org/10.3389/fevo.2026.1894720
Khan, T. (2026). PhenoEmbed: Self-Supervised Multispectral UAV Time-Series Embeddings for Individual Tree Crown Phenology. Resilience and AI Workshop Proceedings at the INFORMATIK Festival (archival track). arXiv:2607.10231. DOI: https://doi.org/10.48550/arXiv.2607.10231
Khan, T. (2026): HeideBench: A Multispectral UAV Time-Series Benchmark for Forest Crown Phenology in Dölauer Heide [dataset]. PANGAEA, https://doi.pangaea.de/10.1594/PANGAEA.993969 (DOI registration in progress)
Khan, T., Feilhauer, H., & Zafar, M. J. (2026). FSKD: Monocular Forest Structure Inference via LiDAR-to-RGBI Knowledge Distillation. arXiv preprint arXiv:2604.01766. DOI https://doi.org/10.48550/arXiv.2604.01766
Krüger, N., Uhlig, S., Gardke, S., & Khan, T. (2026). Von Geodaten zu Erkenntnissen – KI-basierte Waldanalyse für den Digitalen Fachzwilling. In 46. Wissenschaftlich-Technische Jahrestagung der DGPF, 25–27. März 2026 in Darmstadt (pp. 315–320). Geschäftsstelle der DGPF. DOI: https://doi.org/10.24407/KXP:1969211504
Khan, T. (2026). TiledAttention: a CUDA Tile SDPA Kernel for PyTorch. In AI on HPC Workshop Proceedings at ISC 2026 (archival track). arXiv:2603.01960. DOI: https://doi.org/10.48550/arXiv.2603.01960
Khan, T., Krebs, J., Gupta, S. K., Renkel, J., Arnold, C., & Nölke, N. (2026). Validation Challenges in Large-Scale Tree Crown Segmentations from Remote Sensing Imagery Using Deep Learning: A Case Study in Germany. In International Conference on Theory and Practice of Digital Libraries (pp. 311-323). Cham: Springer Nature Switzerland. DOI: https://doi.org/10.1007/978-3-032-06136-2_30
Khan, T., Arnold, C., & Grover, H. (2025). DeepTrees: Tree Crown Segmentation and Analysis in Remote Sensing Imagery with PyTorch. Journal of Open Source Software (JOSS). DOI: https://doi.org/10.21105/joss.08056
Khan, T. (2025). Forecasting Smog Events Using ConvLSTM: A Spatio-Temporal Approach for Aerosol Index Prediction in South Asia (Version 1). arXiv. DOI: https://doi.org/10.48550/ARXIV.2508.13891
Khan, T., de Koning, K., Endresen, D., Chala, D., Kusch, E. TwinEco: A Unified Framework for Dynamic Data-Driven Digital Twins in Ecology. Ecological Informatics, 91, 103407. DOI: https://doi.org/10.1016/j.ecoinf.2025.103407
Taubert, F., Rossi, T., Wohner, C., Venier, S., Martinovič, T., Khan, T., ... & Banitz, T. (2024). Prototype Biodiversity Digital Twin: grassland biodiversity dynamics. Research Ideas and Outcomes, 10, e124168. DOI: https://doi.org/10.3897/rio.10.e124168
Khan, T., El-Gabbas, A., Golivets, M., Souza, A., Gordillo, J., Kierans, D., & Kühn, I. (2024). Prototype Biodiversity Digital Twin: Invasive Alien Species. Research Ideas and Outcomes, 10, e124579. DOI: https://doi.org/10.3897/rio.10.e124579
Khan, T. (2023). Designing Data Drive Digital Twin Systems. Workshop 9: European Conference on Ecological Modeling 2023. DOI: https://doi.org/10.5281/zenodo.8313904
Khan, T., Banitz, T., Golivets, M., Grimm, V., Groeneveld, J., Kühn, I., Taubert, F. (2022). Prototyping a Biodiversity Digital Twin. Helmholtz-UFZ Science Days 2022. DOI: https://doi.org/10.5281/zenodo.8079131
Morche, D., Baewert, H., Schuchardt, A., Faust, M., Weber, M., & Khan, T. (2019). Fluvial sediment transport in the proglacial Fagge river, Kaunertal, Austria. Geomorphology of Proglacial Systems (pp. 219-229). Springer, Cham. DOI: https://doi.org/10.1007/978-3-319-94184-4_13
Khan, T. (2017). DC Resistivity: Estimating pore moisture distribution and mapping permafrost content in Kaunertal, Austria. Department of Geosciences. Skidmore College.
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