Research Assistant
Big Data Analytics Lab
Department of Information Systems
University of Maryland Baltimore County
Baltimore, Maryland, U.S.A.
Email: xingyanli@umbc.edu
Lab: ITE 471
Short Biography
Xingyan Li is a Ph.D. candidate in the Department of Information Systems, University of Maryland, Baltimore County (UMBC). Xingyan started her Ph.D. studies in Fall 2021, working as a Research Assistant to the present. Her research interests include foundation models and artificial intelligence for Earth science.
Research Interests
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- Deep Learning
- Foundation Model
- Remote Sensing
Education
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- 2021 ~ Present: Ph.D. in Information Systems, University of Maryland, Baltimore County, U.S.A.
- 2017 ~ 2021: B.S. in Mechanical Engineering, Beijing Jiaotong University, China.
Employment
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- 2021.8 ~ Present Graduate Research Assistant at Big Data Analytics Lab, University of Maryland, Baltimore County, Baltimore, MD, U.S.A.
- 2022.5 ~ Present Treasurer at Chinese Student and Scholar Association (CSSA), University of Maryland, Baltimore County, Baltimore, MD, U.S.A.
Publication
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- Xingyan Li, Jordan A. Caraballo-Vega, Jie Gong, Mark L. Carroll, Jianwu Wang. SPECTRA: Band-Routed Embedding and Parameter-Efficient Cross-Sensor Fine-Tuning of Geospatial Foundation Models. Accepted by 34th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2026), ACM, 2026. [preprint, Open Source Code]
- Xingyan Li, Andrew M. Sayer, Ian T. Carroll, Xin Huang, Jianwu Wang. MT-HCCAR: Multi-Task Deep Learning with Hierarchical Classification and Attention-based Regression for Cloud Property Retrieval. Accepted by 2024 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2024). [preprint, Open Source Code]
- Xingyan Li, Jian Li, Zachary Williams, Xin Huang, Mark Carroll, Jianwu Wang. Enhanced Deep Learning Super-Resolution for Bathymetry Data. Accepted by 2022 IEEE/ACM 9th International Conference on Big Data Computing, Applications and Technologies (BDCAT 2022). [preprint, Open Source Code]
- Danielle Murphy, Kevin Zhang, Caleb Parten, Autumn Sterling, Haoxiang Zhang, Xingyan Li, Jordan Caraballo-Vega, Jie Gong, Mark Carroll, Jianwu Wang. Deep Learning Approaches for Cloud Property Retrieval: Comparing Foundation Model Fine-Tuning with Training from Scratch. In Proceedings of the 2025 IEEE International Conference on Data Mining Workshops (ICDMW 2025), pages 2816-2825, IEEE, 2025. [DOI:10.1109/ICDMW69685.2025.00360, Open Source Code]. Earth Informatics
- Sahara Ali, Uzma Hasan, Xingyan Li, Omar Faruque, Akila Sampath, Yiyi Huang, Md Osman Gani, Jianwu Wang. Causality for Earth Science — A Review on Time-series and Spatiotemporal Causality Methods. [arXiv:2404.05746], 2024. Earth Informatics, Causal AI
- Omar Faruque, Xingyan Li, Md Azim Khan, Homayra Alam, Jianwu Wang. Comparative Evaluation of Causal Discovery and Inference Approaches on Arctic Sea Ice Time Series Data. In Proceedings of the 4th International Workshop on Big Data Analytics for Sustainability (BDA4S 2024) at 2024 IEEE International Conference on Big Data (IEEE Big Data 2024), pages 4588-4597, IEEE, 2024. [DOI:10.1109/BigData62323.2024.10825273, Open Source Code]. Earth Informatics, Causal AI
- Xin Wang, Pei Guo, Xingyan Li, Aryya Gangopadhyay, Carl E. Busart, Jade Freeman and Jianwu Wang. Reproducible and Portable Big Data Analytics in the Cloud. IEEE Transactions on Cloud Computing, vol. 11, no. 3, pages 2966-2982, 1 July-Sept. 2023. DOI:10.1109/TCC.2023.3245081. [Open Access Paper, Open Source Code]. Distributed Analytics
- Sahara Ali, Seraj al Mahmud Mostafa, Xingyan Li, Sara Khanjani, Jianwu Wang, James Foulds, Vandana Janeja. Benchmarking Probabilistic Machine Learning Models for Arctic Sea Ice. In Proceedings of the International Geoscience and Remote Sensing Symposium (IGARSS 2022), pages 4654-4657, DOI:10.1109/IGARSS46834.2022.9883505, IEEE. [Paper Pre-Print, Open Source Code]. Earth Informatics
Awards
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- Technuf Endowed Fellowship, 2024
- Goddard Earth Sciences Technology and Research (GESTAR) II Graduate Fellowship, 2022 – 2023
- Student Travel Award, 2021 IEEE International Conference on Big Data.
- China National Scholarship, 2019, Ministry of Education of the People’s Republic of China