Bohan Chen

Contact Information

Office: MS 7601

Email: bhchenyz [at] g [dot] ucla [dot] edu

Phone: 424 402 7355

Research Interests

• Machine learning: Graph learning; Active learning; Transfer learning; Semi-supervised learning; Self-supervised learning
• Image processing: Image segmentation and classification； Hyperspectral image unmixing.
• Mathematical Modeling： Optimal control problems; Stochastic process; Point process.
• Knowledge Graph and language models

Recent Papers

• Chen, B., Peng, K., Parkinson, C., Bertozzi, A. L., Slough, T. L., & Urpelainen, J. (2021). Modeling illegal logging in Brazil. Research in the Mathematical Sciences, 8(2), 29.
• Chen, B., Shrestha, P., Bertozzi, A. L., Mohler, G., & Schoenberg, F. (2022). A Novel Point Process Model for COVID-19: Multivariate Recursive Hawkes Process. In Predicting Pandemics in a Globally Connected World, Volume 1: Toward a Multiscale, Multidisciplinary Framework through Modeling and Simulation (pp. 141-182). Cham: Springer International Publishing.
• Chapman, J., Chen, B., Tan, Z., Calder, J., Miller, K., & Bertozzi, A. L. (2023, June). Novel batch active learning approach and its application on the synthetic aperture radar datasets. In Algorithms for Synthetic Aperture Radar Imagery XXX (Vol. 12520, pp. 96-111). SPIE.arXiv preprint version
• Chen, B., Miller, K., Bertozzi, A. L., & Schwenk, J. (2023). Batch Active Learning for Multispectral and Hyperspectral Image Segmentation Using Similarity Graphs. Communications on Applied Mathematics and Computation, 1-21
• Chen, B., Miller, K., Bertozzi, A. L., & Schwenk, J. (2023). Graph-based Active Learning for Surface Water and Sediment Detection in Multispectral Images, IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Pasadena, CA, USA, 2023, pp. 5431-5434, doi: 10.1109/IGARSS52108.2023.10282009..
• Chen, B., Lou, Y., Bertozzi, A. L., & Chanussot, J. (2023). Graph-based Active Learning for Nearly Blind Hyperspectral Unmixing, in IEEE Transactions on Geoscience and Remote Sensing, doi: 10.1109/TGRS.2023.3313933.
• Brown, J., Chen, B., Hardiman-Mostow, H., Weihs, A., Bertozzi, A. L., & Chanussot, J. (2023). Material Identification in Complex Environments: Neural Network Approaches to Hyperspectral Image Analysis, to appear in WHISPERS 2023.

Honors

• (2013) Silver Medal in the 6th Romania Master of Mathematics (RMM).
• (2013) First prize in the 29th Chinese Mathematical Olympiad (CMO).
• (2019) Horn-Moez Prize - for excellence in first-year graduate studies.
• (2021) UC-National Lab In-Residence Graduate Fellowship.
• (2023) Best Student Paper for the Algorithms for Synthetic Aperture Radar Imagery XXX workshop at the 2023 SPIE Defense + Commercial Sensing Conference
• (2023) Session Chair for the session Image Analysis for the Remote Sensing of Water Bodies in IGARSS 2023.