Bohan Chen's Personal Page

Research Interests

Machine learning: Graph learning; Active learning; Transfer learning; Semi-supervised learning; Convolutional neural networks
Image processing: Image segmentation and classification； Hyperspectral image unmixing.
Mathematical Modeling： Optimal control problems; Stochastic process; Point process.

B. Chen, K. Peng, C. Parkinson, A. L. Bertozzi, T. L. Slough, and J. Urpelainen, Modeling illegal logging in Brazil, Research in the Mathematical Sciences 8(29), 2021, preprint version.
Bohan Chen, Pujan Shrestha, Andrea L. Bertozzi, George Mohler, and Frederic Schoenberg, A Novel Point Process Model for COVID-19: Multivariate Recursive Hawkes Process, Modeling and Simulation in Science, Engineering, and Technology, Predicting Pandemics in a Globally Connected World, Volume 1, pp. 141-182, Birkhauser-Springer, New York, USA, Nicola Bellomo and Mark A.J. Chaplain editors.
James Chapman, Bohan Chen, Zheng Tan, Jeff Calder, Kevin Miller, Andrea L. Bertozzi, Novel Batch Active Learning Approach and Its Application on the Synthetic Aperture Radar Datasets, SPIE Defense and Commercial Sensing Conference, 2023.
Bohan Chen, Kevin Miller, Andrea Bertozzi, Jon Schwenk, Graph-based Active Learning for Surface Water and Sediment Detection in Multispectral Images, to appear in IGARSS 2023.
Bohan Chen, Kevin Miller, Andrea L. Bertozzi, and Jon Schwenk, Batch active learning for multispectral and hyperspectral image segmentation using similarity graphs, accepted for publication in Communications on Applied Mathematics and Computation, 2023.
(Submitted to IEEE Transactions on Geoscience and Remote Sensing) Bohan Chen Yifei Lou Andrea L. Bertozzi Member, Jocelyn Chanussot Fellow, Graph-based Active Learning for Nearly Blind Hyperspectral Unmixing, preprint 2023.