Data clustering based on Langevin annealing with a self-consistent potential
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SubjectScience & Technology
Published Version (Please cite this version)10.1090/qam/1521
Publication InfoLafata, K; Zhou, Z; Liu, JG; & Yin, FF (2018). Data clustering based on Langevin annealing with a self-consistent potential. Quarterly of Applied Mathematics, 77(3). pp. 591-613. 10.1090/qam/1521. Retrieved from https://hdl.handle.net/10161/19225.
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Assistant Professor of Radiation Oncology
My research focuses on novel mathematical methods and computational techniques that facilitate the discovery of biomarkers otherwise dormant in biomedical images. By incorporating multi-scale information from both radiological images (i.e., radiomics) and digital pathology images (i.e., pathomics), my work aims to characterize the appearance and behavior of disease across different spatial, temporal, and functional domains. Methodologically, I incorporate various computational and mathemati
Professor of Physics
Professor in Radiation Oncology
Stereotactic radiosurgery, Stereotactic body radiation therapy, treatment planning optimization, knowledge guided radiation therapy, intensity-modulated radiation therapy, image-guided radiation therapy, oncological imaging and informatics
William W. Elliott Assistant Research Professor
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