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Minsun Kim, Ph.D.

Assistant Professor

Education and Training

College: Ewha Womans University, Seoul, Korea

Graduate School: University of Washington, Seattle, WA

Selected Publications from a Total of 29:

M Kim, J Kotas, J Rockhill, M H Phillips. A feasibility study of personalized prescription schemes for glioblastoma patients using a proliferation and invasion glioma model. Cancers, 9(5) 51, 2017

F Saberian†, A Ghate, M Kim. Spatiotemporally optimal fractionation in radiotherapy, INFORMS Journals on Computing, 29 (3) 422-437, 2017

F Saberian†, A Ghate, M Kim. A theoretical stochastic control framework for adapting radiotherapy to hypoxia, Physics in Medicine and Biology, 61(19) 7136-7161, 2016

M Kim, M H Phillips. A feasibility study of dynamic adaptive therapy for non-small cell lung cancer, Medical Physics, 43 2153, 2016

M Kim, D Craft, C Orton. Point/Counterpoint: Within the next five years most radiotherapy treatment schedules will be designed using spatiotemporal optimization, Medical Physics, 43 2009, 2016

M Kim, R Stewart, M H Phillips. A feasibility study: Selection of a personalized radiotherapy fractionation schedule using spatiotemporal optimization, Medical Physics, 42 6671, 2015

F Saberian†, A Ghate, M Kim. Optimal fractionation in radiotherapy with multiple normal tissues, Mathematical Medicine and Biology, 33(2) 211-252, 2015

M Kim, A Ghate, M H Phillips. A stochastic control formalism for Dynamic Biologically Conformal Radiation Therapy; European Journal of Operations Research, 219(3) 541-556, 2012

C Holdsworth, M Kim, J Liao, M H Phillips. A hierarchical evolutionary algorithm for multiobjective optimization in IMRT; Medical Physics, 37(9) 4986-4997, 2010

M Kim, A Ghate, M H Phillips. A Markov decision process approach to temporal modulation of dose fractions in radiation therapy planning; Physics in Medicine and Biology (54) 4455-4476 2009

To see more of Dr. Kim’s publications, please click here.

Research Interests

  • Spatiotemporal optimization of radiation treatment planning
  • Multi-modality optimal radiation therapy
  • Interdisciplinary optimal cancer management
  • Treatment and outcome analysis through machine learning