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Jared Weis

Research Assistant Professor of Biomedical Engineering

Biomedical Engineering

Intellectual Neighborhoods

Research Focus

The overall theme of my research is concentrated in applying computational modeling and non-invasive imaging methodologies to explore the nature of soft-tissue mechanics in cancer and development, with an emphasis on driving clinical therapeutic interventions. My research focuses on the multi-disciplinary study of the multi-scale influences of mechanics in cancer progression and response to therapy, involving the development and validation of image-based mathematical modeling approaches to evaluate quantitative parameterization of cancer properties and predict the response to therapy.

Current Projects

  1. Using Mechanical Stiffness to Evaluate and Predict Breast Cancer Therapeutic Response
  2. Image-Based Biophysical Modeling to Predict the Response of Breast Cancer to Neoadjuvant Therapy
  3. Image-Based Biophysical Modeling to Predict Tumor Recurrence from Pseudo-Progression Following Stereotactic Radiosurgery for Intracranial Metastasis

Selected Publications

  • Weis, J.A., Miga, M.I., Yankeelov, T.E. Three-dimensional image-based mechanical modeling for predicting the response of breast cancer to neoadjuvant therapy. Computer Methods in Applied Mechanics and Engineering. 2017 Feb;314:494-512.
  • Yankeelov T.E., Popel A.S., An G., Ribba B., Weis J.A., Saut O., Ye K., Genin G.M., Vicini P. Multi-scale modeling in clinical oncology: opportunities and barriers to success. annals of biomedical engineering. Annals of Biomedical Engineering. 2016 Sept;44(9):2626-41.
  • Weis, J.A., Flint, K.M., Sanchez, V., Yankeelov, T.E., Miga, M.I. Assessing the accuracy and reproducibility of modality independent elastography in a murine model of breast cancer. Journal of Medical Imaging. 2015 Jul;2(3):036001.
  • Weis, J.A., Miga, M.I., Li, X., Arlinghaus, L.R., Abramson, V., Chakravarthy, A.B., Farley, J., Pendyala, P., Yankeelov, T.E. Predicting the response of breast cancer to neoadjuvant chemotherapy using a mechanically coupled reaction-diffusion model. Cancer Research. 2015 Nov;75(22):4697-4707.
  • Weis, J.A., Miga, M.I., Arlinghaus, L.R., Li, X., Chakravarthy, A.B., Abramson, V., Farley, J., Yankeelov, T.E. A mechanically coupled reaction-diffusion model for predicting the response of breast tumors to neoadjuvant chemotherapy. Physics in Medicine and Biology. 2013 Sept;58(17):5851-5866.
  • Yankeelov, T.E., Atuegwu, N., Hormuth, D., Weis, J.A., Barnes, S.L., Miga, M.I., Quaranta, V. Clinically relevant mathematical modeling of tumor growth and treatment response. Science Translational Medicine. 2013 May;5(187):187ps9.