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Timothy K Chung, PhD

  • Post-Doctoral Associate, Department of Bioengineering

Tim Chung received his BS and PhD from the University of Iowa in biomedical engineering with an emphasis in cardiovascular biomechanics. He is currently a Post-Doctoral Associate in the Vascular Bioengineering Laboratory (VBL) in the University of Pittsburgh department of Bioengineering focusing on computational and experimental projects of cardiovascular diseases that include both abdominal aortic aneurysm and cerebral aneurysms. With advancement in artificial intelligence tools, Dr. Chung has leveraged algorithms to aid with large-scale computational studies towards automation.

Representative Publications

  1. Pichamuthu, J.E., Feroze, R.A., Chung, T.K., Jankowitz, B.T., Vorp, D.A., 2019, “Cerebral Aneurysm Wall Stress After Coiling Depends on Morphology and Coil Packing Density,” J. Biomech. Eng.,
  2. Chung, T. K., da Silva, E. S. & Raghavan, S. M. L. Does elevated wall tension cause aortic aneurysm rupture? Investigation using a subject-specific heterogeneous model. J. Biomech. (2017). doi:10.1016/j.jbiomech.2017.09.041
  3. Nellis, J.R., Chung, T.K., Raghavan, M.L., Turek, J.W. Modeling Outcomes - Modified Aortic Arch Advancement for Neonatal Hypoplastic Arch. American Association of Thoracic Surgeons Aortic Symposium. May 2016. New York, NY. 
  4. Attarian, S., Xiao, S., Chung, T. K., da Silva, E. S., and Raghavan, M. L., 2019, “Investigation of the Observed Rupture Lines in Abdominal Aortic Aneurysms Using Crack Propagation Simulations,” J. Biomech. Eng., 141(7), p. 071004.
  5. Hudson, J., Nagahama, Y., Chung, T.K., Raghavan, M.L., Prout, B., Hasan, D. (2018). Iron Nanoparticle Contrast Enhanced Microwave Imaging for Emergent Stroke: A Pilot Study. Journal of Clinical Neuroscience.   

Research Interests

  1. Computational Biomechanics of cardiovascular disease. Finite element analysis and computational fluid dynamic simulations (CFD).
  2. Experimental Biomechanics to characterize material properties of disease vascular tissues.
  3. Artificial intelligence using machine learning for decision support/analysis and convolutional neural networks for automated segmentation.
  4. Electromechanical devices for precision close-looped feedback pressure or flow measurements.
  5. Image analysis of soft tissues and medical images.

Research Grants

Funding track-records:

  1. Endovascular Orifice Detection Device for Fenestrated EVAR Michael G. Wells Award $10,000 25% effort
  2. ”A Machine Learning Clinical Tool to predict Biomechanical Status of Abdominal Aortic Aneurysm” PI CTSI Biomedical Pilot Award $25,000 50% effort
  3. Aneurysm Prognosis Classifier Co-I Pittsburgh Health Data Alliance UPMC-E Grant $300,000  100% effort