Prasanta Pal, PhD, MS, MPhil, MSc

Senior Research AssociatePrasanta Pal


Post-Doctoral Studies, Yale University School of Medicine, 2012
PhD, Yale University, 2011
MS, MPhil, Yale Unversity 2005
MSc, Indian Institute of Technology, 2003


Focus & Interests


My primary research interest is in quantitative methods—in particular, in feature extraction and classification through the statistical-mathematical modeling of multi-dimensional signals. Previous projects have included modeling the dynamics and pattern of blood flow in the left atrium of the heart in porcine, canine and normal human models, investigating MRI BOLD signal-based hind-limb ischemia models, solving 3D multi-modal image registration problems, quantifying particle dynamics in quasi-one-dimensional systems, etc. Currently, we are working to characterize EEG signals of relevant psychological states by leveraging advances in quantitative biophysical signal processing: source localization/estimation, pattern recognition, machine learning, and under-sampling techniques. I also have extensive experience with programming languages including C++, Java, and HTML. I am now combining these knowledge-bases to monitor large datasets that are generated online, and extract essential features for complex data analysis.


  • 2006-2010 Graduate Student Researcher Fellowship, National Science Foundation
  • 2008 Visiting Researcher Fellowship, Institute of Pure & Applied Mathematics, University of California, Los Angeles
  • 2005 Edward L. Barlow Fellowship, Yale University
  • 2004 Pierre W. Hoge Fellowship, Yale University


Pal, P., O’Hern, C. S., Blawzdziewicz, J. Dufresne, E. R., & Stinchcombe, R. (2008). Minimal model for kinetic arrest. Physical Review E, 78(1), 011111.

Pal, P., Zhang, Z., Lin, B. A., Dione, D., Sinusas, A. J., & Sampath, S. (2012). Flow vortex quantification in the left atrium. Journal of Cardiovascular Magnetic Resonance, 14, 1-2.

Pal, P., Blawzdziewicz, J., O'Hern, C. (2014) Quasi-One Dimensional Models for Glassy Dynamics.