Computational Physiology and Clinical Inference Group
Prof. George Verghese and Prof. Thomas Heldt


Our research brings together concepts from signal processing, systems and control theory, modeling, and estimation to address questions in clinical medicine and physiology. Our students usually complete a core curriculum in signal and systems, and in quantitative physiology. At the undergraduate level, the key subjects for us are the following two (and we are often involved in teaching them):

6.011 Introduction to Communication, Control, and Signal Processing
Examines signals, systems and inference as unifying themes in communication, control and signal processing. Topics include input-output and state-space models of linear systems driven by deterministic and random signals; time- and transform-domain representations in discrete and continuous time; group delay. State feedback and observers. Probabilistic models; stochastic processes, correlation functions, power spectra, spectral factorization. Least-mean square error estimation; Wiener filtering. Hypothesis testing; detection; matched filters.

6.022J Quantitative Systems Physiology
Application of the principles of energy and mass flow to major human organ systems. Mechanisms of regulation and homeostasis. Anatomical, physiological and pathophysiological features of the cardiovascular, respiratory and renal systems. Systems, features and devices that are most illuminated by the methods of physical sciences. Laboratory work includes some animal studies. 2 Engineering Design Points.