Roman Kuc Director of the Intelligent Sensors Laboratory Professor of Electrical Engineering Director of Educational Affairs in Engineering

The Intelligent Sensors Laboratory explores digital signal processing algorithms for extracting information from sensor data by employing physical principles and dynamic constraints. Problems are approached using analysis, simulations and processing of real data. Biological sensing systems, such as echolocating bats and dolphins, are explored and insights are applied to task-oriented problems in robotics and to devices to aid the disabled.

Recent projects include an intelligent wheel chair for use by the blind; a biologically-motivated sonar system for tracking objects in two and three dimensions; a computer model of the bat^Òs sensorimotor system for prey tracking and capture with sonar; an algorithm to image the source current distribution inside the body from magnetic measurements using SQUID detectors; a sonar acoustic vision system for recognizing objects by their acoustic signatures (The system can differentiate head from tail side of coin) and Hidden Markov Models that determine the characteristics of potassium channels in the cell membrane.

1. R. Kuc. Biomimetic sonar locates and recognizes objects. IEEE J. Oceanic Engineering, 22(4), 616-624, 1997.
2. L. Venkataramanan, L.J. Walsh, R. Kuc, and F. J. Sigworth.  Identification of Hidden Markov Models for ion channel currents --  Part I: Colored background noise. IEEE Trans. Signal Processing, 46(7) 1901-1915, 1998.
3. L. Venkataramanan, R. Kuc, and F. J. Sigworth. Identification of Hidden Markov Models for ion channel currents -- Part II: State-dependent excess noise. IEEE Trans. Signal Processing 46(7) 1916-1929, 1998.
4. L. Venkataramanan, R. Kuc, and F. J. Sigworth. Identification of Hidden Markov Models for ion channel currents -- Part III: Band-limited, sampled data. IEEE Trans. Signal Processing 48(2) 376-385, 2000.
5. R. Mueller and R. Kuc. Foliage echoes: A probe into the  ecological acoustics of bat echolocation. J. Acoust. Soc. America, 108(2), 836-845, 2000.
6. R.Kuc. Improving object classification with biomimetic sonar. J. Acoust. Soc. America, 110(3), 1263-1236, 2001.
7. R. Kuc. Transforming echoes into pseudo-action potentials for  classifying plants. J. Acoust. Soc. America, 110(4), 2198-2206, 2001.
8. R. Kuc. Pseudoamplitude scan sonar maps. IEEE Transaction on  Robotics and Automation, 17(5), 767-770, 2001.
9. R. Kuc. Teaching the Nonscience major: EE101 - The Digital Information Age. IEEE Transactions on Education, 44(2), 158-164, 2001.