Daniel R. Fuhrmann

Daniel R. Fuhrmann

Department Chair, Electrical and Computer Engineering; Dave House Professor in Computer Engineering
Daniel R. Fuhrmann

Educational Background: He received a BS in Electrical Engineering cum laude in 1979 from Washington University and three degrees from Princeton University: an MA and MS (1982) and a PhD (1984), all in Electrical Engineering and Computer Science.

Academic Experience: Since 2008 he has served as Dave House Professor of Electrical and Computer Engineering and Chair of the Department of Electrical and Computer Engineering at Michigan Technological University. Prior to his tenure at Michigan Tech, he was an Associate Professor of Electrical Engineering (1984-2008) at Washington University, St. Louis, Missouri.

He has been an American Society of Engineering Education (ASEE) summer faculty research fellow with the Naval Underwater Systems Center, in New London, Connecticut; a consultant to the MIT Lincoln Laboratory, in Lexington, Massachusetts; and an ASEE summer faculty fellow with the Air Force Research Laboratory, in Dayton, Ohio. He is a former associate editor for the IEEE Transactions on Signal Processing, and was the General Chairman of the 2003 IEEE Workshop on Statistical Signal Processing. In the 2000-01 academic year, he was a Fulbright Scholar visiting at the Universidad Nacional de La Plata near Buenos Aires, Argentina.

Areas of Expertise:

Statistical signal and image processing, including sensor array signal processing, radar systems, and adaptive sensing

Courses Taught at Michigan Tech:

EE 1110, Essential Math for EE, 23 courses.

EE 2150, Intro to Signal Processing, 2 courses.

EE 3805, Electrical Engineering Project, 1 course.

EE 4805, Electrical Engineering Project, 1 course.

EE 4901, EE Design Project 1, 3 courses.

EE 4910, EE Design Project 2, 3 courses.

EE 5500, Statistical Signal Processing, 3 courses.

EE 5511, Information Theory, 1 course.

EE 5527, Digital Communications, 1 course.

EE 5805, Directed Study in Elec & Comp, 3 courses.

EE 5900, Radar Systems II, 2 courses.

EE 5950, Signals and Systems Seminar, 1 course.

EE 5990, Thesis Research in EE, 5 courses.

EE 5991, Project Research in EE, 4 courses.

EE 6975, Full-Time Doctoral Research, 3 courses.

EE 6990, Doctoral Research, 25 courses.


IEEE Fellow, "for contributions to adaptive radar signal processing,” 2009

Distinguished Lecturer, 2006 IEEE Workshop on Sensor Array and Multichannel Processing, July 2006

Fulbright Scholarship, Universidad National de La Plata, Argentina, 2000-2001

IEEE SSAP-98 Recognition Award, 1998 Outstanding Professor, Eta Kappa Nu (Washington University Chapter),

1988 Schlumberger Foundation Fellowship, 1980-1981

Published Works (Selected):


2009. San Antonio, G., Fuhrmann, D. R., Robey, F. Published MIMO Ambiguity Functions. In J. Li & P. Stoica (Eds.), MIMO Radar Signal Processing.


D. Fuhrmann, J. P.Browning, and M. Rangaswamy, "Signaling Strategies for the Hybrid MIMO Phased Array Radar," IEEE J. Selected Topics in Signal Processing, vol. 4, no. 1, pp. 66-78, February 2010.

D. Fuhrmann, J. P. Browning, M. Rangaswamy, “Adapting a MIMO/Phased-Array Radar Transmit Beampattern to Target Location,” in Proc. 2nd Intl. Workshop on Cognitive Information Processing, Elba Island, Italy, June 2010.

D. Fuhrmann, “Steady-State Behavior of Discrete-Time Kalman Filter with Online Measurement Selection,” in Proc. Workshop on Sensor Signal and Information Processing (SenSIP), Sedona, AZ, May 2008.

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