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Biography

Frank Huebbers joined the Design & Analysis of High Performance ICs Lab of the Electrical Engineering and Computer Science department at Northwestern University, Evanston, Illinois, in September 2005 as a Ph.D. student. For the 2006-2007 academic year he is supported by Argonne National Laboratory Graduate Fellowship. He received his B.S. Computer Engineering degree with Magna Cum Laude and B.S. Electrical Engineering degree with Magna Cum Laude from Northwestern University in June 2005. He also received the International Engineering Consortium's William L. Everitt Student Award of Excellence and was awarded the prestigious Walter P. Murphy Fellowship for graduate studies the same year. For his academic achievements at Northwestern University, Frank was inducted to the national electrical and computer engineering honor society Eta Kappa NU and the national all engineering honor society Tau Beta Pi in January 2004 and February 2004, respectively.

Awards & Honors

Sept. 2006 Argonne National Laboratory Graduate Fellowship with an associated funding of approximately $50,000.
Feb. 2006 Selected by the EECS department of Northwestern University to be nominated for the Intel Foundation Ph.D. Fellowship
Sept. 2005 Recipient of the full Walter P. Murphy Fellowship for graduate studies with an associated stipend of approximately $48,000
Jun. 2005 Recipient of the International Engineering Consortium's William L. Everitt Student Award of Excellence
May 2004 3rd place in the annual McCormick Robot Design Competition
Feb. 2004 Inducted to the national engineering honor society Tau Beta Pi
Jan. 2004 Inducted to the ECE honor society Eta Kappa Nu
May 2001 Recipient of the Langdon Mathematics Award
May 2001 Inducted to the Cum Laude Society
Nov. 2000 Inducted to the Froelicher Society

 

Research Interests

    Frank Huebbers' research interests include:

    * Static Timing Analysis
    * Statistical Timing Analysis
    * Performance corner analysis under process variation
    * Self-tuning circuits for power and delay optimization under variations

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