Dr. Jeremy Holleman, Ph.D.

Electrical and Computer Engineering
Associate Professor
EPIC 2333
704-687-8407
Education:
  • Ph.D. University of Washington, 2009
  • M.S. University of Washington, 2006
  • B.S. Georgia Institute of Technology, 1997
Research:
  • Low-power Analog, Mixed-signal, and RF Circuits
  • Bio-medical Interface Design
  • Neuromorphic Computation
  • Machine Learning Hardware
  • Resource-constrained Embedded Systems
Selected Publications:
  •  M. Judy, N.C. Poore, P. Liu, T. Yang, C. Britton, D. S. Bolme, A. K. Mikkilineni, and J. Holleman, “A Digitally Interfaced Analog Correlation Filter System for Object Tracking Applications.” IEEE Transactions on Circuits and Systems I: Regular Papers, Vol. 65, No. 9, pp. 2764–2773, 2018.
  • Hasan, M. Munir, and Jeremy Holleman. ”Implementation of Linear Discriminant Classifier in 130nm Silicon Process.” In Circuits and Systems (ISCAS), 2018 IEEE International Symposium on, pp. 1-5. IEEE, 2018.
  • T. Yang, J. Holleman, “An Ultra-Low-Power Low-Noise CMOS Bio-Potential Amplifier for Neural Recording” IEEE Transactions on Circuits and Systems II, Express Briefs, Vol. 62, No. 10, pp. 927– 931, 2015.
  •  J. Lu, S. Young, I. Arel, J. Holleman, “A 1 TOPS/W Analog Deep Machine-Learning Engine with Floating-Gate Storage in 0.13 μm CMOS” IEEE Journal of Solid-State Circuits , Vol. 50, Issue 1, pp. 270–281, Jan. 2015.
  • S. Young, J. Lu, J. Holleman, I. Arel, “On the Impact of Approximate Computation in an Analog DeSTIN Architecture,” IEEE Transactions on Neural Networks and Machine Learning, Vol.25, Issue 5, pp. 934–946, May 2014.
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