Faculty Connections
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Full-Text Search

Jeremy Holleman

Electrical & Computer Engineering
bio-medical interface design
low-power analog circuits
machine learning
machine learning hardware
mixed-signal circuits
neuromorphic computation
resource-constrained embedded systems
rf circuits
Related People
Arun Ravindran
Constantin Bunescu
Douglas Markant
Elaine Luo
Maciej Noras
David Wilson
Yinghao Pan
Mirsad Hadzikadic
Wenwen Dou
Benjamin Radford
Wenhao Luo
Ahmed Arafa
Srijan Das
Jianping Fan
Electrical and Computer Engineering
Associate Professor
EPIC 2333
704-687-8407
jhollem3@uncc.edu
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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