2024 Investiture Information

Kofi M. Odame

Associate Professor of Engineering

Program Area Lead: Electrical & Computer Engineering


Professor Odame is an expert in analog integrated circuits for nonlinear signal processing. His research group is developing ultra low power circuits for implantable and wearable biomedical devices and next generation image sensors. For more information visit the Analog Lab.

Research Interests

Analog integrated circuits; low power sensor interfaces; nonlinear signal processing


  • BSc, Electrical and Computer Engineering, Cornell University 2002
  • MSc, Electrical and Computer Engineering, Cornell University 2004
  • PhD, Electrical and Computer Engineering, Georgia Institute of Technology 2008


  • Jeff Crowe '78 Grand Prize, 2019 Dartmouth Entrepreneurs Forum
  • Neukom/IQBS CompX Faculty Grant (2011–2012)
  • Analog Devices Career Development Assistant Professor of Engineering (2008–2012)
  • Georgia Institute of Technology Tower Award (2008)
  • Cornell Institute for African Development Fellowship (2002–2003)
  • Cornell International Scholars and Students Award (1998–2002)

Professional Activities

  • Senior Member, IEEE
  • Venture Advisor, TandemLaunch
  • Standing Member, NIH/CSR BCHI Study Section (7/2019–9/2020)
  • Standing Member, NIH/CSR Clinical Informatics and Digital Health Study Section (9/2020–6/2025)

Research Projects

  • Cardiac output monitoring

    Cardiac output monitoring

    We are developing a device for continuous, non-invasive monitoring of a patient's cardiac hemodynamic status, allowing for physician intervention before the clinical symptoms of decompensation are observed, and potentially avoiding hospitalization.

  • Asthma symptom monitoring

    Asthma symptom monitoring

    Our asthma symptom monitoring solution is a wearable device that automatically detects and tracks cough, wheezing severity, lung function and inhaler use. The device provides objective information about the patient’s level of asthma control and level of compliance with the asthma plan.

  • Custom ICs for Prostate imaging

    Custom ICs for Prostate imaging

    We are providing advanced integrated circuits (ICs) for sensing to Professor Ryan Halter, who is combining them with transrectal electrical impedance tomography and electrical impedance sensing biopsy devices to improve the accuracy of ultrasound-guided prostate biopsy procedures.

  • Electrical impedance tomography in pulmonary and cardiac applications

    Electrical impedance tomography in pulmonary and cardiac applications

    The most common application, so far, of electrical impedance tomography (EIT) has been pulmonary monitoring of patients. In particular, we have been pursuing EIT for cardiac output monitoring (a related application) and EIT as a surrogate for pulmonary function tests.

Selected Publications

  • A Power Adaptive, 1.22 pW/Hz, 10 MHz Read-Out Front-End for Bio-Impedance Measurement, M. Takhti and K. Odame, in IEEE Transactions on Biomedical Circuits and Systems, vol. 13, no. 4, p. 725–734, Aug. 2019.
  • An Optimized Recurrent Unit For Ultra-Low-Power Keyword Spotting, J. Amoh, K. Odame, in Journal Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technology, vol. 3, no. 2, p. 36, 2019.
  • Deep Neural Networks For Identifying Cough Sounds, J. Amoh, K. Odame, in IEEE Transactions on Biomedical Circuits and Systems, vol. 10, no. 5, p. 1003–1011, 2016.
  • A Bandpass Filter With Inherent Gain Adaptation for Hearing Applications, K. Odame, D.V. Anderson, P. Hasler, in IEEE Transactions on Circuits and Systems I, vol. 55, no. 3, p. 786–795, 2008.
  • An Efficient Oscillator Design Based on OTA Nonlinearity, K. Odame and P. Hasler, in Proc. of IEEE International Symposium on Circuits and Systems, p. 921–924, 2007.
  • The Translinear Principle: A General Framework for Implementing Chaotic Oscillators, K. Odame and B. Minch, in International Journal of Bifurcation and Chaos, vol. 15, no. 8, p. 2559–2568, 2005.


  • Acoustic sensor with an acoustic object detector for reducing power consumption in front-end circuit | 9,964,433
  • Hearing-aid noise reduction circuitry with neural feedback to improve speech comprehension | 9,906,872
  • Electroencephalography monitoring device having a self-adaptive analog-to-digital converter | 8,655,438


  • ENGS 126: Analog Integrated Circuit Design
  • ENGS 129: Biomedical Circuits and Systems
  • ENGS 32: Electronics: Introduction to Linear and Digital Circuits


Graduate Student Research: Brain-Controlled Hearing Aid

Graduate Student Research: Wearable Asthma Monitor

In the News

Child-centered innovation
Nov 15, 2016