Integrated Computational Electronics Laboratory (ICE)

Is that layout on those tiles?

Welcome to the ICE Laboratory Site @ GT

The lab has two current focus directions:

  • Programmable and configurable, analog and digital, circuits, signal processing, algorithms, and systems
  • Neuromorphic Engineering
From these two areas of focus, we research signal processing, analog and digital integrated circuits and systems design, computational neuroscience, nonlinear dynamics, and CMOS device physics.

Lead Professor: Dr. Jennifer Hasler

Topically Organized Publications

Overview writings

Recent Courses Taught

Potential Senior Design / Graduate Special Problems directions

Recent article on the importance of the Faculty--Ph.D. Student Mentoring Relationship (GT press: April 11, 2016)

Programmability and Configurability

Neuromorphic Computation

We want to have systems based on neuroscience, to perform biological like tasks, including robotics, and thereby contribute to neuroscience understanding.

References :
[1] S. George, S. Kim, S. Shah, et. al, "A Programmable and Configurable Mixed-Mode FPAA SOC,” IEEE Transactions on VLSI, 2016.
[2] M. Collins, J. Hasler, and S. George, "An Open-Source Toolset Enabling Analog–Digital–Software Codesign," Journal of Low Power Electronics Applications, January 2016.
[3] J. Hasler, S. Kim, S. Shah, F. Adil, M. Collins, S. Koziol, and S. Nease, "Transforming Mixed-Signal Circuits Class through SoC FPAA IC, PCB, and Toolset," European Workshop on Microelectronics Education, Southampton, May 2016.
[4] M. Collins, J. Hasler, and S. Shah, "An approach to using RASP tools in analog systems education," FIE , October 2016.
[5] J. Hasler, S. Shah, S. Kim, I. Lal, and M. Collins, "Remote FPAA System Setup Enabling Wide Accessibility of Configurable devices," Journal of Low Power Electronics Applications, June 2016.
[6] S. Kim, J. Hasler, and S. George, "Integrated Floating-Gate Programming Environment for System-Level Ics," IEEE Transactions on VLSI , 2016.
[7] J. Hasler, S. Shah, S. Kim, I. K. Lal, and M. Collins, "Remote System Setup Using Large-Scale Field Programmable Analog Arrays (FPAA) to Enabling Wide Accessibility of Configurable Devices," Journal of Low Power Electroncs Applicatyyions, vol. 6, no. 14, 2016, pp. 1-17.
[8] J. Hasler, S. Kim, and F. Adil, "Scaling Floating-Gate Devices Predicting Behavior for Programmable and Configurable Circuits and Systems," Journal of Low Power Electroncs Applicatyyions, vol. 6, no. 13, 2016, pp. 1-19.
[9] S. Shah, H. Treyin, O. T. Inan, and J. Hasler, “Reconfigurable analog classifier for knee-joint rehabilitation,” IEEE EMBC , August 2016.
[10] S. Shah, C. N. Teague, O. T. Inan, and J. Hasler, “A proof-of-concept classifier for acoustic signals from the knee joint on an FPAA,” IEEE SENSORS, October 2016.
[11] A. Natarajan and J. Hasler, ``Modeling, simulation and implementation of circuit elements in an open-source tool set on the FPAA,'' Analog Integrated Circiuits and Signal Processing, January 2017.
[12] S. Shah and J. Hasler, IEEE CASI, 2017.
[13] Electronic Product Magazine, March 21, 2016. "New analog chip uses 1,000 times less electrical power (and can be built a hundred times smaller) than comparable digital devices"
References :
[1] J. Hasler, H. B. Marr, "Finding a Roadmap to achieve Large Neuromorphic Hardware Systems," Frontiers in Neuroscience, vol. 7, no. 118, September 2013. pp. 1-29. DOI=10.3389/fnins.2013.00118
[6] J. Hasler, “Opportunities in Physical Computing driven by Analog Realization,” IEEE IC Rebooting Computing , San Deigo, October 2016.
[7] H. B. Marr and J. Hasler, "Compiling probabilistic, bio-inspired circuits on a field programmable analog array," Frontiers in Neuroscience, 2015. pp. 1-9.