Connie Liu

Hello! I'm Kangni (Connie) Liu, a Ph.D. student in analog/RF IC design with 5+ years of hands-on experience in CMOS circuit development, system-level verification, and tapeout-ready block design (TSMC 180nm). I am expected to graduate in December 2025 and I am looking for hardware engineer positions.

Kangni Liu

Technical Skills

  • CAD Tools: Cadence, Altium Designer
  • Programming Languages: Verilog, Python, C++
  • Highlights: Analog Circuit, ASIC, CMOS, Layout Design, OPAMP, OTA, Circuit Design, SPI, I2C, PCB, ADC, DAC

Education

  • Ph.D. in Electrical and Electronic Engineering University of Pittsburgh, Pittsburgh, PA, USA August 2019 - December 2025 Advisors: Rajkumar Kubendran (Homepage)

  • B.S. in Automation Beijing Institute of Technology, Beijing, China September 2015 - June 2019

Research Experience

Research Assistant | University of Pittsburgh | January 2021 - Present

Programmable Pulse Generator for Pain Relief

  • Designed a wearable Pulse Generator (PG) device for analgesic nerve stimulation using custom ASIC. The PG measures the impedance of the injected electrode and adjusts the current pulse to slow the degradation of the electrode.
  • Designed a current steering DAC for current pulse generation. The DAC could generate ±4mA current pulses with 15.6μA error and linearity mismatch ≤1%.
  • Designed a digital circuit system for SPI communication. A Finite State Machine (FSM) is designed to decide PG work operation. 16 internal registers, each 8-bit wide, are used to store the pulse period.
  • Implemented the PG using TSMC 180nm technology. Designed a PCB for PG using Altium Designer.
  • The system peak power is 26.4mW. A vitro study was conducted and the PG extends the electrode life from 30 hours to 80+ hours.

Bio-mimetic Neuron Network on Hardware with Coupled Rhythms

  • Design and implement the analog circuit for a 5-neuron network with non-linear multi-timescale neuron model. Applied the network to Central Pattern Generator (CPG) to control robot.
  • Constructed the neuron with a custom-designed operational transconductance amplifier (OTA) using Cadence Virtuoso. The Neuron network is verified in both CALIBRE DRC and LVS.
  • The network was implemented on a 2mm × 1mm chip using TSMC 180nm technology. The chip is soldered on a custom printed circuit board (PCB).
  • Tested the neuron network chip with the Verilog program. Performed post-layout extraction and verification to ensure signal integrity in a multi-neuron network, achieving 200 – 1000Hz spike frequencies. The waveform generated by inhibitory rhythm is applied to a dog robot and make it jump.

Nonlinear Mixed-feedback Neuron Chip Design and Test

  • Architected and implemented a mixed-feedback CMOS circuit using TSMC 180nm.
  • Tested the circuit with a custom-designed PCB. The chip is controlled by FPGA development board. The FPGA is programmed in Xilinx Vivado using Verilog RTL code.
  • The tested neuron circuits generate biomimetic behaviors with powers of 31.4μW. It shows the potential of large integrated neuron network hardware.

Work Experience

  • Graduate Research Assistant University of Pittsburgh, Pittsburgh, PA, USA January 2021 - Present

Contact Information

Publications

  1. K. Liu, S. Hashemkhani, J. Rubin and R. Kubendran, “BioNN: Bio-Mimetic Neural Networks on Hardware Using Nonlinear Multi-Timescale Mixed-Feedback Control for Neuromodulatory Bursting Rhythms,” in IEEE Journal on Emerging and Selected Topics in Circuits and Systems, vol. 13, no. 4, pp. 914-926, Dec. 2023, doi: 10.1109/JETCAS.2023.3330084.

  2. K. Liu, S. Hashemkhani, J. Rubin and R. Kubendran, “Neuromorphic Networks using Nonlinear Mixed-feedback Multi-timescale Bio-mimetic Neurons,” 2023 IEEE International Symposium on Circuits and Systems (ISCAS), Monterey, CA, USA, 2023, pp. 1-5, doi: 10.1109/ISCAS46773.2023.10182201.

  3. K. Liu, A. Gormaley, K. Woeppel, T. Emerick, X. T. Cui and R. Kubendran, “Programmable Pulse Generator for Pain Relief Stimulation using Bioresorbable Electrodes,” 2023 IEEE Biomedical Circuits and Systems Conference (BioCAS), Toronto, ON, Canada, 2023, pp. 1-5, doi: 10.1109/BioCAS58349.2023.10389016. [PDF]

  4. K. Liu, G. Chen, K. Woeppel, X. T. Cui, and R. Kubendran, “Active Impedance Monitoring in Programmable Stimulator for Closed-Loop Charge Balancing,” submitted.

  5. G. Chen, Z.-H. Mao, M. Sun, K. Liu, and W. Jia, “Shape-preserving generation of food images for automatic dietary assessment,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Seattle, WA, USA, pp. 3721-3731, June 2024.

  6. G. Chen, M. Sun, Z.-H. Mao, K. Liu, and W. Jia, “Mechanisms of generative image-to-image translation networks,” submitted, Nov 2024.