- Designed and debugged low-noise neural-recording hardware, amplifiers, interconnects, and bench instrumentation.
- Simulated electrode current densities and supported 4D acoustoelectric imaging workflows.
- Built tissue-equivalent phantoms and controlled experimental setups for sensing and recording studies.
- Improved signal fidelity through circuit optimization, grounding, shielding, EMI control, DSP, wavelet processing, and MATLAB analysis.
Work evidence
Research Technician
Designed and debugged low-noise neural-recording hardware, 4D acoustoelectric imaging instrumentation, phantoms, and DSP workflows for current-density detection.
EUNIL / University of Arizona · Jan 2016 – Oct 2019
Role focusResearch role focused on non-invasive neural recording, acoustoelectric current-density imaging, low-noise acquisition, analog front-end optimization, experimental phantoms, and signal processing.
Projects1 documented projects
Responsibilities
What this role covered.
Achievements
Evidence from the work.
- Built and optimized front-end hardware, phantoms, and signal-processing workflows for 4D acoustoelectric current-density imaging.
- Presented the non-invasive neural-recording work at BMES 2017 and IEEE IUS 2018.
Technical range
Tools, systems, and engineering areas.
Low-noise acquisitionAnalog sensingAmplifier optimizationEMI controlDSP / waveletsExperimental phantomsAcoustoelectric imagingUltrasoundMATLAB
Related projects