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Vaishnavi Ranganathan

PhD candidate

(UWIN Graduate Fellow)

Resume

Sensor Systems Lab

Electrical Engineering

University of Washington, Seattle

vnattar@uw.edu


Design Software

Solid Works, AutoCAD, Altium, Eagle, Cadence, HFSS, Encounter, COMSOL, L-Edit, GNU Radio, Labview

Programming

MCU, FPGA, Verilog, C/C++, Python, Matlab, Mathematica,

Instrumentation

IC Station, Wire bonding, SEM imaging, Semiconductor characterization, Clean-100 fabrication


Technical expertise

PCB design, Wireless power transfer, RFID communication, MEMS/NEMS, low-power IoT design, Biomedical signal analysis and low-power FPGA

Software defined radio, Machine learning

IC fabrication, Biocompatible packaging



About Me

PhD / UW EE
Sept 2013 - Current

I am a Ph.D. Student in the Sensor Systems Lab at the University of Washington, Seattle. My research interests involve developing low-power embedded devices for monitoring physiological parameters and IoT applications. Specifically, I have worked on HF and UHF wireless power harvesting, ultra-low-power wireless communication and computation for implantable and wearable devices.

Power Aware Wireless Neural Interface
Power Aware Wireless Neural Interface

My primary research involves developing a closed loop neural interface for rehabilitation and reanimation of paralyzed limbs in patients with spinal cord injury. The images above are a summary of the Brain-Computer-Sinal Interface (BCSI) system that I am developing. They provide a system block diagram and functional illustration along with the devices that I have developed towards this. The system is designed to stimulate in the spinal cord based on intentions decoded from neural signals recorded in the brain. As a part of my research, I have been integrating the typical benchtop equiment that are used for neural interface into small circuit boards that are implantable. The key features of this system include wireless power transfer, ultralow-power communication and closed-loop neural recording and stimulation. The stimulation is controlled by on-device decoding from Local Field Potentials (LFP) recorded in the motor cortex. The goal of this system is also to accommodate for variation in power availabile from a wireless power transfer link. I am currently developing the LFP processing on FPGA and a power-aware goldilocks control loop that periodically assigns a computational complexity based on power available from the wireless link. I was awarded a graduate innovation fellowship from the Washington Research Foundation to support my work on the power-aware neural interface.

Apart form this I have been wokring on other interesting topics including energy harvesting from RF and NFC for wearable sensors, wireless power transfer using phased array systems and low-overhead echolocation for localizing receivers in a HF phased array power transfer system. I have also developed an FPGA implementation of the RFID EPC Gen2 protocol for performing block read and write with an Impinj R1000 RFID reader. This design was implemented for a 65nm CMOS IC development. Email me for the link to the FPGA library git repository.


MS / CWRU EECS
Aug 2011 - Jul 2013

I received my Masters in EECS from Case Western Reserve University (CWRU), Cleveland OH. As a part of the Nanoscape Lab I pursued research on NEMS for harsh environment, high-speed switching and non-volatile memory. In addition, I was involved in the development of a dual purpose implantable ultrasonic assembly for detecting recurrent cancer, and design and analysis of a nanochannel for fast DNA base sequencing.


B.Tech /ASE India
Aug 2007 - July 2011

I received my B.Tech in Electronics and Instrumentation Engineering from Amrita School of Engineering, Coimbatore, India and was a research student at the Indian Institute of Technology, Bombay during my senior year in B.Tech. As an undergraduate I gained experience in robotics, MEMS and was a member of SAE India.


Work Experience

Microsoft Research / Medical Devices Group, Redmond
June 2016 - August 2016, September 2017 - May 2018
Passive Wireless Sensor Interface
Passive Wireless Sensor Interface system

As a summer intern in the Medical Devices Group at MSR in 2016 I developed a fully-analog wearable passive sensor for continuous physiological monitoring. I returned to work with the group in late 2017 to work on further integration of the system to an existing sensor framework and to validate it with testing. The vision for this work is to develop a bandaid-like device that can be worn on the body for bed-side monitoring of heart rate, breathing rate, temperature and audio. The device was also designed for sensor input flexibility as a plug-and-play platform that interfaces with different types of sensors. The prototype device performs sensing and communicates sensed signals at 35 to 160 micro Watts power budget (harvested from a 915MHz radio frequency continuous wave singal).