Specialties
Electronics & Embedded Systems
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Low-voltage electronics
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Microcontrollers: STM32, nRF52, Atmel/Arduino
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Firmware: C, C++
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Software: Python, MATLAB
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Raspberry Pi
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Finite state machines
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Resource-constrained systems
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Device communication: I2C, SPI, UART/serial
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Sensors and actuators
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Deep learning
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Neural network compression
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ONNX Runtime
Instrumentation
R&D Experience
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Biotech instruments
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Semiconductor fabrication
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Microfluidics
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Optoelectronics
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Fluorescence devices
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Hardware-software integration
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PID controls
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High temp/pressure controls
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3D printing/CAD for prototyping
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System modeling
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Systematic and random error
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Monte Carlo models
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Timing issues / Race condition
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Computer vision
CONSULTING SERVICES
DIAGNOSTIC SPRINT
1-2 week sprint to find out what's stalling your hardware AND make sure it never happens again.
INCLUDED
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Onsite full-time investigation during entirety of sprint
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Expert issue tracing through hardware, firmware, and software
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Testing and measurements with an oscilloscope, logic analyzer, multimeter, and JTAG/SWD debugger, as needed to isolate root cause
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Firmware + software scripts for testing, as needed to isolate root cause
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Troubleshooting dashboard with daily updates to monitor progress
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Root cause diagnosis >>> "The problem is caused by X."
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Evidence, data, and logs >>> "Here's proof that the problem is caused by X.
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Corrective actions to resolve problem >>> "Fix the problem by doing Y."
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Procedures and scripts used >>> "Here's how I found out that X is the root cause."
ABOUT ME
Troubleshooting hardware systems can be difficult.
Even with a dozen specialists, you will still struggle to repair them because
system-level issues often arise at the interfaces between specialties.
I'm effective at fixing deep-tech hardware systems because I've researched, designed, built, launched, and troubleshooted complex integrated hardware across many domains: electronics, semiconductors, chemistry, molecular biology, microfluidics, firmware, and software.
Alma Maters
University of Illinois, Urbana-Champaign
M.S. Electrical and Computer Engineering
Master's Thesis: "Fabrication and Testing of Silicon Integrated Nanofluidic Channels for Neurochemical Transport"
Stanford University
B.S. Chemical Engineering
A rigorous ChemE curriculum + research in molecular biology and chemistry labs every summer.
PREVIOUS PROJECTS
I've played a pivotal role in cutting-edge hardware systems across various domains.
Biotech System Architecture
System architect at Illumina, a market leader in biotech. Oversaw design specifications and system integration of optoelectronic and computer vision subsystems for next-gen sequencing platforms.
Neural Implants
Electronic and fluidic testing of microfabricated neural sensors developed by me and others.
Co-authored a 2019 paper for the Transducers/Eurosensors conference.
Device Firmware
Designed device drivers in C/C++ for various microcontrollers across many small electronics projects.
Examples:
STM32 driver for inertial sensor
Smart Wearable with Gesture Detection
Built a rechargeable smart wristband that uses sensor fusion to detect face touching and nail biting. Efficient and battery-powered, requires only 8kB flash and 1kB RAM to run.
Lab Experiment Automation
Repaired automation software codebase for a biotech client's high-throughput fluorescence system, enabling them automate research experiments at scale.
