• Managed a 4-person engineering team, managing timelines and design reviews to ensure on-time hardware and firmware integration

• Led schematic capture and board layout of a mixed-signal PCB in Altium Designer, integrating battery charging and an I2C display for real-time SpO2, heart rate, and temperature readings

• Designed a custom analog front-end, implementing a precision transimpedance amplifier, 3rd-order Sallen-Key filter, and 380x gain stage to process nano-amp photodiode signals

• Engineered a precision bandgap reference and PTAT circuit for LED thermal drift compensation, achieving 0.5°C accuracy and validating a constant voltage within 1mV over a 20°C to 50°C sweep

• Developed embedded C/C++ firmware, utilizing DSP and an adaptive peak detection algorithm to achieve SpO2 accuracy within 2% and heart rate tracking within 3 bpm

Electrolyte imbalances are critical factors in major organ failure, contributing to an average of 13 deaths daily in the United States. Thus, developing an accurate, real-time in-body biochemical sensing system is vital for effective disease management and early organ failure detection. Current methodologies' limitations are: 1) blood draws are time-consuming, one-time measurements; 2) wearable biosensors have detection delays with limited sensing capabilities; and 3) current implantables are bulky, battery-powered, with limited selectivity. We are developing a battery-free, implantable biochemical sensing system designed for localized organ monitoring. The system includes a flexible wearable paired with a passive implantable that uses inductive coupling for wireless power transfer and data transmission. We were previously challenged with low sensitivity, poor sensor performance, and vulnerability to distance-induced distortions on the signal. Here, we introduce an optimized dual-pair system that accurately measures the sensor response by removing baseline variations caused by distance distortions. Our approach leverages a reference implantable to reject environmental variations, thereby enabling isolation of the sensor response. The implantable was redesigned to minimize sensor noise, achieving a 4x improvement in signal-to-noise ratio. Mathematically informed impedance matching enhanced the system's sensitivity by 340%, and the wearable was further miniaturized by 32%. Mathematical modeling paired with a distance rejection algorithm provided accurate vertical distance prediction and enabled the back-calculation of the analyte concentration from the sensor. This work validates a low-noise, high-sensitivity wireless sensing system that resolves a critical barrier by removing environmental variations from sensor readings, enabling accurate in-body concentration determination.

• Engineered a custom hardware testing system for triboelectric nanogenerators, scaling the maximum measurable voltage by 4000%

• Led analog circuit design and board assembly of high-voltage buffers and transimpedance amplifiers for micro-amp signals processing

• Conducted electrical characterization and modeling of display actuators in liquid crystal and electrophoretic display technologies

• Automated 100+ mechanical actuation experiments using robotic test equipment, analyzing datasets in Python and Excel to optimize power transfer efficiency and system performance

• Engineered and assembled a 27 MHz wireless RF communication system as part of the UCLA IEEE WRAP project, managing the hardware lifecycle from initial design to final board integration

• Designed and optimized BJT-based RF circuits, including oscillators, amplifiers, buffers, filters, and mixers, to ensure efficient and reliable signal transmission and reception

• Executed schematic capture and board layout for custom RF transmitter and receiver PCBs in KiCad, validating theoretical circuit performance through LTspice and MATLAB system simulations

• Conducted physical hardware integration and bench testing utilizing oscilloscopes and spectrum analyzers to fine-tune signal integrity and optimize overall system performance

• Designed and assembled a custom mixed-signal PCB featuring a stereo audio amplifier integrated with a real-time 7-band frequency visualizer

• Engineered the analog audio system utilizing operational amplifiers and stereo buffers to implement user-controlled volume, gain, and bass boost functionality for enhanced audio performance

• Programmed embedded C++ firmware on a microcontroller interfaced with a hardware frequency analyzer to process analog audio signals and render the spectrum on an OLED display

• Designed and prototyped an Arduino-based access control system, integrating RFID, ultrasonic sensors, and a membrane keypad for real-time intrusion detection

• Developed embedded C++ firmware to drive an OLED display, creating a menu interface for users to configure security settings and manage access credentials

• Interfaced multiple analog and digital peripherals, linking sensor inputs directly to RGB LEDs and buzzers for immediate visual and auditory alarm feedback