About

I'm passionate engineer who is always curious about things around the world. I enjoy learning and doing what I enjoy. I am ready to contribute to change and make innovations to the world!

This summer, I worked at Micron Technology, developing qualification stress and characterization flows for GDDR7. I also worked as Data Visualization Developer at Raytheon, where I built a real-time RF data collection system with Raspberry Pi 4, using Python and machine learning skills.

In my spare time, I like learning new languages, new technologies, leetcoding, making songs, and weightlifting!

Education

Master of Science in Electrical and Computer Engineering

University of Utah

December 2025

Focused on machine learning, VLSI, and software development. Completed coursework in Machine Learning, Deep Learning Imaging, Data Mining, Digital Image Processing, Computer Vision, Digital VLSI Design, and Computer Architecture. Taught 'Fundamentals of Robotics and Cyberphysical Systems' class and 'Technical Writing and Communication' class.

VLSI / SemiconductorSoftware DevelopmentMachine LearningComputer VisionRobotics

Bachelor of Science in Computer Engineering

University of Utah

May 2024

Focused on embedded systems, data management, and software development. Completed coursework in Embedded Systems Design, Robotics, Digital System Design, and Database Systems.

Embedded SystemsDatabase ManagementNetwork Systems

Experience

High Performance Memory Reliability Test Engineer

Micron Technology

May 2025–August 2025

Developed and optimized qualification stress and characterization flows for GDDR7 DRAM on ATE using a proprietary language. Debugged timing and logic issues encountered during flow development for JEDEC compliance. Built a Python CLI tool for retrieving wafer test logs by ID and date range. Collaborated with cross-functional engineers to diagnose and resolve signal integrity and reliability failures.

PythonCLITestingSemiconductorATE

Data Visualization Developer

Raytheon

August 2023–May 2024

Built a Python-based data visualization platform to map RF signal strengths from distributed Raspberry Pi 4 systems.Designed a multi-threaded real-time monitoring system for GPS and data transmission. Enhanced visualization usability with configurable real-time streaming, visibility filters, and save/load states.

PythonMap VisualizationMachine LearningRadio FrequencyNetworking Protocols

Projects

DES Encryption/Decryption Engine →

Led a 3-member team in designing a VLSI-based ASIC DES encryption/decryption processor featuring a 64-bit datapath and 16-round Feistel structure for secure data transmission. Designed the RTL architecture in Verilog using Modelsim and implemented the ASIC with CAD tools for synthesis, placement, and routing in a complete chip design flow. Verified top-level modules (key generator, left/right data registers, SPI interface) through RTL, gate-level, and post-layout simulations to evaluate timing, area, and functionality across the circuit flow.

SoC DesignVerilogCAD

Pneumonia Detector →

Developed and trained convolutional neural networks (CNNs) on the ChestXray14 dataset using PyTorch, NumPy, and pandas, achieving 97% accuracy for pneumonia classification under a 500k-parameter constraint. Evaluated model performance with precision, recall, and F1-score, optimizing hyperparameters and experimenting with multiple CNN architectures to balance accuracy and computational efficiency.

PythonNumPyPandasTensorFlowMachine Learning

Auto Plant Hydration System →

Developed a distributed IoT system using STM32F072 and ESP32-S3 microcontrollers programmed in C, coordinating soil moisture sensors, valves, and pump actuator via UART communication. Designed a custom PCB and deployed a Docker-based monitoring server with InfluxDB and Grafana for real-time telemetry and remote control over Wi-Fi.

CNetwork ProtocolsPCB DesignInfluxDBGrafana