Since Spring 2025, I have worked as an undergraduate research assistant at MSU's Intelligent Edge Microsystems Lab (I-EML), contributing to projects at the intersection of machine learning and embedded systems for human-centered applications. My key responsibilities have included:

• Deploying and benchmarking image recognition models on the NVIDIA Jetson AGX Orin, evaluating how hardware limitations impact real-time inference performance
• Designing and implementing a modular image augmentation pipeline in C++ for efficient data preprocessing, supporting geometric transformations, color adjustments, and noise injection
• Fine-tuning generative image models to produce high-fidelity synthetic datasets, enhancing model generalization in downstream tasks

Throughout Fall 2024 and Spring 2025, I had the opportunity to work with DayDream, a Midwest technology startup focused on the development of XR hardware devices. I worked as part of a mixed hardware/software team, focusing on embedded systems development. Core duties included:

• Implementing firmware in C++ to interface the ESP32-S2 SoC with rotary encoders via GPIOs and with the BMI270 IMU via I2C
• Leveraging FreeRTOS to manage 6 concurrent tasks across 2 cores, optimizing resource utilization and ensuring reliable system performance
• Designing schematics and PCB layouts for a smart AR device using Altium Designer, with a focus on power and communication circuits

During the summer of 2024, I worked at KPIT, an automotive software development company, as part of their middleware team. This team focuses on developing services and tools that allow applications running on electronic control units (ECUs) to access and interact with low-level operating system services. Key responsibilities included:

• Building a formatting tool with Python to assist with implementing MISRA C guidelines for generated C scripts, identifying over 90% of compliance violations and reducing manual review time
• Automating generation of Lauterbach PRACTICE test scripts using Excel and Python, lowering the technical barrier and accelerating script development
• Preparing project documentation and weekly presentations to keep stakeholders informed and gather feedback

Worked as a professorial assistant within the Physical Ultrasonics, Microscopy, and Acoustics Lab (PUMA), contributing to material characterization projects aimed at measuring the physical properties of materials and identifying defects. Key responsibilities included:

• Employing data augmentation and preprocessing techniques to enhance the diversity of time-series datasets using MATLAB
• Utilizing Python to implement algorithms to compute and visualize material properties from ultrasonic signals, achieving results within 5% of accepted values
• Building a preprocessing pipeline to clean and format raw ultrasonic data and prepare it for machine learning applications