I am currently pursuing my master's degree in Electrical and Computer Engineering at Purdue University ECE and I'm particularly passionate about embedded systems and machine learning. I love how embedded systems bridge the gap between hardware and software to enable physical interactive results, while machine learning solves complex problems once thought impossible. If you're curious to explore my past projects, feel free to visit the Projects section of my portfolio, where you'll find detailed information and demonstrations of 13 completed projects, with more exciting ones in progress.
I'll be joining Amazon Robotics as an Embedded Firmware Engineering Co-op this Spring 2025. Previously, I've been a part of the Walt Disney Company as an Attractions Engineering Intern dealing with IoT and Embedded Systems. At Purdue, I've served as a Graduate Teaching Assistant for ECE 362: Microprocessor Systems and Interfacing.
Beyond academics, I find joy in activities such as biking, swimming (I've also previously worked as a lifeguard), cooking, watching movies, playing Valorant/Overwatch, and expressing my creativity through digital art + UI/UX design. To explore my artistic endeavors further, feel free to visit the Memories section, where you can discover more about what I've been up to and even set a new homepage background.
Feel free to explore my projects or get in touch. I’m always happy to connect!
I led the development and deployment of a real-time monitoring and data acquisition system for a Disneyland boat ride, capturing over 16 critical measurements, including location, speed, water temperature, and fuel levels. I integrated LoRa technology and programmed a gateway optimized for continuous data transmission to a central NAS (Network Attached Storage). This setup enabled 24/7 remote monitoring and prepared the data for Machine Learning to predict and prevent engine failures, potentially reducing downtime by 50% and allowing for an additional 23,000 guests annually. Throughout the project, I refined the design through multiple iterations of breadboard prototypes, ultimately finalizing it on a PCB for mass production. Additionally, I proposed the use of Time Division Multiplexing to enhance transmission efficiency, laying the groundwork for further optimization. By the end of my internship, this design was successfully deployed on 22% of the ride, paving the way for full deployment across the entire attraction.
I redesigned and fixed the web portal interface, making it responsive and cross-browser compatible using HTML5, CSS3, and JavaScript—skills I self-learned during the internship and later used to build this personal website and portfolio. I also optimized backend processes by testing CRUD operations and integrating RESTful APIs with Postman. Additionally, I implemented data validation and security measures within a Ruby on Rails environment using Active Record validations. On the side, I evaluated the machine learning curriculum offered at Preface and provided feedback. This experience sparked my interest that eventually led me to pursue more projects in this field over the years.