Education
I am currently attending the University of Illinois at Urbana-Champaign with a major in Computer Engineering. I plan to graduate in December 2024 with my bachelors degree. Some of the relevant coursework I have taken are Artificial Intelligence, IoT and Cognitive Computing, Distributed Systems, Computer Systems Engineering, and Introduction to Algorithms and Models of Computation.
Hobbies
I enjoy taking photos occasionally either on my phone or my Nikon D5100 and then editing them in lightroom. Below is a linked photo if you want to see more. Additionally I enjoy to play pickleball with my friends.
Work Experience
I interned for 2 summers and 2 school years at the Brunswick Corporation, a marine recreation company. While there, I worked in an Agile environment on many software projects, mainly in Python, that focused on internal tools and QA regarding a mobile app for boat owners. One such project was a theming project in Python that utilized OpenCV computer vision to ensure that the differently branded apps did not include any other brand's elements. This theming automation helped to reduce QA workload during the release cycle. Another project I worked on involved translating old boat trip JSON data files into a CSV compatible with newer hardware systems which enabled a replay functionality to demonstrate and test boat trips on the app without the need for an actual boat trip, increasing efficiency within our QA team. I had a great time while at Brunswick and learned alot about how a real team operates and collaborates.
AZ-900 Certification Acquired
AI-900 Certification Acquired
AI-102 Certification Acquired
My Projects
Operating System
I collaborated with a group to design and develop an operating system from scratch for a class project. The operating system consisted of a file system, paging, multiple terminals with round robin scheduling, IDT, keyboard handler, assembly linkage, system calls, and user level program execution. Since the code is from a class, I can't post it on Github. However, I have an emulation for it setup at the link below if you would like to try it out!
Technologies used: x86, C
Technologies used: x86, C
RAG Chatbot
I developed a retrieval-augmented generation powered chatbot that gives the LLM private grounding data to use in order to answer prompts. I also utilized Flask to create an API that calls both Pinecone and OpenAI APIs through Langchain in order to embed the prompt, retrieve similar texts from the Pinecone database, and then inject this data into the original prompt to allow the OpenAI LLM to reference them in its response. Additionally, I am trying to design the front end in NextJS so users can interact with the chatbot similar to LLMs like ChatGPT. This project is still in progress.
Technologies used: Python, Pinecone, OpenAI, Langhcain, NextJS, and Flask.
Technologies used: Python, Pinecone, OpenAI, Langhcain, NextJS, and Flask.
Machine Learning ECG Sensor
Developed a machine learning based ECG sensor with a partner using a Raspberry Pi that measures and diagnoses your ECG and sends the results by email. Implemented both a classification model trained on MIT data as well as an autoencoder model for anomaly detection and then aggregated the results for higher accuracy. I achieved 77% accuracy on the ECG diagnosis when testing on students like myself and my partner. I attained an approximately 20 second end-to-end solution including measurement, diagnosis, and emailed results.
Technologies used: Python, TensorFlow, and Raspberry Pi.
Technologies used: Python, TensorFlow, and Raspberry Pi.