Vijay's Personal Website

My Projects

Name	What is it?	Link
RISC-V CPU	Designed RISC-V CPU in Logisim	View
Handwritten Digit Classifier	ML algorithm in RISC-V assembly to classify digits	View
FactGrid Cuneiform Project	ML model to segment and transcribe Cuneiform tablets	View
The David Deutsch Dictionary	Online database of quotes with Google Sheets backend	View
Scheme Interpreter	Python-based evaluator and interpreter for Scheme	View
Helium Balloon Project	OpenCV-powered object tracking for helium balloons	View
BYOW (Build Your Own World)	Pseudo-random world generation algorithm in Java	View
2D Convolutions Optimizer	Parallelizable 2D discrete convolutions algorithm	View

More Info

Project Name	Image	Description
RISC-V CPU		Built a full CPU in Logism that runs instructions in assembly language. Implemented two-stage pipelining to increase throughput. Prevent control hazards via pipeline flushing.
Handwritten Digit Classifier		Designed machine learning algorithm to classify handwritten digits from MNIST database of 60,000 28x28 images. Wrote RISC-V assembly procedures for matrix multiplication, dot products, and the activation and loss functions.
FactGrid Cuneiform Project		Develop machine learning model to segment and transcribe dataset of 1,068 annotated Cuneiform tablets using the YOLOv8 architecture.
The David Deutsch Dictionary		Online database of quotes from prolific science author and quantum physicist David Deutsch. Utilizes Google Sheets as a backend database to allow for seamless and near-real-time updates. Scraped quotes off the internet using Python3 and NLTK (Natural Language Tool Kit). Designed UI using Flask and HTML.
Scheme Interpreter		Python-based evaluator and interpreter for Scheme, a dialect of Lisp.
Helium Balloon Project		OpenCV-powered object tracking for helium balloons using the CSRT (Channel Spatial and Reliability Tracking) algorithm.
BYOW (Build Your Own World)		Pseudo-random world generation algorithm built in Java. Also created a UI for generating, saving, and loading worlds.
2D Convolutions Optimizer		Created algorithm for running 2D convolutions. Sped up algorithm by a factor of 8.10x using SIMD Instructions, multithreading via OpenMP, and targeted algorithmic optimizations. Wrote OpenMPI coordinator to support process-level parallelism capabilities.

Bio

My name is Vijay Kethanaboyina, and I’m a computer science student at UC Berkeley aspiring to work as a software or machine learning engineer. I’ve solved problems in technical areas such as computer vision and Linux system administration. I’m also an avid reader and language learner.

Education

Bachelor of Arts in Computer Science (4.0 GPA) from UC Berkeley (2023 – 2026).
Coursework: Data Structures, Efficient Algorithms, Computer Architecture, Probability & Random Processes, Discrete Math, Linear Algebra, Multivariable Calculus.

Skills

Languages: Python (Pandas, Matplotlib, OpenCV), C, C++, Assembly, Java, Lisp, HTML/CSS, JavaScript, SQL
Frameworks: React, Node.js, Flask, OpenMP, OpenMPI, JUnit
Developer Tools: Git, Vim, IntelliJ IDEA, Docker
System Administration: Debian, Arch Linux, DigitalOcean

Experience

Undergraduate Researcher for UC Berkeley Sky Computing Lab

June 2024 - Present

Collaborating with UC Berkeley CS PhD students to enhance R2E, a framework for evaluating code generation capabilities of large language models. Scaling Python code generation benchmarks to include snippets from a wide selection of repositories (end goal: 1000+).
Developing an LLM-powered agent to automate the cloning, setup, and execution of Python GitHub repositories; detecting and fixing installation errors using GPT-4 powered agentic loop.

Hackathon Cofounder

2022-2023

Organized Gilroy Hacks, a multi-school, student-led hackathon series for middle/high schoolers in Gilroy, CA.
Secured a $1,481 grant by convincing sponsors and resolving logistical issues. Coordinated with judges and backers, including Wolfram Language, 1Password, and AoPS.
Support development of 7 hackathon projects in Python, Next.js, Typescript, and Flask.

Research Intern (Paid) at Gavilan College

June - August 2022

Developed Python script with OpenCV to track fast-moving helium balloons using a smartphone camera. Utilized the CSRT (Channel and Spatial Reliability Tracking) and KCF (Kernelized Correlation Filter) algorithms. Collaborated with two teammates under Dr. David Argudo, Ph.D.
Processed balloon motion videos into CSV location data files. Applied Statsmodels to clean datasets and handle out-of-frame objects.
Authored comprehensive, ten-page document describing how to conduct classroom physics demonstrations using the balloon tracking software.

vkethana.com