My Projects
| Project Name | Image | Description |
|---|---|---|
| Cognateful |
|
Interactive language-learning app that teaches you French using stories written in French, with translation exercises that are scored using large language model judgements. |
| NeRFs from Scratch |
|
Designed and implemented a NeRF (Neural Radiance Field) model in PyTorch based on the original NeRF paper. Successfully reconstructed a 3D scene of a rotating LEGO truck from a set of 2D views. |
| Diffusion Models from Scratch |
|
Implemented flow matching generative model in PyTorch using a time and class-conditioned UNet. Trained the model on MNIST with conditional dropout to support classifier-free guidance during inference. Built sampling + visualization pipeline to generate GIFs showing emergence of digits over time. |
| GSO: Software Optimization Tasks for Evaluating SWE-Agents |
|
Paper Accepted at NeurIPS 2025 (Datasets & Benchmarks Track): Coauthored Global Software Optimization (GSO), an LLM code optimization benchmark spanning 102 optimization problems and five programming languages. |
| PintOS (Operating Systems Class Project) |
|
Built a transaction-safe Unix-like file system with hierarchical inode structure, resizable files, and rollback recovery. Developed an in-memory buffer cache with fine-grained locking for concurrent disk I/O. Implemented a POSIX-style threading subsystem with kernel-level synchronization primitives and priority scheduling to enable true parallel execution. |
| RISC-V CPU |
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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. |
| FactGrid Cuneiform Project |
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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 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. |
Bio
My name is Vijay Kethana, and I’m a computer science student at UC Berkeley. I’m interested in natural language processing (NLP), machine learning systems, and artificial intelligence in general. Outside of school, I enjoy cooking, hiking, and learning languages. I also blog.
Links
- Blog: vkethana.com/vjposts
- RSS (Atom) Feed: vkethana.com/feed.xml
- GitHub: github.com/vkethana
- LinkedIn: linkedin.com/in/vkethana/
Education
- Currently pursuing Bachelor of Arts in Computer Science (3.97 GPA) from UC Berkeley (2023 – ).
- Coursework: Operating Systems, Machine Learning, Deep Learning, Computer Vision, Data Structures, Algorithms, Introductory & Intermediate Sanskrit.