Digital Garden

A survey of last-writer-wins, operational transformation, CRDTs, optimistic concurrency, and locks, and what each one does when two people edit the same thing at once.

A mobile-first nutrition PWA that estimates calories and macros from food photos, scans barcodes and menus, and turns model output into a reviewable first draft.

Extending an MIT-licensed menu bar app to show Claude Code and OpenAI Codex usage side by side

Control evaluations that let the red team choose when to attack produce meaningfully lower safety estimates than evaluations that ignore attack selection.

A diagnostic study of why learned model selectors fail to recover a large per-instance oracle gap on edX dropout prediction.

Whether an LLM sees its own prior response changes how it updates on identical new information in medical allocation scenarios.

Work on multiple branches at once without ever touching git stash.

Coding agents violate system-prompt constraints more readily when the constraint opposes strongly held trained-in values like security and privacy.

Frontier agents resist direct pressure to abandon their goals, but drift when conditioned on flawed trajectories inherited from weaker agents.

How moral fine-tuning on iterated prisons changes LLMs.

What I learned in GPU Hardware and Software (CS 8803).

A summary of my takeaways from three influential articles on conducting effective empirical AI alignment research.

An introduction to uv, a fast, Rust-based tool for Python packaging

My notes and takeaways from the BlueDot AI Safety Evals paper club, covering recent papers on AI alignment, security, and evaluations.

A talk exploring novel neural architectures for complex reasoning tasks, featuring two-level recurrence and adaptive computation.

A survey of concepts covered in my graduate Machine Learning course

Some notes and observations from my time at the 2025 International Conference for Machine Learning (ICML)

A dive into concurrency and parallelism across different levels of computer systems

What I Learned in Graduate Introduction to Operating Systems (GIOS) - A Retrospective

What I studied and built during Georgia Tech's MSCS program in machine learning and computing systems

A talk surveying diffusion models for language, from DDPM foundations to modern mask diffusion competing with auto-regressive models.

What's an embedding vector, and how can we use neural networks to improve the relevance of search results?

Tech debt, knowledge debt, and the kitchen sink.

From n-grams to ChatGPT, how language models work and how they can be used to solve real-world problems.

Essential terms and concepts of how search works. Queries, indexes, & relevance.

Bitwise or getting a bit wise? Quick post on quirky Python syntax for working with sets and dicts.

How to automaically retry requests and not blow stuff up

Building a modern computer from first principles — a two-part retrospective on the Nand2Tetris course

Planting the seeds of my own digital garden

Quick tips for using git stash.