Rei Meguro
I enjoy the art of over-engineering complex, fast things
About Me
I'm an ambitious Computer Science student who enjoys
automating systems and workflows. I work extensively with AI
technologies (machine learning, LLMs, computer vision) as
well as full-stack development. I am also the author of
Japan's strongest chess engine, Raphael.
Note: I am comfortable using LLMs as development tools, but
I do not rely on unverified output. Any LLM-generated code
used during development is carefully reviewed and tested by
me before being included in a project.
My Recent Projects
Click on the cards to visit project links
Raphael
Raphael is a chess engine written in C++ and is
currently the strongest chess engine in Japan.
It uses alpha-beta search with multiple
enhancements, along with a quantized neural network
running on the CPU using SIMD intrinsics, trained on
tens of millions of self-play games.
Onyx
Onyx is an open-source AI platform that
automatically ingests documents from connected
sources and uses deep research agents to answer
questions or complete complex tasks.
I contributed to the development of the deep
research agent and the knowledge graph indexing and
inference pipeline, eliminating OOM errors,
improving fault tolerance, and tripling indexing
speed.
AdaPhish
AdaPhish is an adaptive phishing detection and
submission platform that learns attack patterns over
time using a vector store and RAG, built with
Docker, FastAPI, Next.js, and Nginx.
The project was published at the 4th IEEE ICAIC
Conference and received the Best Paper Award.
Kineval
Kineval is a Python-based interactive learning tool
for forward kinematics, inverse kinematics,
collision detection, and RRT motion planning.
It was developed for EECS 367 at the University of
Michigan and is structured to allow students to
implement these algorithms themselves without
needing to manage rendering or other supporting
systems.
Folio
Folio is a startup platform that connects
freelancers with venture-backed startups.
I developed the core email notification system and
contributed to data migration pipelines used to
transition from the previous platform, working with
Django, Next.js, Docker, and Git.
ConverseCart Search Engine
ConverseCart is a startup that helps retail stores
improve product click-through rates by providing an
AI-powered search engine.
I contributed to early versions of the search system
using word embeddings, bag-of-words models, and
cross-encoders to enable fast, personalized natural
language queries.
RTD Toolkit
RTD, developed at the University of Michigan,
enables provably safe motion planning while
accounting for uncertainty in measurements using
polynomial zonotopes.
I worked for the ROAHM Lab to port the MATLAB
implementation into a general-purpose Python
library, while also introducing performance
optimizations and improving usability.
Mandelbrot Fractal Explorer
An interactive Mandelbrot fractal explorer written
in C++ using SFML.
It uses thread pools to exploit the embarrassingly
parallel nature of the computation, enabling 1080p
rendering and zoom levels up to 10^-16.
Sudoku Solver
A Sudoku solver that combines a backtracking
algorithm for solving, a CNN for digit recognition,
and PyAutoGUI for automated number entry.
The system reads the puzzle from the screen,
recognizes digits, computes the solution, and fills
the grid automatically.
Nerd Wrecker: Connect 4
A fully automated multiplayer Connect 4 player.
The program uses alpha-beta search with bitboards to
efficiently compute optimal moves, and leverages
PyAutoGUI to read game states and input moves
through the graphical interface.
LC2K CPU Simulator
LC2K (Little Computer 2000) is a minimal instruction
set architecture with eight instructions, used in
the University of Michigan EECS 370 Computer
Organization course.
This project implements the LC2K CPU along with a
memory-mapped display inside Excel, using
self-referencing cells to simulate the clock,
registers, and memory.
Plaite
Plaite is a nutrition tracking application that uses
YOLOv8 for real-time food detection, developed
during the 24-hour MHacks 2024 hackathon. It also
includes an LLM-based food recommendation assistant.
The project received the Best Use of Intel AI Award.