CS @ UIUC

Building things that matter.

I'm a CS student at UIUC with a focus in AI/ ML. I build interesting projects and I share my class notes here so other students don't have to start from scratch.

// who i am

const me = {

name: "Krishna Mistry",

school: "UIUC",

major: "computer science",

interests: [

"ML", "gaming",

"emulation", "music"

],

available: true

};

About Me

Creativity-first, curiosity-driven.

I'm a CS student at UIUC working toward graduating in 3 years. I care most about creating fun programs that are intriguing to me and the user.

Recently, I studied data structures and computer architecture. I'm currently exploring AI/ML and applying to be a CA for CS 225.

I also believe in sharing knowledge. This site hosts notes I've made from classes like CS 173 and CS 225 so other students can reference them.

C++ Python Java Data Structures Discrete Math MIPS Assembly Cache Optimization Machine Learning

3

Years to graduate

6+

CS courses completed

4

Featured projects

4.0

GPA

∞

Debugging hours

Work

Projects

A few things I've built and contributed to. Focused on creativity and applied ML.

Complete

MemeFocus — Gaze-Driven Productivity App

A Python productivity tool that uses real-time webcam gaze tracking to detect when you look away from your screen — then punishes you by blasting a full-screen meme or brainrot clip. Built with MediaPipe, OpenCV, PyQt6, and python-vlc. Features Chaos Mode, a grace-period warning system, and a configurable media library.

Built the full gaze detection & CV pipeline using MediaPipe Tasks API with adaptive smoothing and per-session calibration
Resolved a camera fake-focus race condition and media looping bug affecting overlay timing
Integrated a full CI/CD pipeline with pytest and GitHub Actions — headless-safe test suite across 6 modules
Collaborated with a 4-person team; led CV integration and coordinated with PyQt6 frontend

Complete

SSBU Optimizer — Smash Bros. Dashboard

A Streamlit dashboard for Super Smash Bros. Ultimate players. Analyze character matchups, find counterpicks with stat radar charts, track learning progress from beginner to pro, and browse the full tier list. Deployed via Streamlit Community Cloud and optimized for mobile.

Developed a responsive web application for Super Smash Bros. Ultimate players to analyze matchup spreads and track progression across 80+ playable characters
Built an interactive counterpick engine with per-matchup stat radar charts to help players identify optimal character choices
Designed a structured learning tracker mapping skill milestones from beginner to pro across all characters
Integrated a full tier list browser with filtering and sorting by stats, tier, and matchup data

Complete

Stock Market Analyzer

A Streamlit-based dashboard for analyzing and backtesting algorithmic trading strategies. Features interactive equity curve visualizations, a configurable strategy builder, and SQL-powered performance reporting via Flask and SQLAlchemy. Supports drawdown analysis, trade history, and complex SQL queries across stored backtest results.

Engineered a financial metrics calculator supporting 17+ distinct performance indicators including Sharpe ratios and max drawdowns in an open-source market analyzer by processing backtest equity curves and trade logs.
Validated end-to-end backtesting pipeline reliability by achieving full metric accuracy across 5 distinct trading strategies
Deployed as a full-stack Streamlit + Flask app with Plotly visualizations

Stock Market Analyzer screenshot unavailable

Complete

Fake News Detector

A multimodal fake news detection web app built with Streamlit. Classifies misinformation in text articles and videos using DistilBERT, CLIP, and Whisper. Includes article scraping and video transcription.

Trained a multimodal classification pipeline combining DistilBERT for text, CLIP for images, and Whisper for video transcription
Built an article scraper and video transcription module to support real-world input from URLs
Integrated all three modalities into a unified Streamlit interface with confidence scores per modality
Handled edge cases for text-only, image-only, and video inputs with graceful fallback logic

Open Knowledge

CS Notes

Notes from UIUC CS courses, free to use. Always cross-reference with official materials.

CS 173

Discrete Structures

Logic, proofs, sets, relations, functions, induction, combinatorics, and graph theory — the mathematical foundations of computer science. Contains content from Fall 2025.

Disclaimer: NP is not covered.

CS 173 — Full Notes PDF

PDF

CS 225

Data Structures

Lists, trees, graphs, hash tables — and the algorithms that operate on them. Tradeoff and Big-O runtime analysis. Core material for technical interviews. Contains content from Spring 2026.

CS 225 — Full Notes PDF

PDF

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