# Prasad Gade — Full Profile

> Data Scientist and Computer Engineer from Mumbai, India. B.Tech student at Sardar Patel Institute of Technology (CGPA 9.26/10). Builds data pipelines, ML models, and interactive web applications. Published researcher and hackathon winner.

## About This Site

prasadgade.dev is Prasad's personal portfolio. It is a single-page React app hosted on GitHub Pages.

This site is not just a resume. It represents who Prasad is as a person. It has technical projects, but also hobbies, favorite movies, a 3D Minecraft skin, a paper physics playground, and hidden easter eggs. The site is built for everyone — recruiters, friends, colleagues, and anyone curious.

Site features:
- 4 visual themes: dark, light, arcade dark, arcade light
- Auto-detects device theme preference
- No-scroll desktop layout (everything fits one screen)
- 3D Minecraft skin viewer (using skinview3d and Three.js)
- Paper playground: the screen turns into a crumpled paper with real physics (cloth simulation)
- Hidden easter eggs: Konami code and "hesoyam" trigger animations
- "Start Here" modal for non-tech visitors explaining every section
- Resume opens in an in-app modal (no redirect, retains users)
- Responsive for mobile, tablet, and desktop-site-on-mobile
- Every modal closes on ESC key
- Custom domain: prasadgade.dev (CNAME via Hostinger)

## Contact

- Email: prasadgade4405@gmail.com
- Phone: +91 8446240041
- Location: Mumbai, India
- Website: https://prasadgade.dev

## Social Profiles

- GitHub: https://github.com/prasad-gade05
- LinkedIn: https://www.linkedin.com/in/prasad-gade05/
- Kaggle: https://kaggle.com/prasadgade
- LeetCode: https://leetcode.com/u/prasad-gade05/
- Streamlit: https://share.streamlit.io/user/prasad-gade05
- Hugging Face: https://huggingface.co/prasad-gade05
- Monkeytype: https://monkeytype.com/profile/prasad_gade05
- Twitter: https://twitter.com/prasad_gade05
- Reddit: https://www.reddit.com/user/prasad_gade05/
- Instagram: https://instagram.com/prasad_gade05
- Spotify: https://open.spotify.com/user/31uuwb7ecf3gglu7rwpl6oxx4hau

## Education

### B.Tech in Computer Engineering
- Institution: Bhartiya Vidya Bhavan's Sardar Patel Institute of Technology (SPIT), Mumbai
- Minor: Management from SPJIMR (S. P. Jain Institute of Management & Research)
- CGPA: 9.26/10.0
- Expected graduation: June 2027

### Diploma in Computer Technology
- Institution: K. K. Wagh Polytechnic, Nashik
- Grade: 96.51%
- Duration: August 2021 to June 2024

## Experience

### Undergraduate Research & Teaching Assistant
- Organization: Department of Computer Engineering, SPIT, Mumbai
- Duration: February 2025 to present
- Performed statistical analysis on student performance data and course feedback to generate reports for faculty
- Conducted literature reviews and migrated manuscripts from Word to LaTeX for research publications
- Created academic posters translating technical research into accessible visual formats

### Data Analyst Intern (Summer Internship)
- Organization: R3 Systems India Pvt. Ltd., Nashik
- Duration: June 2023 to July 2023
- Learned Data Analysis and Business Intelligence using Power BI
- Delivered a sales dashboard for North Wind Traders, improving data visibility by 70%

## Projects

### IPL Analytics Platform — Interactive Cricket Data Dashboard
- Category: Data Engineering & Analytics
- Key stat: 18 IPL seasons analyzed
- Engineered a 3-stage data pipeline processing 278,205 ball-by-ball records across 18 IPL seasons (2008-2025), producing 90 derived features and 15 aggregate parquet files
- Built 14 interactive dashboard pages with 58 preset SQL queries, a custom query builder supporting 9 entity types, season/team/venue/player filters
- Achieved zero data mismatches across 703 batters and 550 bowlers by fixing a critical aggregation bug; validated with 25 automated tests
- Tech: Python, Streamlit, DuckDB, Plotly, Pandas, NumPy, PyArrow, Apache Parquet, SQL, pytest
- Demo: https://analytics-ipl.streamlit.app/
- GitHub: https://github.com/prasad-gade05/IPL_Analysis
- Dataset: https://huggingface.co/datasets/prasad-gade05/ipl-enriched-2008-2025

### UPI Analytics Platform — Data Engineering & Analytics Dashboard
- Category: Data Engineering & Analytics
- Key stat: 9,026 JSON files processed
- Processed 9,026 JSON files from 3 sources across 788 districts/42 months using a 4-stage medallion pipeline into a DuckDB star schema (4 dim + 4 fact tables)
- Quantified market duopoly via HHI, measured geographic inequality using Gini coefficients, segmented adoption tiers with K-Means across 788 districts
- Forecasted UPI volumes using Prophet/ARIMA; delivered 68 visualizations across 11-tab Streamlit + Power BI dashboards, validated by 83 tests via GitHub Actions CI/CD
- Tech: Python, DuckDB, Pandas, Plotly, Streamlit, Power BI, Prophet, ARIMA, Scikit-learn, K-Means, BeautifulSoup4, PyArrow, GitHub Actions
- Demo: https://upi-analytics.streamlit.app/
- GitHub: https://github.com/prasad-gade05/UPI_DS_Project
- Dataset: https://huggingface.co/datasets/prasad-gade05/india-upi-ecosystem-2018-2025

### Lex Simulacra — AI-Powered Legal Courtroom Simulator with Multi-Agent RAG
- Category: AI / NLP
- Key stat: 8 AI agents in simulation
- Built an 8-agent legal simulation (defense, prosecutor, judge) achieving 99% citation accuracy via a LangGraph workflow with state management and iterative debate
- Reduced legal research time by 75% across 100K+ documents by architecting a RAG pipeline with BM25 re-ranking and ChromaDB vector indexing
- Achieved 3.2x context relevance gain and 60% engagement boost via context compression (18K to 15K tokens), hallucination detection, and real-time Streamlit UI with FastAPI SSE
- Tech: Python, LangChain, LangGraph, FastAPI, Streamlit, ChromaDB, Sentence-Transformers, Ollama LLM, Kanoon API, BM25, NLTK, Scikit-learn
- GitHub: https://github.com/prasad-gade05/Law_Courtroom_Simulator

### Comparative Analysis of ML/DL Models for Intrusion Detection
- Category: Machine Learning / Cybersecurity
- Key stat: 99.99% recall, 100% precision
- Benchmarked 6 models (DT, XGBoost, Transformer, Autoencoder, LR, NB) on the 8.6M-sample TII-SSRC-23 dataset (79 features)
- Demonstrated tree models were 12.8x faster (4.7 vs 60 min) with 20x inference throughput (1,005K/s), 10x fewer false negatives
- Reduced classification errors by 30% via hybrid SMOTE-undersampling to address extreme 1:6653 class imbalance
- Tech: Python, Scikit-learn, XGBoost, PyTorch, TensorFlow, SHAP, Pandas, NumPy, Imbalanced-learn
- GitHub: https://github.com/prasad-gade05/IDS_on_TII-SSRC-23

### KindHearts — Multi-Role Donation Management Platform
- Category: Full-Stack Web
- Key stat: 1st place, 80+ teams at Tech Horizon National Hackathon
- Streamlined donation workflows across institutes, donors, and vendors with 60% reduction in request processing time
- Integrated real-time request tracking, crypto-based payments via MetaMask, and impact reporting (45% engagement boost)
- Implemented Kanban-style system for shopkeepers and comprehensive admin controls
- Tech: React, TypeScript, MongoDB, Vite, Tailwind CSS, React Router, ESLint, Context API
- GitHub: https://github.com/prasad-gade05/KindHearts-Multi-Role-Donation-Management-Platform

### Celestial Object Classifier using Sloan Digital Sky Survey Dataset
- Category: Machine Learning
- Key stat: 99.07% accuracy
- Classified 10,000 celestial objects into stars, galaxies, and quasars by engineering 10 features with color-indices and log-redshift
- Improved Neural Network accuracy from 95.13% to 98.78% using Keras Tuner across 10 trials
- Benchmarked 4 classifiers (DT: 87.75%, KNN: 94%, NN: 99%, RF: 99.07%) on 3,000 test samples via GridSearchCV with 5-fold CV and 960+ fits
- Tech: Python, Scikit-learn, Keras, Keras Tuner, Pandas, NumPy, Matplotlib
- GitHub: https://github.com/prasad-gade05/Celestial-Object-Classifier-using-Solana-Digital-Sky-Survey-Dataset

### NutriSnap — Nutrition Tracker Web App
- Category: AI / Web
- Key stat: 95% accurate nutrient estimates via image analysis
- Integrated Gemini API to analyze food images or manual entries for nutrition tracking
- Implemented daily calorie/macro goals and interactive dashboards
- Tech: Flask, Python, HTML, CSS, JavaScript, Gemini API, SQLite, Pandas, OpenCV
- Demo: https://prasadsnutritiontracker.netlify.app/
- GitHub: https://github.com/prasad-gade05/nutrition_tracker

### Audio Visualizer App — Real-Time Music Visualization Tool
- Category: Web / Creative
- Key stat: 1000+ unique visitors in first month
- Real-time audio visualization with multiple dynamic modes (bars, radial waves, scatter plots) and customizable color schemes
- Fully client-side solution on GitHub Pages with file upload and microphone input support
- Tech: TypeScript, Web Audio API, HTML5 Canvas, shadcn/ui, CSS3
- Demo: https://prasadgade.dev/audio_visualizer_app/
- GitHub: https://github.com/prasad-gade05/audio_visualizer_app

### Habit Tracker (Client-Side Progressive Web App)
- Category: Web
- Key stat: fully offline, privacy-first
- GitHub-style contribution charts, streaks, calendar view, and analytics
- IndexedDB (Dexie.js) for persistent offline storage, no server dependency
- Tech: React, TypeScript, Vite, Tailwind CSS, shadcn/ui, Zustand, Dexie.js, Recharts, date-fns
- Demo: https://prasadgade.dev/Habit-Tracker/
- GitHub: https://github.com/prasad-gade05/Habit-Tracker

### Attendance Management Web App (Feature-Rich PWA)
- Category: Web
- Key stat: offline-ready with sync
- Subject-wise reports, student-wise analysis, editable records, data import/export
- Offline-first using IndexedDB (Dexie.js)
- Tech: React, TypeScript, Vite, Tailwind CSS, Zustand, Dexie.js, Recharts
- Demo: https://prasadgade.dev/attendance/
- GitHub: https://github.com/prasad-gade05/attendance

### AI Text Summarizer, Translator, and Extractor
- Category: AI / NLP
- Web app using Python and Eel, integrating Hugging Face, GoogleTrans, and OCR
- Tech: Python, HTML, CSS, JavaScript, Eel, Pytesseract, Googletrans, Pypdf2
- GitHub: https://github.com/prasad-gade05/AI-Text-Summarizer-Translator-and-Extractor

### Real-time Image & Audio Classification App
- Category: Mobile / ML
- Android app with Google ML Kit and TensorFlow YAMNet for real-time image labeling and audio classification
- Tech: Android SDK, Java, Google ML Kit, TensorFlow YAMNet
- GitHub: https://github.com/prasad-gade05/Real-time-audio-and-image-classification

### Encrypted File Sharing Application
- Category: Security
- Secure file-sharing over networks using RSA encryption with a handshake mechanism for key distribution
- Tech: Java, RSA Algorithm
- GitHub: https://github.com/prasad-gade05/End-to-End-Encrypted-Chatting-Application

### Portfolio Site (this site)
- Category: Web / Creative
- 4 themes, 3D Minecraft skin, paper physics playground, Konami code easter egg
- Tech: React, Three.js, Framer Motion, Vite
- Demo: https://prasadgade.dev
- GitHub: https://github.com/prasad-gade05/prasad-gade05.github.io

## Skills

### Languages
Python, JavaScript, TypeScript, Java, C++, SQL, C, HTML, PHP, VB.net, Assembly (x86)

### ML / Data Science
Pandas, NumPy, Scikit-Learn, PyTorch, TensorFlow, LangChain, Keras, Matplotlib, Seaborn, Hugging Face, OpenCV, Google ML Kit, SHAP, Imbalanced-learn

### Visualization & BI
Power BI, Plotly, Streamlit

### Web Frameworks
React, Flask, FastAPI, Node.js, Streamlit, Django, Eel

### Databases
MongoDB, SQLite, ChromaDB, PostgreSQL, DuckDB, SQL, Oracle, Firebase

### DevOps & Tools
Git, Docker, AWS, Linux, GitHub Actions, Arduino, Jupyter Notebook, Google Colab, VS Code, Vim

### Soft Skills
Leadership (served as General Secretary, Student Council), Time Management, Public Speaking, Writing, Communication

## Publications

### Postpartum Depression Predictor using Machine Learning
- Journal: IJIES Vol. 9, No. 1, 2024, PP. 39-43
- DOI: https://doi.org/10.46335/IJIES.2024.9.1.8
- Published findings on accuracies of various ML algorithms for predicting postpartum depression
- Tech: Decision Tree, XGBoost, Random Forest, NumPy, Matplotlib, Pandas

## Leadership

### General Secretary of Students Council
- Organization: K. K. Wagh Polytechnic, Nashik
- Duration: August 2023 to June 2024
- Organized the institute annual fest "Sparsh 2024" on the theme "Swaraj" celebrating the 350th anniversary of the coronation of Chhatrapati Shivaji Maharaj

## Certifications

1. Data Science Job Simulation — BCG (Forage) — January 2025
2. Developer & Technology Simulation — Accenture UK (Forage) — January 2025
3. Introduction to Cloud Computing on AWS — Udemy — July 2024
4. The World of Computer Networking — Udemy — June 2024
5. Java Training — IIT Bombay — March 2024
6. Arduino Course — Robo-Tech-X — August 2023
7. Introduction to Machine Learning — Infosys — November 2022

## Achievements

1. Winner — Tech Horizon National Hackathon (1st place out of 80+ teams) — March 2025
2. Published Researcher — IJIES Journal — April 2024
3. Open-Source Dataset Contributor — Published IPL and India UPI datasets on Kaggle and Hugging Face — 2025

## Volunteering

### Teaching Assistant
- Organization: Sardar Patel Institute of Technology (SPIT), Mumbai
- Duration: 2025 to present

### General Secretary — Students Council
- Organization: K. K. Wagh Polytechnic, Nashik
- Duration: 2023 to 2024

## Hobbies & Interests

- Sports: Cricket, Minecraft
- Favorite Book: "How to Win Friends and Influence People" by Dale Carnegie
- Favorite Songs: "Take Me Home, Country Roads" by John Denver, "Main Zindagi Ka Saath Nibhata Chala Gaya" by Mohammed Rafi
- Favorite Series: Squid Games, Money Heist
- Favorite Movies: 12th Fail, Sam Bahadur, American Sniper, Hacksaw Ridge, The Green Mile, 1917, WALL-E, Ratatouille, Kung Fu Panda series, Toy Story series, and more (47 movies listed on the portfolio)

## Sub-Projects Hosted on prasadgade.dev

These are separate web apps hosted as sub-paths on the same domain:

- Audio Visualizer: https://prasadgade.dev/audio_visualizer_app/ — Real-time music visualization with multiple modes
- Attendance Tracker: https://prasadgade.dev/attendance/ — Smart attendance tracking PWA with offline support
- Habit Tracker: https://prasadgade.dev/Habit-Tracker/ — Privacy-first habit tracking with GitHub-style charts

## Structured Data Endpoints

- Resume (JSON): https://prasadgade.dev/api/resume.json
- Projects (JSON): https://prasadgade.dev/api/projects.json
- Skills (JSON): https://prasadgade.dev/api/skills.json
- Social (JSON): https://prasadgade.dev/api/social.json
- About (JSON): https://prasadgade.dev/api/about.json
- Resume (PDF): https://prasadgade.dev/Prasad_Gade_Resume.pdf

## Agent Discovery Endpoints

- Agent endpoint: https://prasadgade.dev/agent/
- A2A Agent Card: https://prasadgade.dev/.well-known/agent.json
- agents.json discovery file: https://prasadgade.dev/.well-known/agents.json
- Agent skills index: https://prasadgade.dev/.well-known/agent-skills/index.json
- API catalog: https://prasadgade.dev/.well-known/api-catalog
- OpenAPI specification: https://prasadgade.dev/openapi.json
- Well-known OpenAPI: https://prasadgade.dev/.well-known/openapi