_______ _______ ______ _____ _______
|_____| | | | |_____/ | |
| | | | | | \_ __|__ |
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❯ ./boot_amrit.sh
[■■■■■■■■■■■■■■■■■■■■] 100% loading personality...
[■■■■■■■■■■■■■■■■■■■■] 100% injecting caffeine...
[■■■■■■■■■■■■■■■■■■■■] 100% compiling opinions...
✔ kernel: ECE @ GSV Central University (CGPA: 8.5)
✔ runtime: React · Node · C++ · Python · GoLang
✔ daemon: always_building.service [ACTIVE]
✔ uptime: since 2003, no planned downtime// languages
let langs = ["C++", "C", "JavaScript ES6+", "TypeScript",
"Python", "SQL", "MATLAB", "GoLang"];
// where the pixels live
let frontend = ["React.js", "Next.js", "Redux", "Tailwind CSS",
"ShadCN UI", "HTML5", "CSS3"];
// where the data flows
let backend = ["Node.js", "Express.js", "WebSockets", "WebRTC",
"Prisma ORM", "Mongoose", "JWT", "REST APIs"];
// where the models grind
let ml_stack = ["Scikit-learn", "XGBoost", "LSTM", "Random Forest",
"Pandas", "NumPy", "OpenCV", "RAG", "Gemini"];
// the essentials
let tools = ["Git", "Postman", "Figma", "VS Code",
"Jupyter", "Arduino", "MongoDB"];+ [Feb 2026 → NOW] Hibiscus Tech — Full Stack Product Intern
>> shipping core platform pages to production
>> React frontends wired to live backend APIs
>> built game bot logic from scratch w/ custom heuristics
>> analysis section? designed & delivered end-to-end.
+ [May–Jun 2025] MMRDA — ML Intern @ Mumbai Metro
>> real trains. real data. real optimization.
>> Random Forest + LSTM → predicted dwell times
>> automated data pipeline → cut manual cleaning 40%
>> scheduling algos that actually reduce delays. shipped.
+ [ongoing] IEEE IGDTUW — Open Source Contributor
>> 5+ PRs merged into main
>> React bug hunts, feature drops, clean code onlyPROJECTS = [
{
"name" : "Mumbai Metro — Dwell Time & Headway Optimizer",
"stack" : ["Python", "Scikit-learn", "LSTM", "Pandas", "NumPy"],
"flex" : "ML on real metro operational data → reduced peak delays",
"alpha" : "Random Forest + LSTM combo for dwell time forecasting",
"impact" : "40% reduction in manual data cleaning via pipeline automation",
},
{
"name" : "Broker Management Platform",
"stack" : ["React", "Node.js", "Express", "MongoDB", "JWT", "Multer"],
"flex" : "full property rental backend — auth, listings, geospatial filters",
"alpha" : "role-based JWT auth + geospatial MongoDB schemas",
"impact" : "cloud-ready image pipeline + optimized search APIs",
},
{
"name" : "House Price Predictor — Bangalore",
"stack" : ["Python", "XGBoost", "Scikit-learn", "GridSearchCV"],
"flex" : "stacking ensembles + XGBoost → low RMSE on housing data",
"alpha" : "extensive feature engineering + GridSearchCV tuning",
"impact" : "high-accuracy regression model, production-grade pipeline",
},
]LEETCODE ████████████████████░░░░ 1726 rating [TOP 15%]
CODECHEF █████████████░░░░░░░░░░░ 1300
CODEFORCES ███████████░░░░░░░░░░░░░ 1100
TCS iON NQT → 89% in C++ | top percentile cognitive
RoomGi Hackathon → top 25 teams [ qualified ]
Wabtec Exceed 3.0 → top 25 teams [ qualified ]
❯ curl -X POST https://amrit.dev/contact \
-d "twitter=@print_amrit" \
-d "linkedin=amrit-bhardwaj-50836528a" \
-d "email=amritbharadwaj4@gmail.com" \
-d "open_to=collabs,internships,hackathons,chaos"
> 200 OK — signal received. reply time: fast.
while (alive) {
eat();
code();
learn();
ship(); // most important
}
grad: 2027 · cgpa: 8.5 · commits: ∞