.svg)
const satyamKumar = {
title: "Aspiring Software Engineer | AI/ML Enthusiast",
location: "Jharkhand, India",
education: "B.Tech CSE @ Siksha 'O' Anusandhan University, ITER (CGPA: 8.98/10)",
stack: {
languages: ["Java", "Python", "C", "JavaScript", "SQL"],
web: ["React", "Node.js", "Express", "Flask", "REST APIs", "HTML/CSS"],
databases: ["MySQL", "MongoDB"],
aiMl: ["Scikit-learn", "NumPy", "Pandas", "NLP", "Azure Custom Vision"],
tools: ["Git", "GitHub", "Postman", "VS Code", "Azure", "AWS", "Linux"],
},
launchedProjects: [
"EduFlow-SkillForge1",
"Saarthi — Multi-Agent AI Banking Assistant",
"SentinelAI — NLP Cyberbullying Detection System",
"Kitchen Preparation Time (KPT) Prediction System",
],
certifications: [
"Microsoft Azure AI Fundamentals",
"Google Machine Learning Crash Course (MLCC)",
"Google Generative AI",
],
achievements: [
"300+ LeetCode problems solved",
"SBI AI Hackathon @ Global Fintech Fest 2026",
"SEBI TechSprint @ Global Fintech Fest 2026",
"SynthQuest @ IIT Delhi",
"Hackentine National Hackathon",
],
status: "🌱 Learning scalable systems & GenAI",
openTo: ["Software Engineering Roles", "AI/ML Internships", "Open Source Collaboration"],
} as const;An education / skill-building web platform, deployed live on Vercel.
| Layer | Technology |
|---|---|
| Frontend | React.js |
| Styling | Tailwind CSS |
| Deployment | Vercel |
A multi-agent AI system for dormant bank account reactivation, with dedicated Reasoning, Voice, Handoff, and Feedback agents. Submitted to the SBI AI Hackathon at Global Fintech Fest 2026.
| Layer | Technology |
|---|---|
| Backend | Java, Flask (REST API) |
| Database | MySQL (normalized schema, audit logs) |
| AI/LLM | LLM-powered intent detection, multilingual conversation |
| Architecture | Multi-agent, modular OOP, service-layer separation |
🔗 Code
A multi-model NLP pipeline achieving 93.8% accuracy and a 0.914 macro F1-score across 6 hate-speech categories, with real-time moderation via a Flask REST API.
| Layer | Technology |
|---|---|
| ML Models | TF-IDF, Linear SVM, Logistic Regression, Random Forest, Naive Bayes |
| Backend | Flask (REST API), ensemble voting |
| Database | MySQL (classification results, audit trails, indexing) |
| Validation | 5-fold cross-validation |
🔗 Code
A predictive framework estimating kitchen preparation time using merchant bias correction, kitchen load algorithms, and adaptive composite scoring — simulated across 3,000+ order lifecycles on 60 merchants.
| Layer | Technology |
|---|---|
| Core Logic | Java, Python |
| Algorithms | Graph-based DSA for dependency resolution |
| Database | MySQL (indexed relational schemas) |
🔗 Code
Languages
Frontend
Backend & APIs
Databases
Cloud & Dev Tools
AI / ML
🐍 The snake animation above needs a one-time GitHub Action set up in your
Satyam5367/Satyam5367repo. See the snake workflow guide — it commits anoutput/github-contribution-grid-snake.svgon a schedule, which is what this image points to.
