Hello! I Am
Basant Rauniyar

I am a highly motivated programmer and machine learning enthusiast with a diverse skill set spanning data science, AI development, web applications, and cloud technologies. I have a strong foundation in Python, Flask, and deep learning, with hands-on experience in building solutions such as a crop recommendation system, heart disease prediction model, and an SRS parameter extraction tool. I am passionate about solving complex problems and developing innovative, real-world applications.

Beyond programming, I enjoy building AI-powered tools, exploring microprocessors, and expanding my technical skills. I created the AgeGuard Chrome extension, which uses machine learning for content filtering. I'm always eager to learn new tech and craft impactful, scalable solutions.

Hire Me See My Work
Basant Rauniyar - Full Stack Developer and CE-SE Student
Academic Background

Education

Mar 2018 – Jun 2019
Biratnagar, Nepal

GRADE X, National Examination Board (NEB)

Arpan English School
Cumulative GPA: 3.6/4
  • • Rank 1 in School
Aug 2019 – Jul 2021
Biratnagar, Nepal

GRADE XII, National Examination Board (NEB)

Shiksha Deep Boarding Secondary School
Cumulative GPA: 3.22/4
Aug 2021 – Jul 2025
Bengaluru, India

Bachelor of Technology in Computer Science and Engineering

Jain Deemed to Be University
Cumulative GPA: 9.0/10
  • • Full scholarship recipient through Pragati Scholarship (IND-SAT) funded by Study in India (EDCIL)
My Skills

Technical & Professional Skills

Technical Skills

Programming Languages:
Python C++ Java HTML CSS JavaScript
Tools:
NodeJS React Excel SQL MongoDB Flask VS Code Git Canva Microsoft Office
Software Testing:
Integration Testing Regression Testing Unit Testing

Soft Skills

Professional Competencies:
Leadership Teamwork Adaptability Continuous Learning Effective Writing Verbal Communication Analytical Thinking Decision Making Attention to Detail
Additional Skills:
Problem Solving Critical Thinking Time Management Project Management Research Content Writing Content Adaptation & Implementation
Recent Work

My Projects

AgeGuard

AgeGuard: Advanced 18+ Content Blocking and Safe Browsing Extension

JavaScript HTML CSS Chrome APIs Face-api.js WebRTC
  • • Designed a privacy-first Chrome extension that uses face detection to identify user age in real time.
  • • Blocks access to adult content if the detected user is underage using webcam.
  • • Integrated face-api.js with Chrome APIs to perform real-time age classification.
  • • Technologies Used: JavaScript, HTML, CSS, JSON, face-api.js, WebRTC, Manifest V3
  • View Source Code
AgriRec

AgriRec: Decision Tree Based Agricultural Crop Recommendation with Web Platform Integration

Machine Learning Python Flask Decision Tree Classifier
  • • Uses Decision Tree Classifier to recommend the best crop.
  • • Takes input like soil nutrients (N, P, K) and pH value.
  • • Considers environmental factors like rainfall, humidity, and temperature.
  • • Technologies Used: Python, Flask, Scikit-learn
  • View Source Code
CardioVisionary

CardioVisionary: Boosting Based Cardiac Disease Prediction using ML Techniques

Machine Learning Python Flask Scikit-learn Gradient Boosting
  • • Predicting cardiac diseases using ML boosting techniques.
  • • Evaluated models like Logistic Regression, SVM, and Random Forest.
  • • Gradient Boosting achieved the best performance and was deployed.
  • • Integrated a user-friendly web interface for real-time predictions.
  • • Technologies Used: Python, Flask, Scikit-learn
  • View Source Code
Motion-Detector-Chrome-Extension

MotionDetector: A Chrome Extension for Real-Time Webcam-Based Movement Detection

JavaScript HTML CSS Chrome APIs
  • • Built a lightweight Chrome Extension that uses the webcam to detect motion in real-time.
  • • Implemented a responsive UI that updates live status: “Motion Detected!” or “No motion detected.
  • • Designed for simplicity—no external dependencies, just plug-and-play.
  • • Technologies Used: JavaScript, HTML, CSS, Chrome Extension APIs
  • View Source Code
SafeBrowse

SafeBrowse: A Chrome Extension for Real-Time Malicious URL Detection

JavaScript HTML CSS Chrome APIs JSON
  • • Developed a Chrome browser extension that protects users from phishing, malware, and scam websites.
  • • Redirects users to a custom warning page when malicious activity is detected.
  • • Continuously monitors URLs in real-time and blocks access to unsafe domains.
  • • Technologies Used: JavaScript, Manifest V3, HTML, CSS, JSON, Chrome Extension API
  • View Source Code
SecureLogger

SecureLogger: AI-Based Keystroke Monitoring & Bot Detection

Python Machine Learning AES Encryption Random Forest
  • • Advanced AI-enhanced keystroke logger that detects bots using keystroke dynamics.
  • • ML model (Random Forest) classifies human vs. bot typing behavior in real time.
  • • Features automatic log clearance and real-time anomaly detection.
  • • Dataset generated from real and synthetic keystrokes with preprocessing.
  • • Technologies Used: Python (pynput, numpy, pandas), Scikit-learn, PyCryptodome.
  • View Source Code
Friday - AI Voice Assistant

Friday: Your Personal AI Voice Assistant for Smarter Everyday Taskst

Python SpeechRecognition pyttsx3 Tkinter Wikipedia API
  • • Designed a voice assistant to automate tasks like web search and note-taking.
  • •Integrated speech recognition for seamless, real-time, hands-free user interaction and control.
  • • Developed a GUI using Tkinter for an interactive user experience.
  • • Technologies Used: Python, SpeechRecognition, pyttsx3, Tkinter, Wikipedia API
  • View Source Code
PatanHelper

PatanHelper: A Python Chatbot for Patan Hospital Assistance

Python Flask HTML CSS JavaScript Vercel
  • • Developed an interactive chatbot for Patan Hospital to assist users with queries.
  • • Implemented Fetch API for securely and efficiently sending user queries to the Flask backend.
  • • Deployed the chatbot using Vercel for easy hosting and accessibility.
  • • Technologies Used: Python, HTML, CSS, JavaScript, Flask, Vercel
  • View Source Code
Secure Login System

SecureLogin: A Flask-based Multi-Factor Authentication (MFA) System

Python Flask Email OTP MFA
  • • Built a robust Flask-based login system with Multi-Factor Authentication (MFA) via email OTP.
  • • Implements secure user authentication with encrypted password storage and OTP verification.
  • • Prevents brute-force attacks and unauthorized access through session control and login attempt limits.
  • • Customizable settings for OTP expiry, email configuration, and UI elements.
  • • Ideal for personal, educational, and corporate login systems requiring enhanced security.
  • • Technologies Used: Flask, Python, SQLite, smtplib, hashlib, secrets.
  • View Source Code
Software Requirement Specification

Software Requirement Specification Document Analysis and Parameter Identification Using ML

Machine Learning PyMuPDF Python Scikit-learn LangChain
  • • Extracts key parameters from SRS documents using ML & NLP.
  • • Automates requirement categorization with text classification.
  • • Includes Chatbot using LangChain for clarifying unclear SRS requirements
  • • Technologies Used: Python, PyMuPDF, NLP, LangChain, Scikit-learn
  • View Source Code
ShieldPass

ShieldPass: Secure Password Storage with Real-Time Breach Warnings

Python Tkinter SQLite Fernet Encryption Have I Been Pwned API
  • • Offline password manager that securely encrypts and stores credentials.
  • • Integrates Have I Been Pwned API to check for password breaches in real time.
  • • Built-in GUI using Tkinter for easy password management and retrieval.
  • • Maintains an activity log for breach alerts, saves, and retrieval attempts.
  • • Technologies Used: Python, SQLite, Cryptography, Requests, Tkinter, Logging.
  • View Source Code
Academic Contributions

Papers & Publications

2025

AgriRec: Decision Tree-Based Agricultural Crop Recommendation with Web Platform Integration

IEEE INOACC 2025

• AgriRec delivers accurate and reliable crop recommendations using a decision tree model, seamlessly integrated into a Flask-based web platform for streamlined agricultural planning.

2025

CardioVisionary: Boosting Based Cardiac Disease Prediction using ML Techniques

IEEE INOACC 2025

• CardioVisionary leverages boosting-based machine learning to predict cardiac diseases with high accuracy, enabling seamless integration for smarter healthcare decisions.

2025

Software Requirement Specification Document Analysis and Identification of Important Parameters for Development through Machine Learning

IEEE 2025

• Leveraging machine learning, this project automates SRS document analysis, efficiently extracting key development parameters like cost, security, infrastructure, and functionality.

Get in Touch

Any Questions? Feel Free to Contact

Biratnagar - 9, Morang, Nepal

+977 98105 70690 / +91 78701 81590

basantrauniyar15@gmail.com

basantrauniyar

Basant Rauniyar

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