Hi there, I'm

Barsha KC Khatri

Building scalable systems, data-driven solutions, and AI-powered applications.

About Me

I am an Electronics, Communication and Information Engineer with a focus on backend systems, data engineering, and AI-driven applications.

I have an experience in building full-stack applications, data pipelines, and scalable systems, with work in computer vision (YOLO) and assistive technology research.

I enjoy solving real-world problems by combining software engineering, data analysis, and machine learning to create practical and impactful solutions.

Education

Bachelor’s in Electronics, Communication and Information Engineering

Institute of Engineering, Pashchimanchal Campus

2021 – 2025

Skills

Programming

C • C++ • Python

Frameworks & Libraries

Django • FastAPI • Pandas • NumPy • Streamlit

Backend & APIs

REST APIs • Celery • Redis

Machine Learning

YOLO • OpenCV

Databases

PostgreSQL • MySQL

Tools & Others

Git • Docker • Power BI

Projects

Obstacle Detection System

AI + IoT system for real-time obstacle detection with audio and haptic feedback.

Python, OpenCV, YOLOv3, Raspberry Pi

Paper ↗

Finance Tracker

Full-stack system for tracking transactions, budgets, and financial analytics.

Django, DRF, React, PostgreSQL, Docker, Nginx, Chart.js

GitHub ↗

Task Scheduler

Backend system for scheduling and managing tasks with real-time monitoring.

FastAPI, Celery, Streamlit, Docker

GitHub ↗

YouTube Data Analytics

Automated data pipeline and dashboard for analyzing video performance.

Python, Airflow, PostgreSQL, DRF, Power BI

GitHub ↗

Nepali Sign Language Recognition

Developed a real-time sign language recognition using YOLOv8.

Python, OpenCV, ML

Link

Research & Publications

Obstacle Detection for Visually Impaired

IOE Graduate Conference (IOEGC-16), 2025

A real-time obstacle detection system using YOLOv3 and Raspberry Pi to assist visually impaired individuals with navigation through audio and haptic feedback.

Research Paper ↗

Nepali Sign Language Recognition

RTSTI Conference, 2025 (Conference Abstract)
Abstract No: 20P-MAC-ORAL-051 | Oral Presentation | p.

A computer vision-based system for recognizing Nepali sign language gestures using YOLO models.

Abstract ↗