Hello, I'm

Himani Shrestha

I'm a passionate computer science enthusiast with hands-on experience in data analysis, pipelines, machine learning, and product development. I enjoy exploring the intersection of data and intelligent systems, and I'm driven by curiosity to learn new technologies and solve real-world problems. From backend systems to AI-driven applications, I love turning ideas into impactful solutions while continuously growing along the way.

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Himani Shrestha
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About Me

Curious to discover new experiences, learn new skills, and enjoy the journey ahead—driven by passion for technology, creativity, and continuous growth.

About Himani

Personal Details

Date of Birth
November 21, 2005
Location
Kathmandu, Nepal
Email
himanistha78@gmail.com
Phone
+977-9847390710
Hobbies
Dancing, Cooking, Travelling
Languages
Nepali, English, Hindi

A passionate and motivated computer science enthusiast with hands-on experience in data analysis, machine learning, and backend development. I enjoy building practical solutions that combine data engineering and AI technologies. With a solid foundation in programming and a strong curiosity for intelligent systems, I aim to contribute to innovative, forward-thinking teams. I thrive in dynamic environments where I can solve real-world problems and grow through continuous learning.

I specialize in Python, FastAPI, and ML/AI frameworks, and have worked with tools like Scikit-learn, LangChain, PySpark, and various vector databases. From academic research to building full-stack applications and AI-powered systems, I bring both technical precision and creative problem-solving to every project. Outside of coding, I enjoy exploring emerging technologies, mentoring peers, and staying curious about how data can shape the future.

Education

Bachelor of Computer Science
Herald College, Kathmandu
Affiliated to University of Wolverhampton
2023 - 2025
Completed a Bachelor’s degree in Computer Science with practical experience in machine learning, data pipelines, and product development. Coursework covered core topics including data structures, algorithms, database systems, and intelligent systems. Gained hands-on knowledge through research papers and academic studies in advanced computing concepts and emerging technologies.
Higher Secondary Education (+2)
Herald International College, Kathmandu
2022 - 2023
Completed Higher Secondary Education in Science stream with a strong focus on Mathematics and Computer Science. Achieved a GPA of 3.49 and built a solid foundation in logical reasoning, programming, and core scientific principles.
20+ Projects Completed
2+ Years Hands-on Experience
1 Research Paper
10+ Technologies
My Expertise

Skills & Technologies

A comprehensive overview of my technical skills and proficiency levels in various technologies and tools.

Frontend Development

React.js 45%
JavaScript 70%
TypeScript 55%
HTML & CSS 80%
Tailwind CSS 68%

Backend Development

Python 87%
Java 65%
SQL 78%
MYSQL 75%
FastAPI 70%
MongoDB 70%

Tools & Others

Git & GitHub 93%
Docker 58%
AWS 55%
Figma 80%
Agile/Scrum 85%
My Work

Featured Projects

A showcase of my recent work, demonstrating my skills in full-stack development.

NEPSE-Navigator

Developed a stock market chatbot leveraging large language models to provide fundamental, technical, and policy-based insights. Conducted comprehensive market research on NEPSE data, broker regulations, and user pain points. Built robust data pipelines using FAISS and LangChain for preprocessing, semantic search, query reranking, and multilingual (Nepali-English) document indexing.

FastAPI Transformers MongoDB Langchain

Course Management System

A desktop-based academic management system developed using Java Swing and MySQL, featuring secure, role-based dashboards for Admin, Teachers, and Students. The application includes modular functionalities for course, student, and tutor management, along with personalized dashboards and report generation features.

Java OOP Java Swing MySQL

News Category Classification

An end-to-end machine learning pipeline designed to classify sentiment in text-based news data. Utilized NLP techniques such as tokenization, stop-word removal, and TF-IDF vectorization for effective feature extraction. Multiple classifiers including Multinomial Naive Bayes, Logistic Regression, and SVMs were trained, evaluated, and optimized for better accuracy and reduced overfitting.

Python NLTK Scikit-learn Seaborn Matplotlib Pandas
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Let's Work Together

Have a project in mind? I'd love to hear about it. Let's discuss how we can bring your ideas to life.

Contact Information

Location

Kathmandu, Nepal

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