Nirajan Basnet

About

Namaste! I am Nirajan, a tech enthusiast. I have over two years of experience in the tech world, comprising roles in full-stack, AI, and DevOps. I am interested in security, DevOps, and the site reliability side of things.

Interests

Full Stack
Data Infrastructure
DevOps

Education

PhD in Computer Science, 2024 - Present
Wichita State University
BE in Computer Engineering, 2017 - 2022
IOE, Pulchowk Campus, Tribhuvan University

Experience

Associate Software Engineer

Fidenz Technologies

July 2022 – January 2024 Remote

Backend
Frontend
DevOps

Support and Solutions Intern

January 2022 – May 2022 Lalitpur, Nepal

Participated in the Hands-on Sessions on Linux System Administration, SIEM, and LogPoint architecture
Experimented with various backend storage and networking aspects of the LogPoint system
Reviewed various customer support tickets to identify major SIEM issues and solutions

NLP Research Intern

NepAl Applied Mathematics and Informatics Institute for research (NAAMII)

August 2021 – March 2022 Remote

Worked on a semi-supervised classification of Nepali tweets in eight inclusive COVID-related categories

Junior Researcher

May 2019 – March 2020 Remote

Conducted extensive research on implementing two-dimensional In-Video Advertising, emphasizing seamless integration of advertisements within platform videos to ensure a non-disruptive viewing experience.

Accomplishments

Algorithmic Toolbox

Coursera Oct 2021

See certificate

Networking Essentials

Cisco Aug 2021

See certificate

Deep Learning Specialization

DeepLearning.AI Apr 2020

See certificate

Projects

Public Discourse Analysis System

COVID tweets analysis platform that allows health decision-makers to view a real-time analysis of narratives of tweets, particularly in Nepali and Devanagari scripts.

An academic project for COVID Volunteer and Plasma Donor system assigned by the Department of Electronics and Computer Engineering, Pulchowk Campus under the subject Database Management System

Modelling a Villa

An academic project assigned by the Department of Electronics and Computer Engineering, Pulchowk Campus under the subject Computer graphics which models a villa using C++/OpenGL

Featured Publications

Rabin Adhikari, Safal Thapaliya, Nirajan Basnet, Samip Poudel, Aman Shakya, Bishesh Khanal

October, 2022 In Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, Workshop & Shared Task

COVID-19-related Nepali Tweets Classification in a Low Resource Setting

Billions of people across the globe have been using social media platforms in their local languages to voice their opinions about the various topics related to the COVID-19 pandemic. Several organizations, including the World Health Organization, have developed automated social media analysis tools that classify COVID-19-related tweets to various topics. However, these tools that help combat the pandemic are limited to very few languages, making several countries unable to take their benefit. While multi-lingual or low-resource language-specific tools are being developed, there is still a need to expand their coverage, such as for the Nepali language. In this paper, we identify the eight most common COVID-19 discussion topics among the Twitter community using the Nepali language, set up an online platform to automatically gather Nepali tweets containing the COVID-19-related keywords, classify the tweets into the eight topics, and visualize the results across the period in a web-based dashboard. We compare the performance of two state-of-the-art multi-lingual language models for Nepali tweet classification, one generic (mBERT) and the other Nepali language family-specific model (MuRIL). Our results show that the models’ relative performance depends on the data size, with MuRIL doing better for a larger dataset. The annotated data, models, and the web-based dashboard are open-sourced at https://github.com/naamiinepal/covid-tweet-classification.