About me
I am a Full Stack Engineer. Based in Kathmandu, Nepal, I build production-grade systems at the intersection of software engineering and data-driven intelligence.
My engineering work spans scalable backend architectures, search and retrieval pipelines, and end-to-end ML systems trained on real-world datasets. At Ryyft, I design and maintain data pipelines using Elasticsearch and PostgreSQL that power live product features. My applied ML projects include a sentiment classification pipeline trained on 1.6 million tweets, a clinical prediction system for diabetes diagnosis, and a voice-enabled recommendation engine — each built with rigorous model evaluation and error analysis.
I am actively seeking graduate research and teaching opportunities to advance my work in machine learning, explainable AI, and intelligent systems. If you are a researcher or faculty member working in these areas, I would welcome the opportunity to connect.
Expertise & Solutions
Applied Machine Learning
Designing and evaluating end-to-end ML pipelines — from raw data preprocessing and feature engineering to model training, error analysis, and performance validation on real-world datasets.
Natural Language Processing
Building text classification and sentiment analysis systems using TF-IDF vectorization, logistic regression, and preprocessing pipelines. Experienced with large-scale datasets (1.6M+ records).
Scalable Backend & Data Systems
Architecting production-grade APIs and data retrieval pipelines using NestJS, Prisma, PostgreSQL, and Elasticsearch — with a focus on reliability, maintainability, and performance at scale.
Research & Problem Solving
Applying rigorous experimental methodology — hypothesis formation, controlled evaluation, comparative analysis — to optimize algorithms and derive actionable insights from complex datasets.