Computer Engineering student building end-to-end machine learning pipelines, data science workflows and production-ready Django backends — focused on AI/ML engineering, predictive analytics and scalable Python web services.
A quick picture of what I do and where I'm headed.
I'm a Computer Engineering student focused on Artificial Intelligence, Machine Learning, Data Science and Python backend development. I like problems that sit between the data and the product — training the model, then shipping it inside a backend that people can actually use.
My work spans complete ML pipelines (preprocessing, EDA, feature engineering, training, validation, evaluation), deep learning architectures from CNNs and U-Nets to RNN/LSTM/GRU and Transformers, image segmentation with OpenCV, and database-driven Django applications built on the MVT architecture.
Right now I'm focused on bridging the gap between data science and production — serving trained models through Django REST APIs, building analytics dashboards, and exploring scalable backend patterns for ML-powered applications. My code lives on GitHub.
The languages, frameworks and tools I reach for most often.
Selected work across data science, machine learning and Django backends.
A Django-powered data science application that ingests raw datasets, runs preprocessing and EDA pipelines, serves trained ML models through REST endpoints, and visualizes predictions on an interactive dashboard — combining backend engineering with end-to-end data workflows.
View on GitHubA database-driven online shopping system built on Django's MVT architecture — user authentication, product browsing, search, category filtering and product management, with models, views, URLs and templates wired to a SQLite backend.
View on GitHubComplete ML workflows — preprocessing, EDA, feature engineering, training, validation and evaluation — comparing Linear & Logistic Regression, Random Forest, SVM, KNN, Gradient Boosting and XGBoost across regression and classification tasks.
View on GitHubImage preprocessing and segmentation techniques for extracting structure from raw image data — global and Otsu's thresholding, adaptive thresholding, filtering and image enhancement.
View on GitHubWhere the foundations came from.
Certification · CodeIt
Certification · IBM
Everest Engineering College, Pokhara University, Nepal