I’m Bishwa Kiran, a student pursuing a bachelor's degree in Computer Science and Information Technology with a keen interest in Artificial Intelligence, Machine Learning, and Data Science.
I thrive on exploring cutting-edge technologies to create innovative solutions that bridge data and intelligence.
“Through discipline comes freedom.”
- Aristotle
Deep learning-based project for classification of breast tumors (malignant and benign) using breast ultrasound. Utilizes DenseNet for classification and U-Net for segmentation, served via a Django backend API and React frontend.
CNN-based model trained on the American Sign Language dataset, providing real-time translation through an OpenCV application.
This project focuses on fine-tuning a T5-small model on a life insurance dataset formatted in JSON with question-and-answer pairs. The goal is to enhance the model's ability to understand and generate contextually relevant answers in the life insurance domain.
From-scratch implementation and exploration of 8 machine learning models, including Linear Regression, Logistic Regression, Ridge Regression, Lasso Regression, Decision Trees, Random Forest, Naive Bayes, and SVM and 4 advanced regularization and optimization techniques (Dropout, DropConnect, Mixup, Cutmix)
This project demonstrates how to generate classical music using a Long Short-Term Memory (LSTM)-based neural network. The model is trained on MIDI files to predict sequences of notes, offsets, and durations, enabling the creation of new musical compositions.
A collection of multiple EDAs and data story telling on well known datasets.
Deep Dive into Deep Learning is a comprehensive project where I implemented 11 significant deep learning architectures from scratch. This project is designed to deepen understanding and demonstrate practical knowledge of state-of-the-art deep learning models across various domains, including computer vision, natural language processing, and generative modeling.
An ambitious project for creating and developing languages, fonts, and linguistic datasets for language translation, text-to-speech, and speech-to-text applications. Comprises Font Generation, Dataset Generation, and Community Collaboration.
This project is a License Plate Recognition System designed to identify and extract license plate information in real time using deep learning (YOLOv8) and image processing techniques.
This project uses a machine learning model to predict diseases based on input symptoms. The API provides an interface to interact with the model and retrieve detailed information about the predicted diseases, including description, precautions, medications, diet plans, and workouts.
This study evaluates state-of-the-art deep learning models like DenseNet121, EfficientNet-B1, and ResNet50 for detecting kidney abnormalities in CT scans. Transfer learning and advanced optimization techniques like Mixup and label smoothing were applied, with EfficientNet-B1 achieving perfect scores across all metrics while maintaining low computational overhead.
Utilizing transcriptomic data, this study employs machine learning models like Random Forest and XGBoost to identify novel biomarkers for Primary Ciliary Dyskinesia (PCD). Noteworthy genes such as GUCA2A, SCARB2, and ZNF91 were highlighted as potential diagnostic markers, providing insights into PCD pathogenesis.
Hi, I’m Bishwa Kiran Poudel, a student pursuing a Bachelor's degree in Computer Science and Information Technology, with a strong passion for Artificial Intelligence (AI), Machine Learning (ML), and Data Science.
I enjoy solving complex problems, building intelligent systems, and exploring innovative solutions that bridge data and technology. My journey is driven by a desire to learn continuously and stay ahead in the rapidly evolving tech landscape.
When I’m not coding or analyzing data, I’m exploring new ideas and advancements in AI and ML, aiming to create impactful solutions that make life smarter and more efficient.
Executive Member (2021) | Vice Treasurer (2022) | Vice President (2023)
Contributed actively in the planning and management of association activities and events. Oversaw financial planning as Vice Treasurer and provided strategic leadership as Vice President in 2023.
Executive Member (2019)
Assisted in organizing and executing various events aimed at promoting student involvement and development within the department.
Fielder (2022)
Participated in Github Field Day, helping with organizing and supporting various field activities and initiatives.
1st Runner Up for Project Lipi
Received 1st Runner Up position in MBM IDEAX competition for the innovative project 'Lipi,' focusing on a breakthrough solution in the field.
Certified Associate Data Analyst
Successfully completed DataCamp’s Associate Data Analyst certification, gaining expertise in data manipulation, visualization, and analysis techniques.
