Computer Vision • Machine Learning • Software Engineering
Bridging academia and technology — teaching the next generation of engineers while building intelligent systems that solve real-world problems.
I specialize in Computer Vision, Artificial Intelligence, and Machine Learning. As an IT Professor, I bridge theoretical foundations with hands-on applications — from real-time object detection with YOLO and image recognition with Vision Transformers, to building full-stack web applications. My Python expertise spans OpenCV, PyTorch, TensorFlow, Pandas, and NumPy, and I craft clean, responsive interfaces with HTML5, CSS3, JavaScript, and Bootstrap.
Areas I research, teach, and build professional solutions in.
Neural networks, deep learning architectures, and intelligent agent design.
Object detection with YOLO, image segmentation, and Vision Transformers.
Predictive modeling, data analysis, and end-to-end ML pipeline development.
Advanced Python with Django, Flask, NumPy, Pandas, and scientific computing.
Test-driven development, software testing strategies, and QA engineering.
Full-stack development, responsive web design, and system architecture.
Professional experience across AI, computer vision, and software engineering.
Developed ML pipelines for classification, regression, and clustering using Python's scientific stack. Built end-to-end prediction systems and applied models to real-world datasets.
Implemented real-time object detection using YOLO and image recognition with Vision Transformers. Worked extensively with OpenCV for preprocessing and feature extraction pipelines.
Gained hands-on experience with CI/CD pipelines, containerization, and deployment workflows at Nest Nepal's engineering team.
Completed an ML and data analytics internship at CodSoft, working on real-world datasets, building dashboards, and deploying predictive models for business insights.
Open to academic partnerships, research collaborations, and speaking opportunities.
