Introduction
I began my journey with a deep passion for computer science, which led me to pursue a Bachelor's degree in Computer Science and Engineering at AUST in 2022. From the very beginning of my academic career, I immersed myself in competitive programming, sharpening my problem-solving skills and building a solid foundation in algorithms and data structures.
Alongside my academic studies, I actively worked on various projects, experimenting with different programming languages and frameworks. This hands-on experience allowed me to gain practical knowledge in web development and software engineering.
However, as I delved deeper into the world of technology, I became increasingly fascinated by the field of Computer Vision, Image Processing, and Explainable AI. Driven by this passion, I decided to shift my focus towards AI research and development.
Currently, I am in my final year, specializing in Image Processing for my thesis. I am exploring advanced techniques and working on innovative solutions to push the boundaries of AI in visual recognition and analysis.
Alongside my academic studies, I actively worked on various projects, experimenting with different programming languages and frameworks. This hands-on experience allowed me to gain practical knowledge in web development and software engineering.
However, as I delved deeper into the world of technology, I became increasingly fascinated by the field of Computer Vision, Image Processing, and Explainable AI. Driven by this passion, I decided to shift my focus towards AI research and development.
Currently, I am in my final year, specializing in Image Processing for my thesis. I am exploring advanced techniques and working on innovative solutions to push the boundaries of AI in visual recognition and analysis.
- [July 2026] Spectral-Spatial Mamba with Uncertainty-Guided Refinement for Thyroid Nodule Diagnosis got published in Array (Elsevier)!
- [June 2026] HyFormer-Net for Breast Lesion Analysis got published in Intelligence-Based Medicine (Elsevier)!
- [June 2026] MedSaab-US: A Backpropagation-Free Multi-Scale Wavelet-Saab Framework for Thyroid Nodule Segmentation in Ultrasound Images was accepted at IEEE ICIP 2026 Satellite Workshop!
- [June 2026] RadiomicNet: A Hybrid Radiomics-Guided Lightweight Architecture for Interpretable Medical Image Segmentation was accepted at IEEE ICIP 2026 Satellite Workshop!
- [February 2026] Abstract accepted for a book chapter in AI for Medical Imaging and Precision Diagnostics: From Theory to Practice (Routledge, Taylor & Francis Group)!