Biography
I am a Full Stack Developer with a broad passion for software development and building high-quality applications. Currently, I’m working on an offline desktop application that delivers real-time AI feedback for echocardiography, combining modern frontend technologies—Next.js, React, TypeScript, Preact, Astro, and Tailwind CSS—with Express.js and Django backends to create seamless and reliable user experiences in demanding environments.
My background includes a Bachelor’s degree from London Metropolitan University and extensive experience designing and optimizing high-performance web applications. At Avinto AS, I led development teams building robust solutions with the MERN stack, Next.js, and Astro, focusing on improving performance, mentoring developers, and delivering impactful features.
In addition to my core software development expertise, I am pursuing MSc Artificial Intelligence to broaden my technical skill set. I enjoy integrating these insights into my development work, creating solutions that are both innovative and practical.
I enjoy tackling complex challenges across the full stack, from frontend UI design and responsive layouts to backend API integration and performance optimization. My approach is grounded in strong technical skills, attention to detail, and a commitment to delivering practical, efficient software solutions.
Outside of work, I explore new frameworks, UI component libraries, and open-source projects, always eager to expand my knowledge and keep up with the latest trends in software development. My goal is to continue creating innovative and reliable applications that solve real-world problems across diverse domains.
Qualifications
- Artificial Intelligence, University of West London, London, United Kingdom, MSc (Ongoing)
- B.Sc. in Computing, London Metropolitan University
Supervisors
Professor Massoud Zolgharni, Dr. Nasim Dadashiserej
Research Projects
Research Interests
- Blood Disease detection using Deep Learning
- Integration of AI with modern web and desktop technologies
- Explainable and ethical AI
- Human-centered AI and user experience in clinical applications