Hey there!
I'm Abdulkadir, a software developer and machine learning enthusiast based in South Korea.
My passion for programming started in high school back in 2012. I earned my Bachelor's in Computer Science and am currently on the exciting journey of completing my Master's in Big Data.
With over five years of experience, I've developed web and mobile applications for clients across various countries and industries
Here are some of the technologies with which I am most familiar:
Web & Mobile Development
Machine Learning & AI
Experience
Big Data Lab Researcher
Sep 2023 - current
As a Master’s degree student at Chungbuk National University (CBNU), I am actively engaged in cutting-edge research within the Big Data Lab. My work focuses on leveraging machine learning (ML) and computer vision techniques to advance laboratory projects. I collaborate with a team of researchers to train models, develop APIs, and implement concepts from research papers. I contribute to the integration of computer vision applications, including skin cancer detection, object detection, and projects involving large language models (LLMs) and Retrieval-Augmented Generation (RAG). This role has enabled me to deepen my technical expertise in ML frameworks, data processing tools, and advanced programming
App Developer
May 2018 - Aug 2022
I have been actively involved in developing and implementing various mobile applications as an app developer. In this role, I have effectively utilized my technical knowledge and creativity to create user-friendly and feature-rich apps tailored to our clients' specific requirements. Working alongside a talented team of designers, developers, and project managers, we have successfully delivered exceptional applications that exceeded our customers' expectations. Additionally, I transitioned to remote work in 2020, continuing my app development journey remotely.
Projects
Beecbile an ecommerce website
Key features:
Server-Side Rendering (SSR)
Cache Control and CDN Integration
Bundle Analysis and Optimization
RAG-Powered LLaMA for International Student Support
Key features:
Fine-tuned LLaMA with LoRA for domain adaptation
Efficient document retrieval using PINECONE for vector search
FastAPI for backend API to handle queries
Flask for front-end integration
Deep learning–based skin lesion image analysis for early detection of skin cancer.
Key features:
Convolutional Neural Networks (CNN) for feature extraction
Transfer Learning with EfficientNet-B7 and Vision Transformer (Eva-02)
Utilization of large-scale datasets (ISIC 2018 and 2024)
Get In Touch
Seeking software development and ML opportunities
Contact me!