AbdulkadirUgas
Software Eng

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

  • πŸ“±Swift
  • β˜•Java
  • βš›οΈReact Native
  • 🌐JavaScript
  • βš›οΈReact.js
  • β–³Next.js
  • 🟒Node.js
  • πŸ–₯️Laravel
  • πŸ”—GraphQL
  • πŸ—„οΈSQL
  • πŸƒMongoDB
  • 🎨Tailwind CSS
  • Machine Learning & AI

  • 🐍Python
  • πŸ”₯PyTorch
  • 🧠TensorFlow
  • πŸ“ŠScikit-learn
  • 🐼Pandas
  • πŸ”’NumPy
  • πŸ‘οΈOpenCV
  • πŸ”YOLO
  • πŸ”„Vision Transformers
  • πŸ•ΈοΈCNN
  • βœ‚οΈImage Segmentation
  • πŸ“¦Object Detection
  • πŸ¦™LLM
  • πŸ”„Transformers
  • πŸ€—Hugging Face
  • βš™οΈFine-tuning
  • πŸ’‘Prompt Engineering
  • πŸ”RAG
  • πŸš€FAISS
  • 🎨ChromaDB
  • 🌲Pinecone
  • πŸ“Embeddings
  • 🎯Vector Search
  • ⛓️LangChain
  • πŸ”¨LangSmith
  • πŸ“‰Quantization
  • βœ‚οΈModel Pruning
  • πŸ—œοΈModel Compression
  • 🐳Docker
  • ⚑FastAPI
  • πŸ“ŠMLflow
  • 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

    Monitoring & Evaluation Data Analyst

    Dec 2023 - Sep 2024

    As a Monitoring & Evaluation Data Analyst at JUBA Foundation, I developed comprehensive data analytics solutions to measure program effectiveness and impact. I created data cleaning scripts and validation processes to ensure data quality and integrity across all development programs. My responsibilities included designing statistical models and performing regression analysis to quantify program outcomes, calculating optimal sample sizes for representative data collection, and establishing real-time monitoring dashboards using Power BI. I collaborated with field teams to implement mobile data collection methodologies and established robust data security protocols to protect sensitive program information.

    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

    Nextjs

    Beecbile an ecommerce website

    Key features:

    Server-Side Rendering (SSR)

    Cache Control and CDN Integration

    Bundle Analysis and Optimization

    Python, LLaMA, RAG, FastAPI, Flask

    Multi-Agent AI framework for International Student Support

    Key features:

    Multi-agent architecture with specialized domain agents

    Fine-tuned LLaMA 3.2 with LoRA for domain adaptation

    Retrieval-Augmented Generation (RAG) pipeline

    LLM and RAG Evaluation using RAGAS and LangSmith

    Deep Learning

    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)

    Computer Vision, NLP

    AI-powered system analyzing beef quality through image processing and customer sentiment analysis

    Key features:

    Computer vision pipeline for marbling assessment

    Korean-language sentiment analysis

    Daily review scraping from major e-commerce platforms

    CNN-based texture and fat distribution analysis

    Python, Power BI, Statistical Analysis

    Data analysis and monitoring system for development programs effectiveness

    Key features:

    Real-time monitoring dashboards

    Statistical modeling for impact measurement

    Data quality validation processes

    Mobile data collection integration

    Get In Touch

    Seeking software development and ML opportunities

    Contact me!