I'm a freelance Machine Learning Engineer and Full-Stack Developer based in Munich, Germany, with extensive experience in computer vision, 3D medical imaging, and deep learning. I excel at building end-to-end AI solutions, full-stack web applications, and mobile apps, leveraging a wide range of technologies. My passion lies in solving real-world problems through innovation, and I’m constantly exploring new tools—including Large Language Models (LLMs)—to expand my expertise across software engineering domains.

• Languages: Python, Dart, C#, Java, C++, CAPL, JavaScript, C
• Frameworks: PyTorch, Flutter, ReactJS, NextJS, Flask, FastAPI
• Infrastructure & DevOps: Docker, AWS, GCP
• Collaboration & Version Control: Git, GitHub, GitLab, Notion, Slack, Jira, Figma, ClickUp
• Specializations: Computer Vision, 3D Medical Imaging, Deep Learning, Large Language Models (LLMs), Full Stack Development, App Development
• Spoken Languages: Korean (Native), English (Fluent), German (Intermediate)

• TranscribeTube: A Python tool for transcribing videos from local files or YouTube links using Hugging Face models, with a Gradio web interface.
• Perfect Shapes Game: A mobile game I developed and published on the App Store, built with Flutter for iOS, focusing on engaging shape-matching gameplay.
• Who Wins: An interactive iOS app I created and published, leveraging Flutter to deliver a fun, competitive experience.
• Pytorch_AdversarialAttacks: PyTorch implementation of segmentation models and adversarial attacks for medical imaging research.

• Robustification of Segmentation Models Against Adversarial Perturbations in Medical Imaging (2020)
  International Workshop on PRedictive Intelligence In MEdicine (PRIME)
  Introduced a novel defense framework for segmentation models in medical imaging against adversarial attacks, outperforming existing methods.
• Toward Optimal FPGA Implementation of Deep Convolutional Neural Networks for Handwritten Hangul Character Recognition (2018)
  Journal of Computing Science and Engineering (JCSE)
  Developed an FPGA-based DCNN accelerator for real-time Hangul character recognition, achieving superior energy efficiency over CPU and GPU solutions.

• Email: zerg468@gmail.com
• LinkedIn: linkedin.com/in/hanwool-park

Interested in freelance opportunities or collaboration? I bring hands-on experience in AI, full-stack development, and app publishing to the table. Whether it’s building innovative LLM-powered solutions, crafting mobile apps, or tackling complex machine learning challenges, feel free to reach out—I’d love to discuss how I can contribute to your project!