About

About

Youngung Han, Ph.D candidate

Dedicated to solving complex, real-world challenges by leveraging mathematical frameworks and advanced computational methods.
Driven by the potential of data and algorithms to create tangible impact and innovation.

Areas of Interest

My focus lies at the intersection of theoretical foundations and high-impact applications, particularly in the following domains:

Medical AI

  • Objective: To develop and deploy robust machine learning models that enhance diagnostic accuracy and efficiency in healthcare systems.
  • Focus Areas: Medical Imaging Analysis, Predictive Modeling, Clinical Data Mining.

Industrial AI

  • Objective: To bring vision and multimodal models into real-world industrial environments for safety monitoring, inspection, and quality control.
  • Focus Areas:
    • Visual Intelligence: Anomaly & Defect Detection, Real-time Multi-channel Inference, Vision-Language Models (VLM) for Safety-Critical Systems.
    • Predictive Maintenance, Fault Diagnosis, Time-Series Analysis, Industrial Inspection & Monitoring.

Railroad Science

  • Objective: To apply data-driven approaches to railway systems and transportation networks for improved safety and efficiency.
  • Focus Areas:
    • Logistics Optimization: Routing Algorithms, Demand Forecasting, Inventory Management, Network Optimization.
    • Supply Chain Management (SCM), Operations Research, Mathematical Modeling.

Computer Science

  • Objective: To design efficient algorithmic solutions and deepen understanding of the mathematical principles underlying computation.
  • Focus Areas:
    • Algorithms: Algorithm Design, Data Structures, Competitive Programming, Computational Complexity.
    • Mathematics: Linear Algebra, Optimization Theory, Probability, Discrete Mathematics.

AI & Tech Writing

  • OUTTA AI Tech Blog
    • Regularly publishing in-depth articles on Generative AI, LLMs, and Computer Vision.
    • Making complex AI concepts accessible to a broader audience.

Generative AI

  • 2025 OUTTA Gen AI
    • Comprehensive curriculum and resources for Generative AI study.
    • Covering foundational theories to advanced application development.

Problem Solving

  • Algorithm & Problem Solving
    • Archive of solutions for algorithmic problems (Baekjoon, Programmers).
    • Focus on code optimization and algorithmic efficiency.
  • LeetCode Hub
    • Collection of LeetCode solutions with detailed explanations.
    • Tracking progress and patterns in competitive programming.

Activities & Affiliations

I actively engage in organizations to broaden my expertise, collaborate on challenging projects, and contribute to the community.

Research & Development

  • OUTTA AI
    • Contributing to a non-profit organization dedicated to democratizing AI education and fostering research.
    • Involved in AI research initiatives aiming for publications in top-tier conferences (e.g., NeurIPS, MICCAI) and supporting community learning programs.
  • WaffleStudio
    • Developing practical software engineering capabilities through the full lifecycle (planning, development, deployment) of web and application services.

Academic Societies

Selected Publications

  • LOSA-NET: A LOCALIZED AND SCALE-ADAPTIVE NETWORK FOR BOUNDARY-SENSITIVE PREDICTION OF PERINEURAL INVASION IN 3D MRI - IEEE ISBI 2026 (Oral)
  • MMA-FORMER: MULTI-WINDOW MIXTURE-OF-HEAD ATTENTION TRANSFORMER FOR ADAPTIVE PNI PREDICTION IN 3D MRI - IEEE ISBI 2026 (Oral)
  • NeoNet: An End-to-End 3D MRI-Based Deep Learning Framework for Non-Invasive Prediction of Perineural Invasion via Generation-Driven Classification - Workshop on Health Intelligence (W3PHIAI), AAAI 2026 (Oral)

📚 Full publication list on my Google Scholar.