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kaopanboonyuen.github.io

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All about Kao Panboonyuen

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# 👋 Welcome to **Kao Panboonyuen’s GitHub Page**

🚀 Representation Learning • Diffusion Models • Geospatial AI

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This repository serves as my **personal research and engineering workspace**, collecting projects, prototypes, and research artifacts at the intersection of:

- 🧠 **Representation Learning & Generative Models**
- 🌫️ **Diffusion Models & Stochastic Processes**
- 📐 **Optimization Theory for Deep Learning**
- 🌍 **Geospatial AI & Remote Sensing at Scale**

My work emphasizes **mathematically grounded AI systems**—where optimization theory, probabilistic modeling, and geometric structure are treated as first-class design principles, not afterthoughts.

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## 🧠 Research Focus

I am particularly interested in:

- **Latent-space optimization** for generative models  
- **Diffusion-based inverse problems** (inpainting, restoration, uncertainty-aware generation)  
- **Kernel methods and adaptive optimization** in high-dimensional spaces  
- **Scalable learning for very high-resolution (VHR) satellite imagery**

These themes sit at the boundary between **theory-driven AI** and **large-scale real-world deployment**.

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## ✨ Research Philosophy

> *“Good AI systems emerge when optimization, probability, and geometry are treated explicitly—not hidden behind heuristics.”*

I value:
- 📐 **Mathematical rigor in model design**
- 🧪 **Reproducible, inspectable experiments**
- 🏗️ **Systems that scale beyond toy benchmarks**
- 📖 **Clear articulation of assumptions and limitations**

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## 🛠️ Technical Scope

- **Core Stack**: Python, PyTorch  
- **Modeling**: Diffusion Models, Latent Variable Models, Kernel Methods  
- **Theory**: Optimization, Stochastic Processes, Probabilistic Inference  
- **Domains**: Computer Vision, Remote Sensing, Geospatial Intelligence  
- **Systems**: GPU inference pipelines, research-to-production workflows

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## 🙏 Credits & Acknowledgements

This site is built using **[Hugo](https://gohugo.io)**.

The structure and academic layout are inspired by **[Natasha Jaques](https://natashajaques.com)** and the **[Wowchemy Academic Template](https://github.com/wowchemy/starter-hugo-academic)**, with custom extensions to **[wowchemy-hugo-modules](https://github.com/wowchemy/wowchemy-hugo-modules)**.

Grateful to the open research community for advancing transparent and rigorous AI 🌍

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## 🤝 Let’s Connect

I’m always open to discussions around:
- Diffusion models & generative learning  
- Optimization and representation learning  
- Research collaboration & applied AI systems

📩 **Email**: panboonyuen.kao [at] **gmail** **dot** com

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**Teerapong Panboonyuen (Kao)**  
ธีรพงศ์ ปานบุญยืน (เก้า)

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