Research Intern → PhD @ IST Austria (Bronstein Group) Geometric deep learning for structural biology — generative models guided by experimental data.
Protein structure and dynamics through graph neural networks, diffusion models, and inference-time guidance with experimental constraints. I like problems where the math is clean but the biology is messy.
Previously:
- 🧲 QuantCo / Virdx — MRI denoising for prostate cancer diagnosis
- 🧬 IBS Korea — protein engineering & antibody design
- 🔭 Earlier — computer vision and representation learning
- 🎵 Electronic music — techno, melodic house, ambient
- 🥾 Long hikes and weekend trips in the Austrian Alps
- 🎾 Tennis — always down for a match
- 🇰🇷 Years spent in Korea — still miss the food, the late nights, the people
- 📐 Communications Chair @ LoG Conference — Learning on Graphs
- ☕ Coffee chats welcome
| Machine Learning | Systems / Infrastructure |
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| Development | Research / Writing |
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