CV

Curriculum Vitae and professional background

πŸ“„ Curriculum Vitae

Professional background and academic achievements

πŸ“₯ Download CV (PDF)

Industrial Experience

🏒 Samsung (Summer '24)

ML Research Scientist - Advanced Materials Lab

End-to-end discovery of solid-state battery electrolyte materials - from generative models to experimental validation.

Key Takeaway: Battery & semiconductor material synthesis challenges

πŸš€ Orbital Materials (Summer '23)

ML Research Intern - Early-stage startup

Generative foundation model for material design focusing on porous materials applications.

Key Takeaway: ML engineering, startup dynamics, business & VCs

πŸ€– Meta AI (Summer '22)

Research Intern - AI Research

Atomic foundation model across molecules, materials, and proteins. Contributed to OC22 dataset and SCN model.

Key Takeaway: Large-scale AI training & ML engineering

Academic Research Experience

πŸŽ“ Carnegie Mellon University

PhD Student (2020-2024)

Machine learning for materials discovery under Prof. John Kitchin and Prof. Zachary Ulissi.

🌍 Columbia University

Research Intern (2019)

Air quality modeling with Prof. Faye McNeill using machine learning methods.

πŸ‡ΈπŸ‡¬ National University of Singapore

Research Intern (2018)

Protein motif identification with Prof. Duane Loh using deep learning approaches.

Skills & Technologies

πŸ€– Machine Learning

PyTorch, Graph Neural Networks, Diffusion Models, Multi-task Learning, Transfer Learning

βš—οΈ Materials Science

DFT, Molecular Dynamics, Catalysis, Battery Materials, Computational Chemistry

πŸ’» Programming

Python, CUDA, High-Performance Computing, Data Analysis, Scientific Computing

πŸ“§ Contact for Opportunities

For detailed CV, references, or collaboration opportunities, please reach out via email.