Education

2018 - 2023

Ph.D. in Computer Science

🎓 Stanford University

Thesis: Graph Neural Networks for Molecular Representation Learning. Advised by Prof. Jane Doe.

2014 - 2018

B.S. in Computer Science & Mathematics

🎓 University of California, Berkeley

Graduated with Highest Honors.

Experience

2023 - Present

Postdoctoral Researcher

💼 ETH Zürich

Developing deep generative models for de novo protein design.

Summer 2021

Research Intern

💼 DeepMind

Applied reinforcement learning to chemical synthesis planning.

Skills

Programming Languages

PythonC++TypeScriptRustR

Frameworks & Tools

PyTorchJAXTensorFlowDockerGit