Zachary Wu

Zachary Wu is a Senior Research Scientist at DeepMind, focusing on protein-related problems and the application of machine learning to molecular science.1 Here's a comprehensive overview of his background and expertise:

Education and Academic Background

Zachary Wu holds a PhD in Chemical Engineering from Caltech, where he studied under Frances Arnold's group from 2015 to 2020.12 During his doctoral research, he developed methods applying machine learning for protein engineering and generated functional peptides using transformers.1 Prior to his PhD, he earned a Bachelor's degree in Chemical Engineering from Cornell University.2

Professional Experience

DeepMind Career::

• Joined DeepMind in July 2020 as a Research Scientist2
• Promoted to Senior Research Scientist in May 20232
• Works on protein-focused problems, leveraging artificial intelligence for molecular modeling and design1

Previous Work Experience::

• Applied Scientist Intern at Amazon Web Services (AWS) in 20192
• Biomolecular HTS Intern at Regeneron Pharmaceuticals, Inc. in 20152
• Process Engineering Intern at Kraft Foods Group in 20142
• Undergraduate Researcher at DeLisa Research Group, Cornell University from 2013 to 20152

Research Contributions

Zachary Wu has made significant contributions to the field of protein engineering and machine learning applications in molecular sciences:

1. Co-authored a highly cited paper on protein structure prediction for the human proteome using AlphaFold3
2. Published work on machine learning-guided directed evolution for protein engineering3
3. Developed methods for protein sequence design using deep generative models3
4. Contributed to research on signal peptides generated by attention-based neural networks3

Skills and Expertise

• Protein engineering and biomolecular modeling3
• Machine learning applications in molecular sciences3
• Directed protein evolution3
• High-throughput screening techniques2
• Process development and optimization2

Zachary Wu's research focuses on combining advanced machine learning techniques with molecular biology to push the boundaries of protein engineering and drug discovery.