Overview
Our faculty are at the forefront of developing transformative AI and machine learning methods that are reshaping basic biological research and its applications. This group pioneers novel computational frameworks—from deep generative models for protein engineering and genomic language models that predict functional effects of genetic variants, to machine learning methods for deciphering gene regulation and RNA processing, probabilistic models for evolutionary inference, and algorithms for CRISPR guide design and therapeutic development. Rather than merely applying existing AI tools, our researchers develop innovative algorithms and models designed specifically for the unique complexities of biological systems.
The real-world impact spans human health (improving CRISPR gene editing, predicting disease risk from genetic variants, designing proteins with therapeutic properties), agriculture (engineering climate-resilient crops), and biotechnology (accelerating drug discovery and protein design). Research in this area drives cutting-edge advances in machine learning and statistical theory while tackling challenges that matter—from developing computational tools that guide and accelerate laboratory experiments to creating frameworks that integrate genomic, evolutionary, and molecular data for precision medicine. With Berkeley's unparalleled resources in computation and biology, collaborations across campus, and partnerships with leading biotech companies, this work creates the next generation of AI methods that translate directly into solutions for pressing biological challenges.
Primary Faculty
- Steven Brenner, Professor, Departments of PMB, MCB, and Bioengineering
- Sandrine Dudoit, Professor, Department of Statistics and Division of Biostatistics
- Haiyan Huang, Professor, Department of Statistics
- Ian Holmes, Professor, Department of Bioengineering
- Anthony Joseph, Professor, Department of EECS
- Liana Lareau, Associate Professor, Departments of Bioengineering and MCB
- Jennifer Listgarten, Professor, Department of EECS
- Yun S. Song, Professor, Departments of EECS and Statistics
- Max Staller, Assistant Professor in Residence, Department of MCB
- Allon Wagner, Assistant Professor, Departments of EECS and MCB
- Jingshen Wang, Associate Professor, Division of Biostatistics
- Bin Yu, Professor, Departments of Statistics and EECS
Secondary Faculty
- Nicholas Ingolia, Professor, Department of MCB
- Priya Moorjani, Associate Professor, CCB and Department of MCB
- Rasmus Nielsen, Professor, Departments of Integrative Biology and Statistics
- Elizabeth Purdom, Associate Professor, Department of Statistics
- Peter Sudmant, Associate Professor, Department of Integrative Biology
- Ashley Wolf, Assistant Professor, CCB and Division of Infectious Diseases and Vaccinology
Affiliated Faculty
- Teresa Head-Gordon, Professor, Departments of Bioengineering, Chemistry, and CBE
Professor of the Graduate School
- Michael Jordan, Professor Emeritus, Departments of EECS and Statistics