Katie Pollard and her team develop models that enable them to decode how genomes work, evolve, and break in disease. Their analyses of massive sets of genomic and epigenomic data include investigating human genetic variation, understanding what makes humans unique compared to other species, and characterizing the genomic diversity of the human microbiome, the group of bacteria that populate our digestive system and other body sites. An evolutionary focus, coupled with rigorous statistical methods and bioinformatics tool development, gives the lab a unique perspective on human biology and disease.

Disease Areas

Congenital Heart Defects
Genetic Diseases
Infectious Diseases
Inflammatory Bowel Disease and Other Microbiome-Related Diseases
Neurodegenerative Diseases
Psychiatric Diseases

Areas of Expertise

Data Science
Developmental Biology
Genome Evolution
Machine Learning/AI
Technology Development
Working in the Pollard lab

Lab Focus

Creating tools for genomic data analysis that combine statistical rigor, an evolutionary perspective, and massive integration of public data.
Using AI and other predictive computational models to gain a mechanistic understanding of human biology.
Identifying the genetic basis for human traits and diseases.
Characterizing the human microbiome through metagenomic data analysis.
Designing biomedical research technologies to optimize what we can learn from them.
Science communication and education.

Research Impact

Pollard pioneered a statistical approach to identify the fastest-evolving regions of the human genome, known as Human Accelerated Regions (HARs). Her team showed that many of these correspond to non-coding sequences controlling the expression of genes important for development and associated with psychiatric disorders. The lab also used machine learning to reveal the importance of DNA shape and folding in gene regulation. These studies have generated research tools for studying human disease that are yielding novel therapeutic targets.

Pollard has also designed metagenomic-based methods to study the human microbiome at the resolution of individual genes and genetic mutations. From these studies, novel insight will arise into the relationship of the microbiome to health and disease, setting the stage for using metagenomics in precision medicine.

The Pollard Lab’s open-source code for gene expression analysis, detecting evolutionary conservation and acceleration, and quantifying genetic changes in the human microbiome is used in thousands of labs and classrooms.


Professional Titles

L.K. Whittier Director, Gladstone Institute of Data Science and Biotechnology

Senior Investigator, Gladstone Institutes

Professor, Department of Epidemiology and Biostatistics, UC San Francisco

Investigator, Chan Zuckerberg Biohub San Francisco


Computational biology, which empowers scientists to draw new insights from massive amounts of data, is Katie Pollard’s métier. She earned her PhD in biostatistics at UC Berkeley, then completed a postdoctoral fellowship at UC Santa Cruz, where she worked with David Haussler, the renowned bioinformatician who led the team that assembled the first human genome sequence. During her fellowship, Pollard discovered rapidly evolving regions in the human genome that may help explain the emergence of brain capabilities unique to humans and may also point to their vulnerability to neurological diseases. After serving as an assistant professor at UC Davis, Pollard joined Gladstone in 2008. She was appointed founding director of the Gladstone Institute of Biotechnology and Data Science in 2018.

In her work, Pollard designs computer programs that can test a million or more hypothetical experiments in a day to predict outcomes. This approach helps identify and prioritize which research avenues performed in a lab are most likely to lead to success, increasing efficiency and speeding discovery.

Her team is recognized for both its rigor to the field of genomics and for its generosity: the open-source software they create is readily shared with scientists around the world. Pollard herself is a dedicated mentor who takes pride in equipping women and other underrepresented groups in science with the skills and training to launch successful careers—and encourages them to extend the practice to the next generation.

Pollard also lends her expertise as an advisor to research programs across the country, including those at the Simons Foundation, The Rockefeller University, and Stanford University, and to biotechnology companies such as Phylagen and Tenaya Therapeutics.

What are you most excited about in your lab right now?

“It is such a thrill that we can now rapidly screen trillions of causal hypotheses about genetic diseases using AI models built in our lab This pushes us to take risks and enables us to prioritize the experiments that are most likely to yield new discoveries.”

Katie Pollard, PhD

Honors and Awards

2023 Fellow, American Association for the Advancement of Science

2022 Elected member, National Academy of Medicine

2021 Fellow, American Institute for Medical and Biological Engineering

2020 Fellow, International Society for Computational Biology

2018 Named to “San Francisco Business Times’” list of “Women Who Lead in the Life Sciences”

2018 Named to UC Berkeley School of Public Health’s list of “75 Most Influential Alumni”

2017 Named a Chan-Zuckerberg Biohub Investigator

2013 Fellow, California Academy of Sciences

2013 Alumna of the Year, UC Berkeley School of Public Health

2013 Best Scientific Visualizations of the Year, “Wired” Magazine

2009 Breakthrough Biomedical Research Award, UC San Francisco

2008 Sloan Research Fellowship, Alfred P. Sloan Foundation

2007 Faculty Development Award, UC Davis

2003 Evelyn Fix Memorial Prize, Chin Long Chiang Biostatistics Student of the Year, UC Berkeley

1998 Berkeley Fellowship, UC Berkeley

1996 Thomas J. Watson Fellowship, Watson Foundation

1995 Valedictorian, High Scholarship Prize, Math Prize, Anthropology Prize, Phi Beta Kappa Award, Pomona College

1993 Sophomore Math Prize, Pomona College



Katie Pollard

Lab Members

Cindy Barrios
Graduate Student
Annamarie Bustion
Shiron Drusinsky
Graduate Student
Veronika Dubinkina, PhD
Bioinformatics Fellow
Amanda Everitt
Graduate Student
Sandy Floren
Rotation Student
Katie Gjoni
Graduate Student
Miriam Goldman
Graduate Student
Laura Gunsalus
Alisha Holloway, PhD
Zhirui Hu, PhD
Bioinformatics Fellow
Xiaofan Jin, PhD
Ryan Keivanfar
Graduate Student
Beniamin Krupkin
Rotation Student
Shuzhen Kuang, PhD
Bioinformatics Fellow
Jodi Lee
Graduate Student
Abigail Lind, PhD
Calla Martyn
Cindy Pino
Graduate Student
Maureen Pittman
Pawel Przytycki, PhD
Ashvin Ravi
Rotation Student
Jason Shi, PhD
Byron Smith, PhD
Bioinformatics Fellow
Sean Whalen, PhD
Senior Staff Research Scientist
York Zhang, MS
Rotation Student
Xinru Zhang
Shu Zhang
Graduate Student
Chunyu Zhao, PhD
Visiting Scientist