Rushika Perera, PhD

Associate Professor

In our lab we study how autophagy and the lysosome regulate the response to cellular stress to promote cancer progression.

Katie Pollard, PhD

Professor in Residence
Epidemiology & Biostatistics

The Pollard lab develops statistical and computational methods for the analysis of massive biomedical datasets. Our research focuses on emerging technologies for genomics, mass spectrometry, and imaging. We specialize in evolutionary and comparative approaches, including machine-learning integration of diverse types of data and longitudinal models of dynamics in disease and development. Examples of current projects are massively parallel dissection of regulatory networks and decoding cryptic variation in the human microbiome.

Kira Poskanzer, PhD

Associate Professor
Biochemistry and Biophysics

Nadia Roan, PhD

Professor in Residence

The Roan Lab studies how intracellular and extracellular factors in the tissue microenvironment can affect infection by HIV, mucosal immunity, and reproductive health. We have demonstrated that genital and rectal fibroblasts, amongst the most abundant cells of the mucosa, potently increase HIV infection of T cells through at least two distinct mechanisms: promoting viral entry, and altering the cellular state of T cells to render them more permissive to viral replication.

Dorit Ron, PhD

Professor In Residence

Dr. Ron is a Professor in the Department of Neurology at UCSF, and is a member of the Neuroscience Graduate Program. She is also the Endowed Chair in Cell Biology of Addiction in Neurology at UCSF, the Director for a P50 NIH-NIAAA Center Grant. She is a recipient of several NIH RO1 and DOD grant awards. In 2013, Dr. Ron received and NIH MERIT. She has served as an Associate Editor for the Journal of Neuroscience and is currently a reviewing editor for Addiction Biology, the Alcohol Journal, as well as a field editor for Alcoholism: Clinical and Experimental Research. Dr.

Rada Savic, PhD

Vice Dean & Professor

My research uses computational methods to study the dynamic interplay between disease progression, treatment regimen, and drug and biomarker response across relevant scales (molecule, cell, tissue, organ & whole body) to determine causal links underlying variability in (safety and efficacy) clinical outcomes. By integrating multi-scale, and multi-level clinical data, we aim to determine the right dose, schedule, and treatment duration of various therapies, potentially bringing novel, precise and personalized treatment options to patients with unmet need more quickly.

Licia Selleri, PhD, MD

Orofacial Sciences

UCSF School of Medicine
Department of Anatomy
Institute of Human Genetics
Eli and Edythe Broad Center of Regeneration Medicine & Stem Cell Research

Genetic and regulatory control of morphogenesis in embryonic development, evolution, and disease

Marina Sirota, PhD

Assoc Professor in Residence

Marina is currently an Assistant Professor at the Bakar Computational Health Sciences Institute at UCSF. Prior to that she was the Lead Research Scientist in the Division of Systems Medicine at Stanford University and has worked as a Senior Research Scientist at Pfizer where she focused on developing Precision Medicine strategies in drug discovery. She completed her PhD in Biomedical Informatics at Stanford University, where her graduate work focused on predicting drug-disease relationships based on gene expression to identify novel therapeutic indications for known drugs.

Thea Tlsty, PhD


Dr. Tlsty has over 25 years of experience in studying human cells and the earliest responses to injury. She has lead multi-disciplinary groups that address both the epithelial and stromal contributions to wound healing and malignancy. The model systems the Tlsty laboratory has developed and the applied translational insights obtained have great potential to contribute to clinical utility.

Susan Voglmaier, MD, PhD

Assoc Professor in Residence

Rong Wang, PhD



Lauren Weiss, PhD

Professor In Residence

My laboratory focuses on understanding the genetic architecture of autism. We are working with genome-wide genetic data to identify additional susceptibility loci, the genetic mechanisms by which DNA variants influence autism risk, and the genetic and physiological pathways these risk loci implicate. We can use rich genetic datasets to ask questions about the role for copy number vs. SNP variation, rare vs. common variation, gene-sex interaction, gene-gene interaction, and gene-environment interaction.