Bryan J. Winn, MD, is a Clinical Professor of Ophthalmology at UCSF and Chief of Ophthalmology at the San Francisco Veterans Affairs Medical Center. He is board-certified in Ophthalmology and a fellow of the American Society of Ophthalmic Plastic and Reconstructive Surgery (ASOPRS), specializing in the medical and surgical management of eyelid, lacrimal, and orbital disorders, as well as aesthetic rejuvenation of the face.

The translational research in my lab bridges basic and clinical investigation by engaging genomic technologies to understand relationships between microbes, host response and clinical outcomes. We study lower respiratory tract infections, ARDS, sepsis, nosocomial infections, and emerging pathogens including SARS-CoV-2. One focus area involves developing new diagnostic techniques that combine metagenomic sequencing and machine learning to simultaneously profile both host and microbiome from clinical samples.

Dr. Renuka Nayak, MD, PhD, is a physician-scientist dedicated to advancing the care and treatment of patients with rheumatologic conditions such as rheumatoid arthritis, lupus, psoriatic arthritis, and other autoimmune diseases. She uses her unique backgrounds in Biology, Computer Science, and Clinical Rheumatology to investigate the role of the human gut microbiome in the treatment of rheumatoid arthritis.

Dr Waubant trained as a neurologist in Toulouse, France. She continued her training as a neuroimmunology fellow in Dr Stephen Hauser’s UCSF laboratory, focusing on matrix metalloproteinases (MMP) and their tissue inhibitors (TIMP), and their role in migration of lymphocytes through equivalents of the blood-brain barrier. In 1994, Dr Waubant returned to Toulouse to complete her 2-year junior faculty/chief residency in neurology. Dr Waubant later returned as a clinical research fellow at the UCSF MS Center with Dr Donald Goodkin.

Research Interests: Bronchial hyperreactivity in asthma. Effects of viral infection on airway function. Regulation of airway mucous secretion and vascular permeability.

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.