Primary Faculty

All A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

Shyam Visweswaran, MD, PhD

Associate Professor, Department of Biomedical Informatics

Associate Professor of Intelligent Systems, Clinical and Translational Science, and Computational Biology

Director of Clinical Informatics, Department of Biomedical Informatics

Director of the Data Enabled Clinical Informatics Center (DECIC)

Director of the Biomedical Informatics Core, Clinical and Translational Science Institute

Biomedical Informatics Training Program Core Faculty

University of Pittsburgh School of Medicine

Application of artificial intelligence and machine learning to problems in the Learning Health System with a specific focus on learning electronic medical record (EMR) and computerized clinical decision support, precision medicine and personalized modeling, data mining and causal discovery from genomic and biomedical data, and enabling reuse of EMR data and research data warehousing.

Michael M. Wagner, MD, PhD

Vice Chairman, Population Informatics
Director, RODS Laboratory
Professor of Biomedical Informatics and Intelligent Systems
Biomedical Informatics Training Program Core Faculty
University of Pittsburgh School of Medicine
Dr. Wagner’s research focuses on real-time methods for detecting and characterizing disease outbreaks, including the development and testing of operational biosurveillance systems. In his role as director of the RODS Laboratory, Dr. Wagner led the development and implementation of two widely used biosurveillance systems: the RODS system and the National Retail Data Monitor (NRDM). Currently, Dr. Wagner is developing a third system called BioEcon. BioEcon is a decision analytic tool for use by analysts working in health departments. BioEcon is a logical extension of Dr. Wagner’s research in biosurveillance. BioEcon addresses the problem of what is the optimal action to take in response to incoming biosurveillance data.

Erik S. Wright, PhD, MS

  Assistant Professor, Department of Biomedical Informatics

Erik's research integrates experimental and computational approaches to tackle the problem of antibiotic resistance. Although antibiotics have been used by microorganisms for eons, it remains unclear how these organisms have mitigated the rise of antibiotic resistance in their competitors. Erik studies the strategies that naturally antibiotic-producing bacteria have evolved to discourage the build-up of resistance, how we might employ similar tactics in the clinic, and how some pathogens have adapted to overcome antibiotics while paying a minimal price for resistance. The goal of this research is to develop new strategies for treating infectious disease, ultimately turning the tide against increasing antibiotic resistance.