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

Xia Jiang, PhD

Associate Professor, Department of Biomedical Informatics
University of Pittsburgh School of Medicine
Faculty, Pitt Intelligent Systems Program
Faculty, CMU-Pitt Computational and Systems Biology PhD Program
Interests:
Application of AI, Machine Learning, and Bayesian Networks in biomedical domain, clinical informatics, causal learning, prediction and decision support, biomarker/risk factors discovery via learning from data, design and development of computational methods/algorithms, and cancer and translational informatics.

Songjian Lu, PhD

Assistant Professor, Department of Biomedical Informatics
University of Pittsburgh School of Medicine
Interests:
Using computational method to search for driver somatic genome alterations, such as somatic mutations, copy number alterations, that are related to cancer development. Formulating the biological problems into graph or statistical problems. Designing efficient exact algorithms for the hard computational problems.

Xinghua Lu, MD, PhD, MS

Professor of Biomedical Informatics
Biomedical Informatics Training Program Core Faculty
University of Pittsburgh School of Medicine
Interests:
Computational methods for identifying signaling pathways underlying biological processes and diseases, statistical methods for acquiring knowledge from biomedical literature, translational bioinformatics and systems/computational biology, natural language processing and text mining.

Hatice Ulku Osmanbeyoglu, PhD

Assistant Professor
Department of Biomedical Informatics
School of Medicine, University of Pittsburgh
UPMC Hillman Cancer Center

 

Google Scholar Page 

LinkedIn Profile

Lab Page

Interests:
Bioinformatics Specialties: Machine learning, information integration, knowledge discovery

Yalini Senathirajah, PhD

Associate Professor, Department of Biomedical Informatics
University of Pittsburgh School of Medicine

Interests:
Clinical Informatics Global Health Informatics Interface Design

Jonathan C. Silverstein, MD, MS, FACS, FACMI

Chief Research Informatics Officer, Health Sciences and Institute for Precision Medicine (IPM)

Professor, Department of Biomedical Informatics (DBMI), School of Medicine

Affiliate Scholar, Pitt Cyber

Interests:
Clinical Informatics Imaging/Visualization/Virtual Reality Vocabularies Virtual Organizations Learning Health Systems Oncology Informatics

Sofia Triantafillou, PhD

Assistant Professor, Department of Biomedical Informatics

Interests:

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

Interests:
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.

Erik S. Wright, PhD, MS

  Assistant Professor, Department of Biomedical Informatics

Interests:
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.
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