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Ramkiran Gouripeddi, M.B.B.S., M.S.

Languages spoken: English

Academic Information

Departments: Biomedical Informatics - Research Assistant Professor

Academic Office Information

Research Interests

  • Clinical Research Informatics
  • Comparative Effectiveness Research
  • Health Services Research
  • Clinical Decision Support Systems
  • Data Mining
  • Machine Learning
  • Knowledge Discovery
  • Personalized Medicine
  • Terminologies & Ontologies
  • Distributed Information Systems for Clinical and Translational Research
  • Data Architecture
  • Federated Biomedical Query Systems
  • Data Quality
  • Phenotyping
  • Data Modeling
  • Health Information Standards Development and Use
  • Big Data Analytics
  • Identity Resolution
  • Semantic Integration of Information
  • Distributional Semantics
  • Metadata Discovery
  • Exposomics
  • Air Pollution
  • Computational Modeling
  • Global Health
Dr. Ram Gouripeddi earned his MS from Arizona State University (2009) and his medical degree from MGR Medical University, India. He is an Assistant Professor in the University of Utah’s Department of Biomedical Informatics.

He has broad interests in clinical and clinical research informatics. He participates in research in which investigators attempt to understand the requirements of the clinical research community and develop the means and tools to enable, accelerate and scale clinical research. In particular, these are in the use of informatics methods for comparative effectiveness research and health-services research; machine learning and data mining for knowledge discovery and personalized medicine; biomedical data modeling; biomedical terminologies and ontologies.

Dr. Gouripeddi was previously a Research Associate with the office of the AVP for Health Sciences Information Technology and continues to work with the FURTHeR team. He played an instrumental role in extending and deploying FURTHeR as a platform for comparative effectiveness research. Dr. Gouripeddi practiced medicine before obtaining his informatics training from Arizona State University.

I believe informatics is trying to create a seamless flow of information between humans using systems in a healthcare setting to make informed decisions. Informatics can also tap into this flow and be a springboard for clinical knowledge discovery and utilization, reducing the lag time between the ‘bench’ and ‘bedside’.

Research Statement

I am an Assistant Professor in the Department of Biomedical Informatics, and a Senior Biomedical Informatics Scientist, Center for Clinical and Translational Science, University of Utah. I lead the research and development of diverse health informatics projects including data integration, metadata discovery, recruitment, streamlining research data and statistical analytics, and machine learning. I have led and participate in multiple data federation and integration projects for clinical and population health research. I am the R&D lead for OpenFurther project, an open source informatics solution for biomedical data integration and federation. I am currently extending its capabilities as a Big Data integration platform including exposomic and sensor data in order to perform environmental biomedical research fpr performing sensor-based epidemiological research. As the Principal Investigator of a bioCADDIE pilot project, I led work in automation of metadata discovery for different biomedical data and using the same within data integration platforms. In previous work, as the informatics principal investigator for the PHIS+, I lead the development of a multi-site data integration project using the OpenFurther technology for performing pediatric clinical and comparative effectiveness research. I am also currently the Utah site informatics lead for the PaTH PCORnet Clinical Data Research Network and the CTSA Accrual to Clinical Trials network. I lead the development of novel approaches for recruitment of participants for clinical trials, and streamlining analytics and provisioning of biomedical data and metadata needed for different biomedical studies undertaken at the University of Utah. I have extensive experience with clinical machine learning including using medical knowledge and temporal modeling. I practiced as a medical doctor managing patients with various conditions. My experience and training as a biomedical informaticist and physician and my lead involvement with multi-site large data projects as well as supporting the needs of clinical and translational research make me uniquely qualified to contribute as co-principal investigator for this CDC project. I will work with Dr. Julio Facelli (Principal Investigator) and other key personnel and staff in advancing the science of data integration for supporting public health surveillance and public health research.

  1. Gouripeddi R, Facelli JC, Bradshaw RL, Schultz D, LaSalle B, Warner PB, Butcher R, Madsen R, Mo P. (2013). FURTHeR: An infrastructure for clinical, translational and comparative effectiveness research. AMIA Annu Symp Proc. 2013:513.
  2. Gouripeddi R (2016). An Informatics Architecture for an Exposome, AMIA 2016 Joint Summits on Translational Science, 2016.
  3. Gouripeddi R, Mo P, Madsen R, Warner P, Butcher R, Wen J, Shao J, Burnett N, Rajan N, LaSalle B, Facelli JC (2016). A Framework for Metadata Management and Automated Discovery for Heterogeneous Data Integration, 2016 BD2K All Hands Meeting, Bethesda, MD, DOI:
  4. Gouripeddi R, Cummins M, Madsen R, LaSalle B, Harper S, Redd A, Ye X, Presson A, Greene T, Facelli JC (2017). Streamlining Study Design and Statistical Analysis for Quality Improvement and Research Reproducibility, Translational Science 2017. DOI:

Education History

Graduate Training Arizona State University
Biomedical Informatics
Residency Stanley Government Hospital
Professional Medical Stanley Medical College, M.G.R. Medical University

Global Impact