Our Mission Statement
The mission of the Department of Biomedical Informatics Training Program is to prepare trainees to become outstanding leaders in biomedical informatics research, education, and practice. To optimize student learning in these areas, we immerse them in class training focused on artificial intelligence and computing methods for biomedical problems.
Who We Are
The University of Pittsburgh Biomedical Informatics (BMI) Training Program offers outstanding training for students who want to conduct innovative research at the intersection of biomedicine and computing. With core faculty members from 13 departments, our program offers students research opportunities in almost every area of biomedical informatics.
Generous Funding
Our trainees are well-supported. National Library of Medicine training fellowships are available to eligible candidates. Others are supported through our grant-funded research. All positions provide health insurance and competitive stipends.
Commitment to Diversity
Our program welcomes students from diverse backgrounds who enter our program with an array of skills and interests. We help you to tailor your program to provide a unique training experience individualized to your specific needs.
Our Research
Our training program faculty participate in numerous national research consortia at the intersection of computing and healthcare.The PaTH Clinical Research Network is a large regional consortium aimed at using health data to build a Learning Health System. The Evolve to Next-Gen Accrual to Clinical Trials is a nationwide network focusing on EHR-based real-world data research. The MIDAS Coordination Center provides informatics and community support for infectious disease modeling researchers. These projects, our Center for Clinical Artificial Intelligence, and faculty labs in imaging informatics, cancer informatics, and many other topics offer abundant research opportunities for graduate students on innovative research programs across numerous areas of biomedical informatics research, including bioinformatics, imaging informatics, clinical informatics, and public health informatics, often working with clinical partners at UPMC and collaborators nationwide. To learn more about what our students are up to, see the spotlights below or take a look at the graduate student or postdoctoral researcher web pages.
Student Highlight: Aidan Lakshman
Student Highlight: Brittany Gomez
Brittany Gomez is a second-year doctoral GEM fellow in Biomedical Informatics. In her personal time, she enjoys hiking, cycling, painting and volunteering.
Acute Respiratory Distress Syndrome (ARDS) affects 3 million people globally each year. While current treatments like mechanical ventilation help, they often cause further lung damage and restrict patients to hospital care. Their collaboration aims to revolutionize care for ARDS patients by developing the world’s first remote artificial lung for in-home use.
Her research focuses on creating a robust medical alert system and optimizing device parameters such as oxygen saturation and pump flow, tailoring them to a patient’s specific activities. A key challenge in developing a fully remote system is ensuring that any technical failures are detected early, giving clinicians ample time to intervene. To address this, she is leveraging advanced imaging and computer vision techniques to monitor key physiological markers and inform the alert system.
Most of her work takes place at CMU’s Robotics Institute, where they develop, test, and refine the remote infrastructure. They are also conducting in-vitro and in-vivo experiments at Allegheny General Hospital. As the project has evolved, what began as individual contributions is now a unified effort, integrating each aspect to make remote, real-time patient care a reality.
Student Highlight: Vishal Soman
Vishal Soman is a second-year Master’s Candidate in Biomedical Informatics working under Dr. Uma Chandran at the Genomics Analysis Core (GAC). The GAC provides data analysis expertise for genomics research in collaboration with the Pitt Center for Research Computing (CRC) and the Pittsburgh Supercomputing Center (PSC). He primarily uses Python, Bash, and R, specializing in bulk and single-cell RNA-sequencing analysis, and is based on the fifth floor of DBMI. Additionally, he is researching the use of large language models (LLMs) to parse, extract, and integrate structured data from a high volume of publications. In his free time, he enjoys gaming, playing golf, and spending time with his fiancé.