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Collaborations

We collaborate extensively across the University of Pittsburgh and beyond. Within the School of Medicine, this includes close partnerships with basic science departments such as pharmacology and human genetics, and clinical departments spanning medicine, anesthesiology and perioperative medicine, neurosurgery, critical care medicine, neurology, surgery, psychiatry and oncology, among others. We also work closely with faculty in other health sciences schools, as well as with colleagues in the Swanson School of Engineering, the School of Computing and Information, and the Kenneth P. Dietrich School of Arts and Sciences. A particularly rich and long-standing partnership with Carnegie Mellon University spans causal machine learning, population health informatics and biomedical data infrastructure.

Our clinical collaborations are central to our research mission. Working closely with clinicians and clinical departments across UPMC and the School of Medicine, we develop and evaluate artificial intelligence (AI) and machine learning models for clinical decision support in high-acuity settings. These efforts span predicting surgical complications such as post-induction hypotension and postoperative venous thromboembolism, detecting brain ischemia during carotid endarterectomy, identifying patients at risk of opioid overdose, and monitoring for outlier patient-management actions in the intensive care unit. By grounding our computational work in real clinical workflows and evaluating our tools alongside practicing clinicians, we aim to develop systems that are accurate, interpretable and ready for deployment in real-world care environments.

These collaborations also extend to large-scale data infrastructure and translational research. We serve as coordinating centers for national and international programs—including the Human BioMolecular Atlas Program (HuBMAP), the Cellular Senescence Network (SenNet), the Breast Cancer Research Foundation Global Data Hub, and the Evolve to Next-Gen Accrual to Clinical Trials (ENACT) federated network—working with partner institutions across the country to harmonize data, build shared infrastructure and enable reproducible research at scale. In cancer genomics and precision oncology, we partner with UPMC Hillman Cancer Center and investigators at Carnegie Mellon University and other institutions to advance biomarker discovery, tumor microenvironment characterization and personalized treatment prediction. Across these efforts, we serve as a bridge between computational methods and clinical and biomedical applications, translating advances in informatics and AI into tools and knowledge that improve research and patient care.