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On March 26, 2026, the Yale Center for Clinical Investigation (YCCI) and the Yale Biomedical Informatics and Computing (YBIC) Core co-hosted the inaugural 2026 Yale Medical AI Symposium at 101 College Street — home to the Department of Biomedical Informatics and Data Science (BIDS) — bringing together clinicians, researchers, trainees, and CTSA network partners to advance responsible AI in medicine.

The Yale Medical AI Symposium will bring together experts in and outside of Yale to discuss best practices and research collaborations.

The new Human Genome Sciences track in the Biological & Biomedical Sciences (BBS) PhD program, open for applications this fall, is an interdisciplinary initiative at the intersection of human genomics, genetics, and informatics.

Lucila Ohno-Machado, MD, MBA, PhD, and Tsung-Ting Kuo, PhD, have been awarded a four-year, $2.7 million grant from the National Library of Medicine to develop novel methods for explaining clinical AI models. The project, "Supervised Weighted Distances: Patient Similarity to Explain Clinical AI Models," will create algorithms and interactive visualization tools that help clinicians understand AI predictions by showing how individual patients compare to similar past cases with known outcomes. Running from September 2025 through August 2029, the research aims to increase trust and adoption of AI in clinical settings by making machine learning recommendations more transparent and interpretable for healthcare providers.

Yale's S-index project, led by Hua Xu, PhD, wins $15,000 in phase 1 of the NIH's $1 million Data Sharing Challenge and advances to phase 2 for the grand prize with innovative metrics that incentivize quality biomedical data sharing.

Two new research computing platforms, Hopper and SpinupPlus, are now available for analysis of large-scale, high-risk data. These platforms increase Yale’s highly secure research computing infrastructure.

Highlighting recent graduates of Yale’s Computational Biology and Biomedical Informatics (CBB) Ph.D. Program whose cutting-edge research is driving innovation in biomedical science and data-driven discovery.

Highlighting recent graduates of Yale’s Computational Biology and Biomedical Informatics (CBB) Ph.D. Program whose cutting-edge research is driving innovation in biomedical science and data-driven discovery.

Hua Xu, PhD, has received a $977,811 administrative supplement from the National Institute of Mental Health to support his project on coordinating individually measured phenotypes for mental health research.