Research
Dr. Brundage leads an interdisciplinary research program at the intersection of biomedical informatics, artificial intelligence, and veterinary medicine. His work emphasizes reproducible methods, open infrastructure, and the responsible deployment of AI in real-world clinical and research settings.
His research spans:
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Agentic, generative, and multimodal AI systems for clinical decision support
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Veterinary and comparative digital pathology
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Clinical natural language processing and documentation practices
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Privacy, de-identification, and governance of health data
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Scalable, cloud-native and edge-deployed AI infrastructure
His work has contributed to NIH- and NCI-funded initiatives, including the Medical Image De-Identification Task Group and large-scale computational pathology efforts.
Clinical Interests
Dr. Brundage’s work focuses on the development and evaluation of artificial intelligence systems that support veterinary, comparative, and wildlife medicine. His clinical interests include digital pathology workflows, veterinary clinical documentation, AI-enabled clinical decision support, and privacy-preserving use of veterinary health data. He is particularly interested in translational and One Health applications that bridge veterinary, human, and environmental health.
Graduate Training
Dr. Brundage mentors DVM students, graduate students, postdoctoral fellows, and trainees from computer science, biomedical informatics, and related disciplines. Dr. Brundage is a faculty trainer in the Comparative Biomedical Sciences graduate program. His mentorship emphasizes methodological rigor, reproducibility, interdisciplinary collaboration, and translational impact. Trainees in the Brundage Lab gain experience spanning data curation, model development, evaluation, and deployment.