David Carlyn

PhD Candidate seeking full-time position (~May 2026)

Research focus in explainable/interpretable methods for machine learning to improve robustness and trustworthiness. Has ample experience in deep learning, team collaboration, research writing, and programming while conducting research at Ohio State University and the Imageomics Institute. Engineered features and developed a recommendation model for optimal notification delivery for the Instagram team during an internship at Meta. Created a genotype to phenotype pipeline for Heliconius butterflies through Imageomics and developed rust detection technology via the X-Force Fellowship, showcasing interdisciplinary collaboration and project management. General research interests in machine learning, computer vision, generative models, interpretable AI, concept bottleneck models, foundational models, genetics, biology, and health care.