Tiffany Callahan is a Principal Applied ML Engineer with nearly a decade of cross-sector experience building interpretable, production-ready AI for healthcare, materials science, and cellular biology. She combines deep academic training (PhD in Computational Biology and postdoctoral work in Biomedical Informatics) with hands-on engineering—leading agentic multi-agent systems, simulation platforms, and knowledge-engineered workflows for drug response prediction and regulatory-grade studies. Tiffany has driven patented privacy-preserving data protocols and led international, interdisciplinary collaborations that bridge symbolic, statistical, and physics-based models. Based in New York, she mentors teams, advises startups, and translates complex multimodal data into actionable systems that accelerate translational science. An emerging distinguishing strength is her track record of operationalizing autonomous scientific agents and building infrastructures that make in silico experimentation accountable and deployable.
9 years of coding experience
19 years of employment as a software developer
Bachelors, PSYCHOLOGY, Bachelors, PSYCHOLOGY at The University of New Mexico
Doctor of Philosophy (Ph.D.), Computational Biology, Doctor of Philosophy (Ph.D.), Computational Biology at University of Colorado Anschutz
Postdoctoral Fellowship, Biomedical Informatics, Postdoctoral Fellowship, Biomedical Informatics at Columbia University
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