Rowan Cassius is a research scientist in AI/ML with a strong foundation in applied mathematics and statistics from UC Berkeley and practical experience spanning academic research and industry engineering roles. With 11 years of experience across institutions like Biohub, Columbia University, Salesforce, and UC Berkeley, Rowan blends rigorous statistical thinking with production-minded software engineering and data science. He teaches complex probability and statistics concepts and has led instructional programs, demonstrating an ability to communicate technical ideas clearly to diverse audiences. Rowan emphasizes "persistent thinking"—a willingness to iterate through many approaches and embrace failure—which drives progress on hard problems and underpins his research methodology. Based in New York, he seeks to apply ML and data analytics toward scientifically meaningful problems, combining deep quantitative skills with hands-on engineering to move experiments into impact.
11 years of coding experience
3 years of employment as a software developer
Bachelor's Degree Applied Mathematics Statistics, Bachelor's Degree Applied Mathematics Statistics at University of California, Berkeley
Master's Degree Information and Data Science, Master's Degree Information and Data Science at UC Berkeley School of Information
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Rowan Cassius - Research Scientist, AI ML at Biohub