معرفی
Megan Owen is an Associate Professor in the Department of Mathematics at Lehman College, City University of New York, and serves as a doctoral faculty member at the CUNY Graduate Center. Her academic work focuses on developing mathematical methods for complex data analysis with practical applications.
Dr. Owen specializes in combinatorial, geometric, and statistical methods for analyzing non-Euclidean data, particularly tree-shaped data structures. Her research bridges theoretical mathematics with practical applications in evolutionary biology and medical imaging, often utilizing real-world data from these domains. She has developed algorithms that enable more sophisticated analysis of complex data structures that don't conform to traditional Euclidean geometry.
- Member of the Treespace Working Group
- Recipient of NSF CAREER grant for Geometric and Statistical Analysis for Tree-Shaped Data (2019-2024)
Her teaching portfolio demonstrates expertise across mathematics and computer science, with courses spanning data science, statistical inference, programming methods, and computational biology. She has taught at multiple institutions including Lehman College, University of Waterloo, North Carolina State University, and Cornell University, showing a strong commitment to both undergraduate and graduate education in quantitative fields.
