Dr. Kassel Hingee

Biography

Kassel Hingee is a Postdoctoral Fellow at the Australian National University, specializing in statistical methods for multivariate data constrained to specific spaces, particularly compositional data. This type of data typically involves several non-negative components whose sum is constrained, with applications found in biology, microarrays, geochemical surveys, soil, and finance. Hingee's educational background includes a PhD in Statistics and an MPhil in Applied Mathematics, with a Bachelor of Philosophy in Science. He is well-versed in computer programming and adept at managing large datasets, which is crucial for analyzing spatial data, a key focus of his research. His work extensively involves remote sensing, land management, and addressing climate change through environmental statistics. He has contributed to the development of R packages, such as ‘lacunaritycovariance’, to compute fractal summary statistics and covariance estimates for spatial data. His research interests encompass statistical methods applied to ecology and environmental statistics, with a strong emphasis on automatic differentiation techniques. Hingee has actively participated in various research collaborations and continues to explore innovative methodologies in his field.

Research Interests