I am a method-oriented "Data Scientist" who focuses on designing the optimal statistical and machine learning models to discover hidden patterns in data. I work with small and big data alike, using adaptive methods that scale from typical experimental data consisting of tens of participants to real-world datasets with millions of rows.
My (mostly dormant) academic research focuses on uncovering how humans and animals understand "the order of things". For example, how come we understand the concept of "seasons"? Why did the discrete concepts of Spring, Summer, Fall, and Winter arise from continuous weather changes? Does the order of events influence our ability to categorize them? I find these questions fascinating.