Natural Language Processing

Elucidating the mechanisms that underlie clustering and switching behavior is essential to understanding semantic memory search and …

Behavioral Signal Processing methods provide the basis for modeling human behavior with high resolution. Computational methods developed for Behavioral Signal Processing applications can provide deeper understanding of behavioral phenomena, especially useful for neuropsychiatry. I am developing methods to support dynamic analysis of clinical interviews, online data collection, and neuropsychiatric batteries. These methods are enabling understanding of mechanisms which underlie several disorders including dementia, schizophrenia, trauma, and depression. My work features analysis on the Framingham Heart Study Cognitive Aging Cohort, DCAPS Distress Corpus, and Mental Health America.

Semantic Memory Search describes the cognitive psychological process of exploring internal representations to retrieve semantic knowledge, facts, and experience from memory. I am developing predictive models of memory search via Optimal Foraging theory. This work contributes to both theoretical findings in understanding human semantic memory and clinical informatics approaches for understanding pathological alterations to memory, as the result of neuropsychiatric disorders

Aim: Although clinicians primarily diagnose dementia based on a combination of metrics such as medical history and formal …

Background: There is a need for fast, accessible, low-cost, and accurate diagnostic methods for early detection of cognitive decline. …

Importance: Depression is an illness affecting a large percentage of the world’s population throughout the lifetime. To date, …