I support my Black, Brown, Indigenous, LGBTQIA2S+, low SES, first-gen, visibly/nonvisibly disabled, neurodiverse colleagues, and all intersecting identities. Please reach out to me if there is any way I can use my privileged position to help facilitate to your goals and successes.
Education and Training
Internship/Postdoctoral Training: I am currently a postdoctoral fellow at the University of California San Francisco Clinical Psychology Training Program and Memory and Aging Center under the supervision of Dr. Kate Possin and Dr. Gil Rabinovici. I previously completed a one-year clinical internship at through this program.
Graduate Training: Clinical Psychology Ph.D. from the San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology working with Dr. Mark Bondi and Dr. Kelsey Thomas with a major area of study in Neuropsychology and a Quantitative Emphasis.
Undergraduate Training: B.A. in Philosophy-Neuroscience-Psychology and Psychological & Brain Sciences from Washington University in St. Louis.
Research
My graduate school research largely focused on improving the characterization of cognitive and biological changes that occur during the preclinical period of Alzheimer's disease (AD). In particular, I studied the spatiotemporal dynamics of amyloid and tau accumulation in the context of AD and related pathologic changes (e.g., PART), including how these pathologies may act both independently and synergistically to promote neurodegeneration and cognitive decline. I also examined how biological and environmental factors moderate these biomarker-cognition associations, and assisted on several studies assessing the role of social and structural determinants of health in aging and Alzheimer's disparities. Additionally, I was awarded a National Science Foundation Graduate Research Fellowship (NSF GRFP) to study the role of the locus coeruleus in cognitive aging, with a particular interest in the role of subcortical neuromodulatory systems of noradrenaline and acetylcholine in modulating attentional control changes in aging.
Currently, during fellowship at the UCSF MAC, my research is centered on improving early detection and clinical staging, differential diagnosis, and clinical heterogeneity of AD and related dementias. I have particular interest in combining multimodal clinical assessments and neuropathology data to improve clinical conceptualization of disorders of aging (e.g., AD, LATE). I have also been learning new methods for these projects including digital cognitive assessment, working with pathology data, and machine learning analytic methods including incorporation of artificial intelligence.
Clinical Work
My primary clinical interest is the neuropsychological assessment of individuals across the lifespan, from children with neurodevelopmental conditions (e.g., ADHD, SLD) to older adults with neurodegenerative syndromes (e.g., AD, PPAs, bvFTD). I also have an interest in the use of Dialectical Behavioral Therapy (DBT) for a range of presenting symptoms in higher acuity cases, as well as techniques rooted in Cognitive Behavioral Therapy (CBT) for the management of ADHD. My approach to clinical assessment and intervention stems from a biopsychosocial model, with the flexible adaptation of evidence-based tools treatments based on individual experiences, circumstances, and identities across intrapersonal, interpersonal, and systemic levels of influence.
Statistics
I have a strong interest in quantitative statistical methods and their application to data analysis. To this end, I have obtained a quantitative emphasis in my graduate program, and have been selected to attend multiple statistical conferences/workshops (e.g., Advanced Psychometrics of Cognitive Aging [PsyMCA/Friday Harbor], Methods for Longitudinal Research on Dementia [MELODEM]). I have particular interest in multilevel modeling to examine longitudinal trajectories of change in cognitive, functional, and biological outcomes, as well as clustering techniques such as latent profile analysis to identify unique latent patterns that emerge from a range of indicator variables to distill heterogeneous data into data-driven components that may reflect distinct phenotypic patterns.