Kim Nguyễn Ph.D. 

(she/her)

Hi! I'm a Research Scientist at Cooper Health and Penn Medicine. I use multimodal methods including behavioral, health records, and neuroimaging to understand trends and patterns in clinical research topics and human health.

I completed my Ph.D. at Temple University and my Bachelors of Science at UT Austin. My Ph.D. aimed to decode various inputs to memory by focusing on development and maturation. I used behavioral and MRI methods (functional, structural, and diffusion) with mixed-methods analysis to resolve multi-factor human interactions. 

With 8 years of research experience, I have developed proficient research design, technical problem-solving, and effective storytelling. I am looking forward to applying my expertise and expanding my toolkit into novel and exciting datasets!

git hub projects

statistics in R beginner workshop on github

neuroimaging in python workshop on github

jupyter notebook workshop on github

research projects

Memory for real world navigation

Role: Lead researcher

Method: Behavioral factor analysis

Funding: NIH R01 + PhD diversity grant


Using dimensionality reduction factor analysis, I found that variables of memory for real world experiences in children and adults are intertwined across two memory factors: spatiotemporal structure and perceptual/factual/locale. This work is in prep for a peer-reviewed publication.

Preprint available here.

Neural coding of a real world experience

Role: Lead researcher

Method: fMRI univariate and multivariate analysis

Funding: NIH R01 + PhD diversity grant


Tracking neural BOLD level, I found that when children and adults have good memory of a rich tour experience, the brain codes this information for later incidental retrieval.

Children's relational language supports their spatial mapping

Role: Lead researcher

Method: Behavioral mixed-effects modeling

Funding: NIH R01


With mixed-effects linear modeling, I found that using prepositions to link environmental features during a map reading task predicted spatial mapping in a virtual paradigm. This relationship was only seen in children 6-12 years, but not adults.

Preprint available here

Fornix integrity relates to memory behavior

Role: Researcher & mentor

Method: Behavioral and diffusion MRI

Funding: NIH R01 + PhD diversity grant


We used probabilistic tractography to reconstruct the fornix to measure tract volume and microstructure. Fornix tract volume and FAt were predictors of memory for real world encoding.

Figure: fornix reconstruction by Giovanna Arantes De Oliveira Campos

Behavioral nuances of virtual and real world navigation

Role: Researcher & mentor

Method: Behavioral

Funding: NSF EHR + PhD diversity grant


Using two virtual paradigms and one real world paradigm, we discovered that human behavior factors together based on the paradigm instead of other characteristics such as environmental build, task used, or modality.

Preprint available here

Hippocampal CA1-2 volume positively correlated with navigation memory

Role: Researcher & mentor

Method: structural MRI

Funding: NIH R01 + PhD diversity grant


Automatic and manual QC segmentation of hippocampal subfield volume using a T2-weighted scan taking with children (8-13y) and adults. CA1-2 volume is correlated to better route efficiency and free recall of real world navigation.

relevant training

Happy to chat! kimvnguyen246@gmail.com