I am currently a Data Scientist II at Mastercard as part of the the Model Services team within Mastercard’s Merchant and Acquirer Solutions. I develop and deploy predict models using various statistical and machine learning techniques to address business challenges. I collaborate with data engineers, product managers, and stakeholders to understand business requirements and translate them into data-driven solutions. I work at Mastercard’s St. Louis Tech Hub in O’Fallon, Missouri.
I worked as a Postdoctoral Research Associate for 3 years with Dr. Henry Roediger and Dr. Jim Wertsch at Washington University in St. Louis (2021 - 2024). I received my A.M. (Master’s degree; 2017) and Ph.D. (2021) in Psychological & Brain Sciences at Washington University in St. Louis working under Dr. Kathleen McDermott in her Memory & Cognition Lab. I received my B.Sc. in Psychology and Statistical Methods from Truman State University in 2015 and also spent summers doing research at the University of Michigan and University of Vermont.
My main interests are in examining both collective memory and individual differences in long-term memory, in particular how memories are formed and how they change over time. I am also interested in the similarities (and differences) between individual and group memory and forgetting. Much of my doctoral work was focused on the relation between how quickly people learn information and how well they remember it over time, as well as how learning rate related to forgetting rate. I participated in the Cognitive, Computational, and Systems Neuroscience (CCSN) pathway and was a National Science Foundation GRFP recipient.
PhD in Psychological & Brain Sciences, 2021
Washington University in St. Louis
AM in Psychological & Brain Sciences, 2017
Washington University in St. Louis
BSc in Psychology & Statistical Methods, 2015
Truman State University
People differ in how quickly they learn information and how long they remember it, and these two variables are correlated such that people who learn more quickly tend to retain more of the newly learned information. Zerr and colleagues (2018) termed the relation between learning rate and retention as learning efficiency, with more efficient learners having both a faster acquisition rate and better memory performance after a delay. Zerr et al. also demonstrated in separate experiments that how efficiently someone learns is stable across a range of days and years with the same kind of stimuli. The current experiments (combined N = 231) replicate the finding that quicker learning coincides with better retention and demonstrate that the correlation extends to multiple types of materials. We also address the generalisability of learning efficiency: A person’s efficiency with learning Lithuanian-English (verbal-verbal) pairs predicts their efficiency with Chinese-English (visuospatial-verbal) and (to a lesser extent) object-location (visuospatial-visuospatial) paired associates. Finally, we examine whether quicker learners also remember material more precisely by using a continuous measure of recall accuracy with object-location pairs.
Most research on long-term memory uses an experimental approach whereby participants are assigned to different conditions, and condition means are the measures of interest. This approach has demonstrated repeatedly that conditions that slow the rate of learning tend to improve later retention. A neglected question is whether aggregate findings at the level of the group (i.e., slower learning tends to improve retention) translate to the level of individual people. We identify a discrepancy whereby—across people—slower learning tends to coincide with poorer memory. The positive relation between learning rate (speed of learning) and retention (amount remembered after a delay) across people is referred to as learning efficiency. A more efficient learner can acquire information faster and remember more of it over time. We discuss potential characteristics of efficient learners and consider future directions for research.
People differ in how quickly they learn information and how long they remember it, yet individual differences in learning abilities within healthy adults have been relatively neglected. Across 2 studies (combined N = 372) we found that quicker learners were also more durable learners (i.e., exhibited better retention across a delay), despite studying the material for less time.