This is part of my Ph.D. thesis project. I improved the accuracy of regression analyses by over 20% by developing a bayesian general location model to impute missing and mismeasured data while studying the effect of household allergen concentration on childhood asthma in New York City neighborhoods. I was sponsored by my research advisor to present the results to statistics faculty at the June 2022 International Chinese Statistical Association (ICSA) conference and I first-authored a paper for… Show more This is part of my Ph.D. thesis project. I improved the accuracy of regression analyses by over 20% by developing a bayesian general location model to impute missing and mismeasured data while studying the effect of household allergen concentration on childhood asthma in New York City neighborhoods. I was sponsored by my research advisor to present the results to statistics faculty at the June 2022 International Chinese Statistical Association (ICSA) conference and I first-authored a paper for publication. Show less

I facilitated the learning of statistics for master's and doctoral level students with various statistical backgrounds by breaking down statistical concepts in one-one and small group teaching sessions. I held in-person and virtual office hours, graded and created solutions to assignments, and helped design course syllabi. I taught Probability, Randomized Clinical Trials, Categorical Data Analysis, Longitudinal Data Analysis, Statistical Inference, Survival Analysis, and Data Science.

I self-taught and performed time-series and bayesian spatiotemporal analyses in R on over 20 thousand datapoints on car crashes and alcohol use from 28 Australian cities, and I recommended the Queensland Police achieved a 5% reduction in the alcohol-related car crash rate at lower law enforcement costs by placing smaller, shorter-duration checkpoints within 3000kms and a week in advance of suspected crash locations. I fully documented the statistical method section of 2 resulting peer-reviewed… Show more I self-taught and performed time-series and bayesian spatiotemporal analyses in R on over 20 thousand datapoints on car crashes and alcohol use from 28 Australian cities, and I recommended the Queensland Police achieved a 5% reduction in the alcohol-related car crash rate at lower law enforcement costs by placing smaller, shorter-duration checkpoints within 3000kms and a week in advance of suspected crash locations. I fully documented the statistical method section of 2 resulting peer-reviewed publications, I presented the work to fellow graduate students, and I taught a teammate to apply the same statistical method to study how COVID-19 incidence and mortality differed by neighborhood demographics in New York City. Show less

I enabled the marketing team of a Fortune 100 company to evaluate their efforts and measure their contribution to insurance sales by creating generalized linear models to quantify the impact of opening and clicking on emails by insurance agents on the company's sales. I built a pipeline for cleaning, processing, and updating big data analyses (over 300 thousand data points) with SAS Enterprise Guide and SQL to update the impact results quarterly. I presented the results to data science and… Show more I enabled the marketing team of a Fortune 100 company to evaluate their efforts and measure their contribution to insurance sales by creating generalized linear models to quantify the impact of opening and clicking on emails by insurance agents on the company's sales. I built a pipeline for cleaning, processing, and updating big data analyses (over 300 thousand data points) with SAS Enterprise Guide and SQL to update the impact results quarterly. I presented the results to data science and marketing managers and to fellow interns. Show less

I updated the user interface of the Bayesian Spatial Model for activation and connectivity (BSMac) MATLAB toolbox and I implemented it on brain images of 20 to 80-year-olds to highlight how brain regions are affected by aging. I presented a poster to public health students and administrators at the Mailman Student Research Diversity Day, and I gave an oral presentation to fellow master's and doctoral level students at the Biostatistics Graduate Student Research Seminar.

I was awarded the Spelman College MathRaMP scholarship to conduct computational Chemistry research, and I devised a mathematical Nonparametric Four-Wave Mixing model for peak pattern prediction in MATLAB to improve the spectral analysis of gas-phase molecules. I co-authored the theory section of 2 resulting peer-reviewed chemistry publications, and I presented a poster at Spelman College's Science Day in April 2017.

I helped college students catch up in their mathematics classes by tutoring them in Precalculus, Calculus, Differential equations, Foundations of Mathematics, Linear Algebra and Abstract Algebra.

I served as a Sustainable Spelman Ambassador for the 2015-2016 academic year. I developed and implemented a trash labeling initiative in order to minimize Spelman College's carbon footprint and make the campus more environment-friendly.

I worked on a group project which aimed at characterizing unconsciousness under the ether anesthetic sevoflurane. I performed multitaper spectral analysis on sevoflurane electroencephalogram data in MATLAB, and explored the use of signal coherence, phase amplitude modulation and burst suppression probability signatures to understand the state of unconsciousness under sevoflurane general anesthesia. I also investigated the Hilbert-Huang Transform technique for the spectral analysis of… Show more I worked on a group project which aimed at characterizing unconsciousness under the ether anesthetic sevoflurane. I performed multitaper spectral analysis on sevoflurane electroencephalogram data in MATLAB, and explored the use of signal coherence, phase amplitude modulation and burst suppression probability signatures to understand the state of unconsciousness under sevoflurane general anesthesia. I also investigated the Hilbert-Huang Transform technique for the spectral analysis of sevoflurane electroencephalogram signals. Show less

I interned with the econometrics department where I prepared surveys, coded questionnaires and collected data for GDP and CPI computation

I conducted computational neuroscience research at the Emory University School of Medicine through the SURE 2014 program. I implemented the nearest neighbor and linear discriminant analysis classifiers in MATLAB to efficiently classify-and thus improve the diagnosis of-three sleep disorders (narcolepsy, REM Behavior Disorder and PLMD)

I performed literature searches, transcribed audios, and organized data from articles and audios for future reference in a research project about the experiences of women in Mathematics.

In addition to warmly welcoming customers and managing the Facebook page of the pharmacy, I recorded daily transactions and balanced average daily sales of $4500