University of Massachusetts, Amherst, US

University of Massachusetts, Amherst, US

Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

Boateng, A., Odoom, C., Mensah, E. T., Fobi, S. M., & Maposa, D. (2023). Predictive Analysis of Misuse of Alcohol and Drugs using Machine Learning Algorithms: The Case of Using an Imbalanced Dataset from South Africa. Appl. Math, 17(2), 261-271.

Odoom, C., Boateng, A., Mensah, S. F., & Maposa, D. (2024). Modeling the daily dynamics in bike rental system using weather and calendar conditions: A semi-parametric approach. Scientific African, 24, e02211.

Odoom, C., Boateng, A., Folitse, D. (Accepted on September 20, 2023, by Springer for their 7th International Conference on Intelligent Computing & Optimization 2023). Modeling the effects of economic growth on employment and forest area in sub-Saharan African countries using a semi-parametric regression technique.

Boateng A., Odoom C, Maposa D., Owusu, S.A. (Under review). Optimizing Binary Classification Performance in Neural Networks: A Comparative Study of Activation Functions.

Odoom, C., Boateng, A., Folitse, D. (under-review). Modeling the Relationship between Health Expenditure and Mortality Rates in Africa: A Comparative Study using Fixed Effect Panel Regression and Penalized Cubic Spline Models.

Non-parametric derivative estimation with penalized b-splines: asymptotics and an improved estimator. (Ongoing)

University of Connecticut

A poster presentation on non-parametric derivative estimation with penalized b-splines: asymptotics, an improved estimator and Applications.

University of Boston

A poster presentation on non-parametric derivative estimation with penalized b-splines: asymptotics and an improved estimator.

University of Massachusetts, Amherst

Presentation on Power analysis in statistical Studies.

Simulate and compare distributions and survival curves for different specifications of the likelihood function using the Bayesian Approach. Different posterior sampling techniques, including Gibbs and Metropolis Hasting, were considered.

Developed a multivariate multiple linear regression model to understand dynamics in bike rentals.

Developed a robust model to predict Diabetes status based on risk factors such as body mass index.

Develop a prediction set for classification problems instead of using traditional label prediction.

Developed a Poisson model to understand the factors contributing to the expected number of goals in the top five leagues, which include the English premier league.

Investigated the main differences between classical and Bayesian regression via simulation study.

Predictive model for claim cost with right-skewed claim cost distribution.

University of Massachusetts, Amherst, US

Work on non-parametric derivative estimation with penalized b-splines: asymptotics and an improved estimator. (Ongoing)

Department of Mathematics and Statistics, University of Massachusetts, Amherst, US

R Tutoring Centre, Department of Mathematics and Statistics, University of Massachusetts, Amherst, US

University of Massachusetts, Amherst, US

• Led discussion sections by explaining statistical concepts to students.
• Introduced advanced Excel tricks to students.

Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

• Assisted in a research project focused on alcohol and drug misuse in South Africa.
• Conducted literature reviews, gathered relevant data, and performed statistical analyses.
• Presented research findings for publication.

Gomoa Central District Assembly, Ghana

Involved in district data collection and manipulation.

In honor of the outstanding virtual poster and oral speedy presentation presented at the 37th New England Statistics Symposium, May 20-24, 2024

Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

• Machine Learning with R - IBM cognitive class
• Python for Data Science - IBM cognitive class
• Excel: avoiding common mistakes Office 365/Excel 2019 - LinkedIn Learning
• Data Science Tools - IBM cognitive class

• Statistical Software: Proficient in R and Python.
• Data Analysis: Expert in semi-parametric regression, particularly generalized additive modeling.
• Programming: Familiar with MATLAB and SQL.
• Data Visualization: Very proficient with tidyverse (data manipulations R), ggplot2(R), matplotlib (Python), and Seaborn (Python).
• Communication: Excellent at conveying complex statistical concepts.

Professor John Staudenmayer

Department of Mathematics and Statistics, University of Massachusetts, Amherst

jstauden@umass.edu

Dr. Alexander Boateng

Department of Mathematics and Computer Science, Modern College of Business and Science, Muscat, Sultanate of Oman

siralexboateng@gmail.com