About Me

I am an Assistant Professor of Mathematics at the University of North Carolina Charlotte. Prior to joining UNCC, I received my PhD from the Department of Mathematics at North Dakota State University where I was advised by Indranil SenGupta and my Masters from the Department of Mathematics and Its Applications at Central European University. I was awarded an Outstanding Academic Achievement Award from CEU. I also have been fortunate enough to received the Graduate Teaching Award , Graduate Teaching Fellow and Graduate Research Award from NDSU. As a Graduate Teaching Fellow I completed my PhD dissertation entitled: " Analysis of Variance Based Financial Instruments and Transition Probability Densities: Swaps, Price Indices, and Asymptotic Expansions." I also received my Bachelors of Science degree in Mathematics from Kwame Nkrumah University of Science and Technology.

Data Science Themes

Reducing Traffic Mortality in the USA

Applied mutlivariate linear regression, pricincipal component analysis and clustering to derive a strategy to reduce the incidence of road accidents across the USA.

Which Debts Are Worth The Bank's Effort?

Modeling with rgression to understand what additional cost per customer a bank should incur for different recovery strategies at different threshold

Mortgage Loans: Will the bank fail?

Let's say a bank made 100 mortgage loans. It is possible that anywhere between 0 and 100 of the loans will be defaulted upon. You would like to know the probability of getting a given number of defaults, given that the probability of a default is š¯‘¯=0.05?

Hans Rosling Bubble Chart

Used data visualization in Python to produce Professor Hans Rosling Bubble Chart.

Bees Image Processing

Loaded, transformed, to understand images of honey bees and bumble bees in Python. This project is the first part of a series of projects that walk through working with image data, building classifiers using traditional techniques, and leveraging the power of deep learning for computer vision.

Predicting Bees Species from Images

Built a model that can automatically detect honey bees and bumble bees in images.This project is the second part of a series of projects that walk through working with image data, building classifiers using traditional techniques, and leveraging the power of deep learning for computer vision.

Bitcoin and Cryptocurrencies

Analyzed the growth and impact of Bitcoin and other cryptocurrencies by exploring the market capitalization of different cryptocurrencies. From the project we see that the cryptocurrency market is exceptionally volatile, and any money you put in might disappear into thin air. Never invest money you can't afford to lose.

Predicting Blood Donations

Built a machine Larning model using TPOT to predict if a blood donor is likely to donante again.

Predicting Credit Approvals

Built a machine learning model to predict if a credit card application will get approved.

Hacker Statisics

Application of hacker statistics to compute the probability of winning a bet on reaching step 60 of a tall building.

Publications

Key: # co- author(s)

Get In Touch