Featured Projects
Teleheal is a subscription based mobile telehealth application for employees that taps into a $20 Billion market. It offers a secure virtual patient portal, a pandemic contact tracing engine, and fitness analytics algorithm that my team and I developed to recommend mental & physical fitness routines to improve patient health.
As part of our Hinman CEOs tech entrepreneurship program, my team and I demoed our project and angel investor proposition in several incubators.
SecureVR is a technology venture and platform that secures the data on VR and AR devices used by individual customers, businesses and organizations to ensure their personal data and security needs are protected when integrating VR into their operations.
As part of my Hinman CEOs tech entrepreneurship program, I worked with a team of 3 other students to build a website, go-to-market and product strategy plans for the SecureVR venture. We demoed our venture in multiple incubators.
AbilityPro is a unique social venture that I developed with a team to offer remote technology jobs to employees in the disability community for government contracts in the telehealth software, contact tracing and clinical trial spaces ($25 Billion Market). AbilityPro 360 Platform was a one-stop application solution that offers contract tracing, clinical trial, and telehealth support services.
This venture also empowers the disability workforce to improve community health. Throughout my social tech entrepreneurship courses, our team created a pitch video, social venture plan, and demoed this venture in multiple incubators including the Dingman Center for Entrepreneurship.
SRFly is a venture that offers a software platform with a unified, analytics-driven view of search & rescue and emergency response operations to assist government agencies in managing and coordinating these operations via drones in a real-time, streamlined manner.
During my Hinman CEOs tech entrepreneurship program, my team and I demoed our pitch, business model, and strategy plans in several incubators.
Our data mining project focused on analyzing online shopping behavior to identify key factors influencing customer purchase decisions. We developed predictive models using the "Online Shoppers Intention" dataset and employed various classification algorithms such as Logistic Regression, KNN, and Random Forest to forecast purchase likelihood.
Our analysis highlighted significant seasonal sales spikes, especially during holidays like Valentine's Day and Mother's Day, emphasizing the importance of tailored promotional campaigns. The project provided actionable insights into customer segmentation and effective marketing strategies, with Bagging and Random Forest models emerging as the most reliable in predicting purchase outcomes.
Created a GitHub page that serves as a tutorial to analyze a heart disease mortality rate dataset using a 5-step data science pipeline (data collection, data processing, exploratory data analysis & visualization, analysis/hypothesis testing/ML & insights/policy decisions).
During my DBMS class for my M.S. in Business Analytics, my team and I went through the database life cycle to construct a database in SQL Server that the NFL can utilize to positively influence social media marketing strategies and directly increase ticket and merchandise sales.
The mission behind our database is to track social media engagement, uncover insights to drive targeted marketing strategies, and, as a result, increase sales for both the league and individual teams.
In this database project, we created an analysis of the business problem we wanted to solve, made a database design (relational, conceptual, and ER models), implemented business case queries, and performed a live presentation to demo our database development from start to end. We also leveraged Tableau to construct dashboards with visualizations for business transactions that provided valuable insights to address our mission statement and objectives.
Teleheal is a subscription based mobile telehealth application for employees that taps into a $20 Billion market. It offers a secure virtual patient portal, a pandemic contact tracing engine, and fitness analytics algorithm that my team and I developed to recommend mental & physical fitness routines to improve patient health.
As part of our Hinman CEOs tech entrepreneurship program, my team and I demoed our project and angel investor proposition in several incubators.
SecureVR is a technology venture and platform that secures the data on VR and AR devices used by individual customers, businesses and organizations to ensure their personal data and security needs are protected when integrating VR into their operations.
As part of my Hinman CEOs tech entrepreneurship program, I worked with a team of 3 other students to build a website, go-to-market and product strategy plans for the SecureVR venture. We demoed our venture in multiple incubators.
AbilityPro is a unique social venture that I developed with a team to offer remote technology jobs to employees in the disability community for government contracts in the telehealth software, contact tracing and clinical trial spaces ($25 Billion Market). AbilityPro 360 Platform was a one-stop application solution that offers contract tracing, clinical trial, and telehealth support services.
This venture also empowers the disability workforce to improve community health. Throughout my social tech entrepreneurship courses, our team created a pitch video, social venture plan, and demoed this venture in multiple incubators including the Dingman Center for Entrepreneurship.
SRFly is a venture that offers a software platform with a unified, analytics-driven view of search & rescue and emergency response operations to assist government agencies in managing and coordinating these operations via drones in a real-time, streamlined manner.
During my Hinman CEOs tech entrepreneurship program, my team and I demoed our pitch, business model, and strategy plans in several incubators.
Our data mining project focused on analyzing online shopping behavior to identify key factors influencing customer purchase decisions. We developed predictive models using the "Online Shoppers Intention" dataset and employed various classification algorithms such as Logistic Regression, KNN, and Random Forest to forecast purchase likelihood.
Our analysis highlighted significant seasonal sales spikes, especially during holidays like Valentine's Day and Mother's Day, emphasizing the importance of tailored promotional campaigns. The project provided actionable insights into customer segmentation and effective marketing strategies, with Bagging and Random Forest models emerging as the most reliable in predicting purchase outcomes.
Created a GitHub page that serves as a tutorial to analyze a heart disease mortality rate dataset using a 5-step data science pipeline (data collection, data processing, exploratory data analysis & visualization, analysis/hypothesis testing/ML & insights/policy decisions).
During my DBMS class for my M.S. in Business Analytics, my team and I went through the database life cycle to construct a database in SQL Server that the NFL can utilize to positively influence social media marketing strategies and directly increase ticket and merchandise sales.
The mission behind our database is to track social media engagement, uncover insights to drive targeted marketing strategies, and, as a result, increase sales for both the league and individual teams.
In this database project, we created an analysis of the business problem we wanted to solve, made a database design (relational, conceptual, and ER models), implemented business case queries, and performed a live presentation to demo our database development from start to end. We also leveraged Tableau to construct dashboards with visualizations for business transactions that provided valuable insights to address our mission statement and objectives.