Roberto Vivas Email & Phone Number

HS-POWER Intern by ORISEOpinions expressed here are personal and not representative of the positions or policies of DHS, ORISE, or the HS-POWER program.

Proposed a novel approach utilizing Random Forest (RF) and Logistic Regression (LR) algorithms to enhance the accuracy of credit card fraud detection, significantly reducing fraud incidents, and limiting false positives.Employed a rigorous methodology, including Python for algorithm comparison, data analysis through Google Colab, and dataset management from Kaggle to test algorithm efficiency, focusing on precision in predictions.Achieved a breakthrough result with RF showing 99% accuracy and 88% ROC AUC, outperforming LR and establishing RF as the study's most efficient method for detecting credit card fraud.Presented and submitted the research findings at the prestigious 23rd Annual Security Conference in Las Vegas, highlighting the impactful contribution to financial security and machine learning.

Guaynabo, Puerto Rico

Worked at CPM Intl on my first internship.

Master Of Science - Ms, Computer Science

Bachelor Of Science - Bs, Computer Engineering, 3.78

Activities and Societies: Programming and honor roll.Computer Engineering student who wants to specialize in Cybersecurity and Software.

High School Diploma, A

Activities and Societies: Bowling Club, Ethics Club, and Community Service TutoringGraduated from High School in May 2018 from Colegio San.