About
Anyone who knows me will tell you I've always had two deep-rooted passions: technology and history. From a young age, I was captivated by the stories of the past-ancient civilizations, world-shaping events, and the evolving nature of society. This curiosity for human behavior and context still shapes many of my social interactions and how I view the world today. Around the same time, I discovered the immersive world of video games, which sparked a lifelong fascination with the boundless creativity and complexity made possible through technology. As I've grown, I've come to appreciate how these two interests, history and technology, are far more interconnected than they first appear.
While pursuing my Bachelor of Science at Southern Connecticut State University, I chose to major in Computer Science with a minor in Psychology-a combination that allowed me to approach problems from both analytical and human-centered perspectives. Through this academic journey, I developed a strong foundation in technical areas such as Algorithm Design & Analysis, Artificial Intelligence, Data Structures, Database Systems, Object-Oriented Programming, Operating Systems, and the Theory of Programming Languages. At the same time, I explored how people think, behave, and interact through courses like Social Psychology, Lifespan Development, and Global Environmental Issues.
Now that I've completed my degree, I'm more excited than ever about the vast possibilities within the tech industry. I believe the best engineers are those who stay curious, adaptable, and open to new challenges. I carry that mindset with me, along with an interdisciplinary approach to problem solving drawing from both technical knowledge and insights from the social sciences. Whether I'm writing code or tackling complex systems, I aim to consider not just how things work, but why they matter. I'm especially eager to explore opportunities in cybersecurity, data engineering, or any area of software development where I can continue to build thoughtful, impactful solutions.
Here are some of the technologies I've learned:
Python
Java
JavaScript
HTML/CSS
Flask
SQL
PHP
Experience
Biopath Research Experience
Southern Connecticut State University (06/23 - 07/23)
Assisted in research pertaining to single-cell sequencing analysis of RNA and DNA in an ever-progressing effort to enhance cancer research.Topics included working with command lines, algorithms, statistical softwares, and other technologies to analyze the neo-epitopes of proteins, parts of the cell which can be examined for cancer and mutations.
Undergraduate Grading Assistant
Southern Connecticut State University (08/23 - 12/24)
Analyzed and corrected student code related to techniques for representing and processing information, including the use of tables, linked lists, trees, and graphs. Comprehensive foundation of data abstraction including stacks and queues using object oriented approach.
Customer Service Representative
Patterson Oil Company (04/21 - Current)
Efficiently handle transactions and maintain inventory while building genuine connections with new and regular customers, ensuring a welcoming and personalized experience in a fast-paced environment.
Favorite Project: 360 Sports Watching Service
Technologies Used:
HTML
CSS
Python
JavaScript
Shell
Socket Programming
Open-CV
Other Projects
Find a Fragrance
Developed an intelligent cologne recommendation platform that uses semantic search and natural language processing (NLP) to match users with fragrances. Users can describe their scent preferences in everyday language (e.g., "I'm looking for something sweet but masculine"), and the system returns personalized suggestions by comparing the query's vector embedding against stored embeddings of colognes. These embeddings are generated using structured scent data like notes, accords, and brand context. The goal was to blend conversational AI with semantic vector similarity to create an intuitive, expressive, and highly personalized fragrance discovery experience for users
Court Vision Predict
Users of this platform can stay updated on their favorite teams and players. They have access to comprehensive statistics, allowing them to gauge performance trends and stay informed about popular events. Moreover, they can anticipate upcoming matchups through current predictions.
Age Detection Project
Implemented a Convolutional Neural Network (CNN) model, that when given face image data, outputs the predicted age of a person. The dataset used for the CNN model was the publically available UTKFace dataset.