I am a Computer Science senior at Georgia Institute of Technology, passionate about data, machine learning, algorithm design, and software engineering. My goal is to work at the intersection of theoretical computer science and practical data driven applications to create more efficient systems and solve real-world problems across multiple disciplines.

 

Recently, I completed my third and final rotation as a Data Engineer Co-op at The Coca-Cola Company. Over the course of the year, I developed scalable APIs, optimized data pipelines using Azure and PySpark, and implemented AI-based solutions to streamline internal processes. One highlight was leading the development of an AI chatbot using Haystack and RoBERTa NLP models, which improved query resolution and data accessibility for internal teams. I also worked on building robust data architectures that automated the processing of 300+ datasets, significantly reducing manual workloads. This hands-on experience strengthened my skills in data engineering, cloud infrastructure, and machine learning while teaching me how large-scale systems operate in a production environment.

During my time with the Quantum Computing Team at Future Computing with Rogues Gallery, I was immersed in an environment where computer scientists and physicists collaborated to tackle multidisciplinary challenges. We worked together to document our progress, hold each other accountable, and deliver weekly updates. This experience taught me how computation can drive problem-solving across different fields. For example, while the physicists developed theoretical models to predict noise in quantum circuits, we applied empirical data from IBM Quantum hardware through a neural network to cross-validate the models. Ultimately, I helped design an LSTM-driven circuit optimization algorithm, which deepened my understanding of how computer science transcends programming and becomes a powerful tool for analysis and innovation.

In another project, I set out to implement the Tideman electoral method using C and graph theory. I mapped each candidate to a node, creating edges based on victory strength, and designed recursive algorithms to handle the system’s complexities. This project, along with my work on a Game Boy Advance Emulator game, fueled my interest in computer architecture. I found that small adjustments to low-level programming could drastically improve time and space efficiency, and overcoming hardware limitations further cemented my fascination with optimizing systems at both the software and hardware levels.

As a Prototyping Instructor and Electronics Room Apprentice at the Invention Studio, I also developed leadership and communication skills, guiding teams through the rapid prototyping process and offering design consultations. These experiences reinforced the importance of clear communication, teamwork, and iterative development—qualities I aim to bring to any future role.

From quantum computing to data engineering, I strive to push the boundaries of computing in every application area. If you’d like a more detailed look at my experience, you can find my resume below.