About

Third-year Information Systems and Artificial Intelligence undergraduate at Carnegie Mellon University with hands-on experience building and maintaining production software systems. I enjoy working on backend and cloud-based systems, distributed architectures, and data-driven applications, and I bring a strong foundation in systems programming, statistics, and machine learning. Through industry and academic projects, I’ve learned how to thoughtfully design, refactor, and scale software in real-world settings while collaborating closely with others to deliver reliable, well-structured solutions.

Previously, I worked as a Software Development Intern at Erin Technologies, where I focused on building and modernizing production software systems. My work centered on backend and cloud infrastructure, including developing AWS Lambda–based services, refactoring legacy notification logic into modular and testable components, and supporting data pipelines used for analytics and reporting. This experience strengthened my ability to work within real operational constraints, collaborate across teams, and take ownership of software that directly supports production workflows.

My academic training reflects a strong emphasis on both software systems and applied computation. I have completed coursework in Computer Systems, Data Structures and Algorithms, Database Development, Application Development, and Robotics Planning, which strengthened my understanding of low-level systems, algorithmic reasoning, and software architecture. I have also taken advanced courses in Probability, Statistical Inference, Modern Regression, and Computer Vision, giving me a rigorous foundation in data-driven modeling and empirical evaluation. Together, these courses have shaped how I approach software engineering problems, with attention to performance, correctness, and real-world constraints.