About

Hi!

I’m a third‑year Information Systems and Artificial Intelligence undergraduate at Carnegie Mellon University. Most of my work sits at the intersection of software engineering, systems, and applied machine learning.

What I enjoy most is understanding how things behave under the hood. That could mean debugging a backend service, designing a simulation model, or figuring out why a system behaves differently at scale than it does in a test environment.

I’m especially interested in:

• backend and cloud systems
• distributed architectures
• data‑driven applications
• simulation and security research

In general, I enjoy projects where software interacts with real constraints — performance limits, messy data, or complex real‑world systems.

Software Engineering Experience

I previously worked as a Software Development Intern at Erin Technologies, where I focused on backend infrastructure and production systems.

My work there involved modernizing parts of the company’s backend architecture. This included building and maintaining AWS‑based services, refactoring legacy logic into modular processors, and supporting analytics pipelines used for reporting and operational insights.

What I enjoyed most about that experience was working with real production systems. Writing code that people depend on daily changes how you think about engineering. Stability, maintainability, and clear architecture become just as important as shipping features.

Research: Cybersecurity Simulation (CASOS Lab)

I also work with the CASOS Center at Carnegie Mellon on cybersecurity simulation research.

One of the projects I’ve worked on models watering hole attacks using agent‑based simulation.

In a watering hole attack, an attacker compromises a website that employees of a target organization frequently visit. When those employees access the site, malware is delivered and can spread through the organization’s network.

Our simulation environment models things like:

• attacker behavior
• defender response strategies
• user browsing patterns
• organizational network structure

The goal is to understand how attacks propagate and how different defensive strategies affect system resilience.

From an engineering perspective, this involves building simulation infrastructure, implementing agent behavior models, and integrating knowledge bases such as MITRE ATT&CK.

Projects

See my projects here!

Technical Background

My coursework combines systems engineering with quantitative modeling.

On the systems side, I’ve studied topics such as computer systems, algorithms, databases, and robotics planning. On the quantitative side, I’ve taken courses in probability, statistical inference, regression, computer vision, and machine learning. I’m also a Teaching Assistant at CMU for probability and statistical inference and I really enjoyed working with students and helping them to learn!

That combination shapes how I approach engineering problems: balancing correctness, performance, and practical constraints.

Outside of Engineering

Outside of programming, I spend a lot of time working with audio.

I enjoy:

• audio engineering
• sound editing and mixing
• recording music
• playing music! (I play the violin in bands and orchestras)

Audio work has a surprisingly similar mindset to software engineering. Small adjustments can completely change the outcome, and careful attention to detail matters.