About Me

I'm a Statistics and Machine Learning student at Carnegie Mellon University with a strong interest in solving problems through code and data.
Whether I’m building predictive models in R, writing backend logic in Python, or digging through messy datasets with SQL, I’m all about solving problems with clean, thoughtful code.
Outside of tech, you’ll find me playing pickleball or watching sports F1, staying curious about the business world, and exploring how data drives decisions across industries.

Work Experience

Software Engineer Intern

Stereotaxis
May 2025 – Jan. 2025

  • Built an automated remittance email system for thousands of invoices using SQL and the Messaging API, streamlining payment notifications and saving the accounting team at least 5 hours weekly.
  • Built interactive dashboards in Excel and Power BI to monitor overdue invoices, enabling targeted recovery actions that recouped over 2 million dollars in outstanding revenue
  • Automated a high-volume invoice approval workflow using Power Automate, reducing average processing time by 87% and increasing scalability across finance operations
SQL Power Automate APIs Power BI Excel Acounting

Lead Teaching Assistant

Carnegie Mellon University
January 2025 – Present

  • Deliver weekly lectures to 2 classes of 20 students to reinforce class topics such as data structures and algorithms in Python
  • Evaluate assignments, quizzes, and test, and offer individualized support for hundreds of students
  • Lead a team of 40+ TAs in coordinating course logistics and grading
Python Communication Leadership Teaching Prompt Engineer

Consulting Intern

Undivided Wealth Management
May 2024 – August 2024

  • Analyzed company financials to identify potential opportunities to streamline client onboarding processes
  • Conducted research on industry trends and market data to support strategic-decision making
  • Created data driven analysis generating actionable insights, leading to a new consulting service, generating an additional revenue stream
Data Analysis Presenting R Powerpoint Finance

Projects

2-D ShellShock

Developed a 2D turn-based tank artillery game using Python, inspired by ShellShock Live. Players battle an AI on terrain generated via recursive point creation and linear interpolation for smooth rendering. Projectile motion, calculated with vector math for gravity and wind, uses 3D vector calculus for precise collision detection with bumpers and portals. The AI, built with modular difficulty logic, employs strategic aiming, movements, and shot selection. A dynamic UI with trigonometric fuel gauges and gradients showcases a user-focused design.

Titanic Survival Prediction

Developed a machine learning project in R to predict Titanic passenger survival using a dataset with 622 observations and six predictors. Conducted extensive exploratory data analysis and implemented and compared Linear Discriminant Analysis, Quadratic Discriminant Analysis, Classification Tree, and Binary Logistic Regression, evaluating error rates to determine predictive power.

Stack'd Overflow

Created a 2D sandwich-stacking game in Python for a hackathon with a team of four, where players build sandwiches by catching falling ingredients to match a goal configuration. Leveraged OpenCV and MediaPipe to implement real-time wrist-tracking via webcam, accurately mapping wrist x-coordinates to control the plate’s horizontal movement for intuitive gameplay. Procedurally generated goal sandwiches using random selection with biased ingredient spawning, implemented via recursive list construction. Falling ingredients, managed with dynamic speed adjustments based on level progression, utilize simple distance-based collision detection for stacking.

Education

Bachelor of Science in Statistics and Machine Learning
Carnegie Mellon University
Aug 2024 – May 2027

Key Coursework and Skills

Statistics Computer Science Linear Algebra Machine Learning Python R C Data Structures Statistics Computer Science Linear Algebra Machine Learning Python R C Data Structures

Academic Highlights

GPA: 4.0/4.0

Major: Statistics and Machine Learning

Minor: Financial Management

Honors: Dean's List High Honors

Leadership & Activities

Effetive Coding with AI Head Teaching Assistant

Introduction to Computer Science Lead Teaching Assistant

Oversee a team of 40+ TAs in coordinating course logistics and grading for CMU's largest undergraduate Intro to CS course. Lead weekly recitation sessions focused on data structures and algorithms for a class of about 20 students, and held regular office hours to provide individualized academic support and mentorship.