Projects
ASL Translation Aid
Real-time ASL gesture → text prototype using hand landmarks and classification for accessibility.
Hackathon • 2025
Built a prototype pipeline that translates American Sign Language gestures into text, focusing on clean
data structures and real-time inference.
Highlights
- Inference loop: designed a frame → landmarks → model → output flow
- Structure: created clear data objects for gestures and predicted tokens
- ML: experimented with RandomForest and TensorFlow-based approaches
- Realtime: used MediaPipe for hand tracking on webcam frames
Tech
Python
MediaPipe
RandomForest
TensorFlow
Team of 4
What I’d do next
- Improve temporal smoothing to reduce irregular variations in predictions
- Turn it into a simple web demo and publish a short case study
Budallas Card Game
A real-time multiplayer card game built with Flask and Socket.IO, featuring live state synchronization.
Coursework • 2026
Developed a full-stack multiplayer card game hosted on Render. The backend handles turn-based logic,
live player updates, and game state management for 2–5 players.
Highlights
- Real-time Sync: utilized Flask-SocketIO to broadcast game state changes instantly to all clients
- Game Logic: implemented complex rules for attacking, defending, and turn rotation in Python
- Idvividual Play: designed server-authoritative logic that only sends a player their own hand data
- Repeatability: created a reconnection system using localStorage so players can rejoin active sessions
Tech
Python (Flask)
Socket.IO
Vanilla JS
Render
What I’d do next
- Make user experience more fun
- A tutorial for new players
- Add bots with a variety of difficulty
Pittsburgh Health Analysis
Neighborhood-level ranking using public datasets to analyze recreation access and community indicators.
Coursework • 2024
Aggregated and analyzed public datasets across Pittsburgh neighborhoods and produced visual insights + a
composite metric for comparison.
Highlights
- Data cleaning: merged multiple sources across 90 neighborhoods
- Geo: used GeoPandas for neighborhood-level joins and spatial context
- Visualization: created 10+ Matplotlib charts to show patterns + tradeoffs
- Composite indicator: built a simple scoring system to compare neighborhood well-being
Tech
Python
Pandas
GeoPandas
Matplotlib
Data storytelling
What I’d do next
- Document data sources and assumptions more formally
- Turn the score into an interactive map
- Add sensitivity analysis for weighting choices
Personal Portfolio Website
A clean, accessible, and responsive portfolio site built from scratch to showcase my work.
Coursework • 2026
Designed and developed a personal website to display my academic and technical projects. I prioritized semantic
HTML, modern CSS variables, and accessibility over using heavy frameworks.
Highlights
- No Frameworks: Built with pure HTML/CSS to ensure lightweight performance
- Responsive: Uses CSS Grid and clamp functions for fluid scaling on mobile/desktop
- Accessibility: Semantic tags, high contrast, and keyboard navigation support
- Design: Custom glass-morphism aesthetic with CSS variables for easy theming
Tech
HTML5
CSS3
Responsive Design
Accessibility
What I’d do next
- Implement a light/dark mode toggle
- Add a blog section for technical writing
- Make the cards more engaging
Crossy Roads Gemini Challenge
A challenge to recreate the classic arcade game Crossy Roads using Gemini 3.
Coursework • 2026
Developed a functional clone of Crossy Roads by prompting Gemini 3 to make step by step changes.
Highlights
- OOP Design: Structured game objects (player, obstacles, terrain) using inheritance and polymorphism
- Game Loop: Implemented a real-time update and render cycle for smooth gameplay
- Collision Detection: Created bounding-box logic to handle interactions between the player and traffic
- State Management: Managed game states (menu, playing, game over) and score tracking
Tech
Python
OOP
Pygame
GUI
What I’d do next
- Add sound affects and animations to the game
- Improve the looks of objects and the background
- Add more fun and exciting features to the game
Basketball Database
A small CLI app that tracks basketball stats (points, assists, rebounds, minutes) in a SQLite database.
Coursework • 2026
Developed a database to hold basketball stats and an interface to interact with it using Cursor.
Operations
- Create: Inserts a new stat row
- Read: Shows stats (all, sorted, or filtered)
- Update: Changes one stat for a row
- Delete: Removes a row by ID
Tech
Python
sqlite3
Cursor
What I’d do next
- Create more tables for the stats, like for games, seasons, player stats, team stats
- Use it in an actual project involving basketball
- Make the UI more pleasant and easier to interact with
Python Quiz App
A CLI quiz app built to explore AI agentic workflows (plan-delegate-review) using Cursor.
Coursework • 2026
Developed a command-line Python quiz application to explore multi-agent AI workflows. I wrote a detailed specification, delegated the initial build to GitHub Copilot's Agent Mode, and utilized an independent AI for code review.
Highlights
- Agentic Build: Directed an AI agent to implement the app based strictly on a comprehensive SPEC.md file.
- Data & Auth: Engineered a local login system, JSON file I/O for question banks, and secure, non-human-readable score tracking.
- Adaptive Logic: Implemented a feedback loop that adjusts future question selection based on user ratings.
- AI Code Review: Prompted a fresh AI agent session to audit the raw codebase for bugs, unhandled errors, and security flaws.
Tech
Python
CLI
JSON
Cursor
Prompt Engineering
What I’d do next
- Experiment with parallel AI reviewers (e.g., separate agents for security and code style).
- Automate the generation of new study subjects into the JSON format.
- Refine the terminal UI with richer text formatting and colors.
Experience
Krka Pharmaceuticals Intern
Supported enterprise data workflows and learned how data moves across systems.
Novo Mesto • 2025
Worked in a pharmaceutical environment with real business processes, internal datasets, and cross-team
communication.
What I did
- SQL: performed joins on internal company datasets to support reporting needs
- SAP workflows: observed and assisted with structured business processes
- APIs: reviewed and documented integrations using M-Files
- Collaboration: worked with IT + business teams on how systems connect
Skills used
SQL
SAP
APIs
Documentation
Enterprise systems
Key takeaway
I got my first real view of how “messy real life” data becomes structured business decisions.
Research Data Engineer
Developing data pipelines and scoring logic to rate corporate Digital & AI Maturity.
Pittsburgh • 2026
Building the "Master Data Collector," a system designed to rate companies based on financial data,
social media presence, and digital maturity. My focus is on data integrity and algorithmic scoring.
What I'm doing
- Algorithm Design: writing core logic to score brands on "Digital Pillars" (e.g., AI, Partnerships)
- API Integration: querying the NewsAPI to automatically fetch and classify relevant corporate news
- Quality Control: auditing complex company merges and validating master datasets
- Data Cleaning: identifying and fixing critical merge errors (e.g., entity resolution mismatches)
Skills used
Python
NewsAPI
Data Validation
Algorithmic Scoring
Research
Key takeaway
Building a reliable scoring system requires balancing automated logic with rigorous human-in-the-loop verification.
Teaching Assistant
Helped students build strong foundations in Java, debugging, and problem-solving.
Pittsburgh • 2025/26
Supported an introductory Java course with labs, office hours, and structured help for debugging and core
concepts.
What I did
- Led: weekly lab sessions for ~20 students
- Debugging: helped students systematically find and fix issues
- Teaching: explained fundamentals clearly (loops, arrays, methods, OOP basics)
- Support: held office hours and guided students through assignments
Skills used
Java
Teaching
Communication
Debugging
Mentorship
Key takeaway
Teaching made me faster at diagnosing code and explaining technical ideas in simple steps.
Peer Tutor
Tutored students in discrete math reasoning and Java programming fundamentals.
Pittsburgh • 2026
Delivered 1:1 and small-group tutoring focused on building confidence, reasoning skills, and repeatable
problem-solving habits.
What I did
- Discrete Structures: logic, proofs, sets, relations, induction
- Intro Programming: Java fundamentals, debugging strategies, code reading
- Coaching: helped students develop step-by-step approaches to problems
Skills used
Discrete Math
Java
Communication
Problem Solving
Mentorship
Key takeaway
The best explanations are structured like algorithms: clear inputs, steps, and checks.
About
I’m a Data Science and Computer Science student at the University of Pittsburgh with a strong foundation in
mathematics and logical problem-solving. I’m drawn to problems where structure, efficiency, and clear reasoning
matter, and where the goal is not just a solution, but the best one.
I like projects that combine data, algorithms, and real-world impact (healthcare, transportation/logistics, and
sports analytics). I’m building experience across Python, Java, SQL, and ML, and I enjoy turning messy,
unstructured inputs into tools people can actually use.
Outside academics, I play water polo and basketball. Those teams taught me discipline, iteration, and how to
perform under pressure, which translates surprisingly well to engineering.
