My name is Alex Verbesey, and I am a Senior studying computer science at Georgetown University. I am currently a Machine Learning Intern at CAVA, where I develop and evaluate forecasting models to support data driven decision-making. I recently returned from spending a semester abroad in Copenhagen, Denmark. I am passionate about AI/ML engineering and eager to apply my skills to real-world challenges. Beyond coding, I enjoy running, basketball, art, music, and chess, which inspire my creativity and problem-solving approach.
$ cat skills.txt
Languages: C++, Python, SQL, Java, JavaScript, TypeScript, Kotlin
Frameworks/Tools: Git, Github, Databricks, Tensorflow, Amazon Web Services (AWS), React.js, HTML/CSS, PyTorch, Bash, Visual Studio, REST APIs, Docker, Firebase, Jupyter Notebook, Scikit-Learn, NumPy, Pandas, Matplotlib, Spark, MLflow, MLOps
Design: Photoshop, Illustrator, InDesign, Figma
$ cat coursework.txt
Computer Science: Data Structures, Algorithms, Neural Networks and Deep Learning, Artificial Intelligence, Programming Languages, Computational Structures, Network Security
Mathematics: Statistics, Math Methods, Calculus I, Calculus II, Linear Algebra
GPA: 3.85
Developed a time series forecasting model using Python and SQL in Databricks to predict future guest traffic and sales for CAVA. The model leverages historical guest counts and sales data and incorporates external factors such as holidays and promotions to improve accuracy.
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Created a multimodal fitness tracking system with a Raspberry Pi and IMU sensor to capture real-time workout metrics. Developed an Android app and web dashboard that connect via Bluetooth to log data and provide seamless performance visualization across platforms.
Developed a convolutional neural network in TensorFlow Keras to classify brain tumors from MRI scans with 94% testing accuracy. Managed the full pipeline from data collection to model optimization, demonstrating strong applied machine learning skills.
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Built a daily To-Do website with HTML, CSS, and JavaScript, integrating Firebase Cloud Firestore for seamless task storage and retrieval. Automatically generates date headers for new days and enhances productivity with a simple, user-friendly interface. Hosted on GitHub Pages and used daily as a personal productivity tool.
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Convolutional Neural Network (CNN) built using TensorFlow Keras to classify images into four categories: Tom, Jerry, both, or neither. It is written in Python using Jupyter notebooks, and includes visual graphs to track the model's performance during training and testing.
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Facial recognition system built in Python using the DeepFace library. It takes a reference image of my face and can identify it in a live feed with high accuracy. The software leverages advanced facial recognition techniques to perform quick and reliable matches.
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A Calorie Tracker app built with React and the ChatGPT API that estimates calorie counts based on food entries and tracks daily intake.
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Interactive chess game, built in React, lets players enjoy chess with all the official rules. It currently allows for local play on one computer and provides an engaging way to practice chess.
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A React-based Jeopardy game featuring five categories, including one focused on me. It includes a working scoreboard and serves as a practical project to explore full-stack development.
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This Wordle solver has a near 100% success rate. It uses your feedback to suggest the next guess, helping you solve the puzzle quickly and accurately.
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