As a Computer Science student at the University of Virginia, I've immersed myself in AI/ML research, full-stack development, and robotics engineering, working on projects that process millions of data points and impact real-world applications.
I'm committed to building scalable solutions that transform data into actionable insights, with a focus on end-to-end development and continuous learning.
• Architected a scalable data pipeline using Python, BeautifulSoup, and Docker to aggregate
and normalize drone activity data from 40+ sources into Firebase, utilizing MD5 hashing for
O(1) deduplication.
• Engineered an AI-driven system using Llama 3.2 to automate 100% of metadata tagging and
relevance scoring, eliminating manual oversight and reducing preprocessing time by 80%.
Built a large-scale benchmark processing >1M sports time-series data points to assess and improve large language models' predictive accuracy on numerical sequence forecasting tasks. Applied knowledge distillation and reinforcement learning techniques to ensemble models, increasing predictive accuracy by 10% on held-out time-series validation sets.
Tech Lead for a 20+ member team building ROS-based autonomy software for underwater submersible competitions; oversaw sprints, code reviews, and delivered a navigation stack integrated with computer vision. Optimized detection and navigation pipeline, reduced navigation error rate by 30%, and increased mission success rate in competition scenarios.
Ran weekly labs and office hours for 200+ students; created 10+ lab exercises and clarified recursion/concurrency concepts that improved average lab scores by 28%.
Built and validated a CNN in Keras to classify 277K histopathology image patches of breast tissue with 85% accuracy, constructing and analyzing a confusion matrix for performance evaluation. Engineered a large-scale IDC image dataset by preprocessing and programmatically splitting 277K 50×50 patches into 80/10/10 training, validation, and testing subsets using Python.
Collaborated as a freelance developer closely with a team of 5 to develop and launch a full-stack published web application utilizing HTML, JavaScript, CSS, React, and Airtable API integration. Reconciled industry design constraints while providing a full engineering design and prototyping report. Optimized software flow to account for 100s of users being C4K education students with sleek UI and data cleaning.
GPA: 3.75/4.0
Relevant Coursework: Data Structures and
Algorithms, Computer Systems and Org., Discrete Math and Theory
I'm always open to discussing new opportunities, interesting projects, or just having a conversation about technology.
Arlington, VA | 703-307-2897