Curriculum Vitae

University of Maryland — College Park · GPA 3.40/4.00

Coursework: Linear Algebra · Differential Equations · Multi-variable Calculus · Computer Systems · Object-Oriented Programming (I, II) · Discrete Structures · Data Science · Compilers · Real Analysis · Machine Learning

KBR — Lexington Park, MD

• Integrated ground, aerial, and maritime unmanned vehicles over a unified real-time communications network
• Configured ArduPilot/MAVLink autopilot stack and QGroundControl for a BlueBoat USV, including telemetry tuning and sensor calibration
• Built a multi-modal AI pipeline fusing live sensor streams across 3 vehicle domains for situational awareness modeling
• Developed an operator-facing C2 dashboard visualizing real-time AI outputs and vehicle telemetry across all domains
• Deployed a DINOv2 model to classify points of interest in sonar data in real time

Country Springs Wholesale Nursery — Lisbon, MD

• Architected a JS/PHP full-stack tool with flat-file JSON storage and client-side Excel parsing, eliminating the need for a database or build pipeline
• Implemented real-time multi-device sync with file-locking and conflict-safe per-item saves across multiple simultaneous iPads
• Built fuzzy search across 1,400+ SKUs with multi-filter support, TSV export, and responsive mobile/desktop layouts

Applied Research Lab for Intelligence and Security (ARLIS) — College Park, MD

• Conducted applied research in quantum machine learning and hybrid classical–quantum architectures for intelligence analysis and decision-support systems
• Achieved 97.3% accuracy on the MNIST dataset using a custom-parameterized quantum circuit optimized via PennyLane and PyTorch with a gradient-free evolutionary optimizer
• Deployed quantum simulation experiments on ARLIS's classified HPC environment, ensuring compliance with DoD and NIST security standards under Secret Clearance
• Optimized performance-critical code, improving runtime by 25–40% through profiling and refactoring
• Executed hundreds of HPC batch jobs via SLURM, reducing experiment turnaround time by 30%
• Collaborated with a 3–5 person team to deliver production-quality ML software against research milestones

FIRE Quantum Machine Learning Lab - University of Maryland — College Park, MD

• Conducted research on Variational Quantum Circuits (VQC) applied to Reinforcement Learning (RL)
• Focused on performance and trainability of quantum algorithms with data re-uploading
• Developed quantum-classical hybrid approaches to improve decision-making in classical control problems

FIRE Rapid Diagnostics - University of Maryland — College Park, MD

• Developed microfluidic and paperfluidic devices for point-of-care diagnostics
• Gained experience with Matlab, CAD, 3D printing, cutter-plotting, and PDMS molding for device fabrication
• Focused on rapid, on-site chemical and bio-analysis for healthcare, environmental monitoring, and disease control