Curriculum vitae

PhD in Physics (Starting Soon)
University of Massachusetts Lowell
Specializing in machine learning applications in astrophysics and gravitational wave detection.
Master of Science in Physics (2023 – Present)
University of Washington
Coursework: Quantum Mechanics, Electromagnetism, Machine Learning for Signals in Engineering.
Bachelor of Science in Physics (2012)
University of Florida

Graduate Research – Gravitational Wave Machine Learning (GWGASF Collaboration)
University of Washington (2023 – Present)
- Developing machine learning models for gravitational wave detection and signal classification.
- Working with S3 storage, Kubernetes, and HPC environments for large-scale astrophysical data processing.
- Implementing deep learning architectures to analyze noisy time-series data from astrophysical sources.
Researcher – He6-CRES Experiment
University of Washington
- Worked on high-precision measurements for fundamental physics experiments.
- Conducted computational modeling and data analysis.
Research Assistant – National High Magnetic Field Laboratory (NHMFL)
Tallahassee, FL
- Applied advanced microscopy techniques for material characterization.
- Conducted high-field measurements and spectroscopic analysis.

Materials & Process Physics Engineer I
Boeing (April 2024 – January 2025)
- Specializing in nondestructive evaluation (NDE) and computational imaging.
- Applying ultrasonic testing (UT), radiographic imaging, and machine learning for defect detection in aerospace materials.
Technical Analyst – Materials & Process Physics
Boeing (September 2023 – April 2024)
- Assisted in developing data-driven quality control methods for composite and metallic materials.

Programming: Python, MATLAB, C++, Git, Docker, Kubernetes
Machine Learning: Deep learning, neural networks, signal processing
Computational Tools: TensorFlow, PyTorch, HDF5, HPC simulations
Nondestructive Evaluation (NDE): Ultrasonic Testing (UT), Radiographic Imaging, Barkhausen Inspections