Physicist

I support the Advanced Systems Integration T&E branch.

Senior Data Scientist

Team lead for new data science team. Responsible for generating actionable insights on force readiness for the USAF and USSF. Managing the development of interactive dashboards for analysis and visualization of readiness metrics.

Key Responsibilities:

• Lead new data science team
• Deliver force readiness insights for USAF & USSF
• Develop dashboards for senior leadership

Senior Data Scientist

Spearheaded a 40% reduction in turnaround time for performance analysis and error identification within the US Navy Joint Simulation Environment (JSE) program VV&A.

Key Achievements:

• Developed a suite of web applications using Bokeh and Flask, streamlining data analysis and visualization.
• Optimized server-database interactions, leading to improved hosting and scalability of analysis applications.

Data Scientist

Developed interactive dashboard for the analysis of the performance of the US Navy Joint Simulation Environment (JSE).

Key Achievements:

• Designed a modular framework, enabling rapid creation of customizable analysis layouts, resulting in increased efficiency and flexibility.
• Implemented an Ad Hoc workflow empowering users to define data filtering and visualization parameters, enhancing their ability to derive insights from complex datasets.

Research/Data Scientist

Oversee daily operations of the Electronics Support Lab (ESL), ensuring the timely completion of tasks and projects. Integrate into multiple physics research groups to support and mentor graduate and undergraduate research students.

Responsibilities:

• Conduct research in X-ray diffraction imaging, contributing to advancements in the field through innovative experimentation and analysis.
• Mentor and guide a team of 2-3 students in the development and implementation of an iterative phase retrieval algorithm in python for image post-processing, fostering their growth and learning in this specialized area.

Key Achievements:

• Introduced Scrum methodology to ESL, resulting in a significant increase in repair and design throughput. This agile approach streamlined processes and improved project management efficiency.
• Designed and successfully implemented custom Printed Circuit Boards (PCB) for physics experiments, optimizing data collection and experimental outcomes. This innovation enhanced the precision and reliability of experiments.
• Provided hands-on mentorship to 2-3 students, equipping them with practical skills in custom electronics repair, design, and construction. This mentorship not only benefited the students but also contributed to the department's overall expertise and capabilities.

Graduate Researcher

Apply Natural Language Processing (NLP) and Machine Learning (ML) to pioneering research in the field of Physics Education Research to enhance learning quantification and course satisfaction.

Key Responsibilities:

• Analyzing grader feedback data to gain insights into student learning experiences and course satisfaction, contributing to evidence-based instructional improvements.
• Developing and training Natural Language Processing (NLP) and Machine Learning (ML) models to extract valuable information from course feedback comments, enabling data-driven decision-making in course design and instruction.
• Creating an innovative NLP-based algorithm designed for efficient and accurate comment rating, streamlining the evaluation process of student feedback.

Key Achievements:

• Designed and implemented a comprehensive quantitative model leveraging grader feedback features, resulting in the accurate prediction of course satisfaction levels and final exam scores. This predictive model has been instrumental in optimizing course design and improving overall student satisfaction.
• Established a robust workflow pipeline for scraping comments from Google Classroom, performing data cleaning and pre-processing, and training NLP-based ML algorithms for the analysis of five critical comment features. This pipeline has significantly enhanced the efficiency and accuracy of feedback analysis, facilitating data-driven insights into instructional improvements.

Master of Science (MS) in Physics

Designed and built an instrument intended to be a 'ruler' able to make absolute frequency measurements of hyperfine transitions in a multitude of atomic elements.

Key Achievements:

• Laser Stabilization: Implemented advanced laser stabilization techniques by employing a high finesse confocal cavity and Pound-Drever-Hall locking, ensuring precise and stable diode laser operation critical for hyperfine transition measurements.
• Frequency Doubler Design: Designed and executed the frequency doubling process through Second Harmonic Generation (SHG) to achieve the necessary laser excitation, enabling accurate spectroscopic measurements.
• Data Acquisition System: Spearheaded the design and development of a comprehensive data acquisition system encompassing both hardware and software components, optimizing data collection and analysis for experimental results.
• Custom Python Code: Developed custom Python code employing the least squares method to fit acquired data to a Lorentz distribution, enabling the extraction of essential parameters with high precision and reliability.
• Ruler: The free spectral range from a Fabry-Perot cavity are the 'tick' marks of the ruler.
• Conference Presentations: Actively and regularly presented research progress and findings at esteemed academic conferences, contributing to the dissemination of knowledge and fostering collaboration within the scientific community.

Bachelor of Science (BS) in Physics

Developed a process to create metalic Micro Electromechanical (MEMS) Devices using templated verticaly aligned carbon nanotube (VACNT) forests that are then infiltrated with tungsten via chemical vapor deposition.