Research Experience
I have a diverse portfolio of projects ranging from deploying Natural Language Processing (NLP) models at NASA, to research in experimental crystallography imaging. Below is a brief overview of the key projects. For a more comprehensive insight, consider downloading the full CV.
Computational Statistics Collaboration in Item Response Theory (IRT)
Role: Collaborator/Co-Author
Period: January 2023 - present
Description: Engaging in various research projects with Yi Zheng and Mark Reiser focusing on managing preprocessing, conducting simulations, developing software, and documenting performance evaluations of R's mirt package under the 2PL IRT model. Created comprehensive visualizations of RMSE and bias metrics for all simulated subjects, enhancing the interpretability and impact of our findings.
Decision Theater
Role: Research Aide at ASU's Decision Theater
Period: August 2024 - present
Description: As a Research Aide at Decision Theater at ASU, I contribute to a variety of research activities including writing briefs, conducting complex research using diverse methodologies, and maintaining comprehensive research documentation as well as contributing to some programming projects. Manage databases, run models and tools for presentations, and present findings to audiences in large part to support the decisions made during ASU Health's creation. My role also involves presentation and public speaking, writing, and editing material for publication and maintaining detailed research documentation.
NASA Glenn Research Center (GRC) Intern
Role: Human Reliability Analyst at NASA Glenn Research Center
Period: June 2024 - August 2024
Description: In the preparation for future manned missions to Mars and aiding in the Human Research Program, I was in charge of developing and deploying NLP/Language Models to analyze astronaut tasks and predict which human system would be used. This effort provides quantifiable risk assessments essential for mission planning and ensuring astronaut safety, performance for long-duration missions. Under the Crew Health and Performance Probability Risk Assessment (CHP-PRA) team, my work involved extensive research and application of various statistical machine learning techniques to best get the job done. This internship was under the wonderful guidance of Dr. Mona Matar and Dr. Hunter Rehm both at NASA GRC.
CXFEL Beus Laser Laboratory
Biodesign Institute, CXFEL Beus Laser Laboratory 
Roles: Graduate Research Assistant, Research Aide, and Data Analyst
Period: June 2023 - August 2024
Description: In my capacity as a Data Analyst and Research Aide, I engaged in developing Python packages tailored for high-throughput experimental crystallography imaging and conduct data analysis to bolster biophysics research.
Project 1: One such project was a deep learning model called cxls_hitfinder that over thousands of images, the model learned the parameter combinations of interaction distance (cm) and photon energy (keV) that were used to generate the images. We also accounted for the realistic scattering patterns that would be seen in each discrete parameter combination. This model was pivotal in the development of a novel hit-finding algorithm that has since been integrated into the laboratory's data analysis pipeline.
Project 2: This project, waterbackground_subtraction involves a sophisticated analysis of improving the signal photon count estimates of both high and low flux diffraction images. The rational is: because the high flux X-ray is destructive to the crystal protein sample during data acquisition, we can infer the true number of photons at each Bragg peak from the low flux image. This tool will be used mainly for post-hoc analysis of large quantities of data collected during experiments.
BioXFEL
Supported research grant by the NSF. Take a glimpse into the work being done as a BioXFEL Scholar:
For more of my work, follow me on GitHub:
To explore more about these projects, visit the project-specific links or reach out directly via the contact details provided on the site.