Research Experience
Explore my diverse research journey spanning computational biophysics, machine learning, and data science. Each role has contributed to my growth as a researcher and problem solver.
School of Mathematical and Statistical Sciences
Role: Research Assistant under Dr. Eleni Panagiotou
Period: January 2025 – May 2025
Description: I collaborated with Dr. Panagiotou and Dr. Wenwei Zheng on a project aimed at learning how topological features change under varying conditions. This involved comprehensive analysis of simulations and their implications of changes on protein structure and function.
UGenome AI
Role: Bioinformatics Intern
Period: November 2024 – January 2025
Description: Created and optimized Python-based pipelines for DNA/RNA mutant allele frequency quantification using next-generation sequencing. Implemented filtering strategies to enhance variant calling accuracy and sensitivity in genomic data.
Decision Theater
Role: Research Aide
Period: August 2024 – December 2024
Description: Sole researcher on podcast sentiment analysis in the context of the 2024 presidential election. I presented findings, managed databases, ran models, and prepared research for publication, contributing to ASU health and policy initiatives.
NASA Glenn Research Center (GRC)
Role: Intern, CHP-PRA Team
Period: June 2024 – August 2024
Description: Designed and led a complete NLP pipeline for Mars mission data classification under Dr. Mona Matar and Dr. Hunter Rehm. Addressed multi-label imbalance using supervised and unsupervised learning to predict human system task categories for astronaut reliability planning.
CXFEL Beus Laser Laboratory
Role: Graduate Research Assistant & Data Analyst
Period: June 2023 – August 2024
Description: Built computational tools for crystallography at femtosecond resolution. Developed cxls_hitfinder (CNN for Bragg peak detection) and waterbackground_subtraction (signal optimization algorithm), enhancing accuracy in diffraction-based protein structure determination.
Notable Projects:
cxls_hitfinder: CNN for peak detection and parameter prediction in crystallographic datasets.
waterbackground_subtraction: Signal-processing algorithm improving diffraction peak detection in variable conditions.
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.