🧬 Analyzed 30,000 genes from single-cell RNA sequencing data using Python's Pandas and Scanpy libraries. Identified 5 potential gene targets aimed at preventing Graft-Versus-Host Disease.

🛠 Developed an automated data analysis pipeline using Python to streamline preprocessing, analysis, and visualization. This became a reliable tool for lab researchers, reducing data processing time by 50%.

📊 Ensured data integrity through meticulous quality control measures using Python. This included data cleaning, normalization, and imputation, ensuring the reliability of research findings.

🚀 Engineered a Python application to automate drone flight route executions, reducing user intervention time from hours to seconds and increasing data collection efficiency by 200%.

🛠 Seamlessly integrated three open-source drone simulators into a single application, empowering users to choose their preferred simulation environment and increasing research flexibility.

📊 Leveraged scikit-learn to pinpoint 8 prevalent automated drone flight patterns. Conducted follow-up tests to establish data-driven benchmarks for selecting the best simulators for specific research purposes.

📊 Created a Python-based GUI application using openpyxl to automate data extraction from 5+ Excel files weekly, eliminating manual copy-pasting and saving 25 work hours per week.

📈 Implemented automated data analysis features to generate daily summary reports for lab procedures, reducing report generation time from 1-2 hours to approximately 5 seconds—eliminating 100% of user input errors.

🧬 Utilized R programming to analyze 1,000+ bacterial DNA sequences, evaluating the effects of gut bacteria on the immune systems of 30 IBD (Inflammatory Bowel Disease) patients. This research led to one publication in a high-impact journal.

🎓 As a Ph.D. student, I investigated the therapeutic potential of type 1 regulatory (Tr1) T cells in treating IBD using a mouse model. This research was recognized with two presentation awards.

🤝 Collaborated with lab members on comprehensive bioinformatics and statistical analyses. Identified relationships between specific bacterial species, isolating 6 inflammatory-promoting bacteria. This work contributed to a peer-reviewed publication.