Responsibilities include:

• Investigate the role of Liver Receptor Homology 1 (LRH-1) in regulating neutrophil functions relevant to cancer progression
• Conducted physical, chemical, and biological laboratory experiments, supporting data acquisition from cell cultures, mouse studies, and genotyping to advance research objectives
• Set up appropriate instruments, materials, and apparatuses; operate laboratory equipment required for genotyping
• Collaborated with colleagues on various tasks, including data collection and analysis, to enhance research outcomes and foster a team-oriented environment

Responsibilities include:

• Managed rodent husbandry and handling, including manual restraint, injections, tumor measurement, and necropsy, ensuring adherence to ethical and regulatory standards
• Applied both in vitro and in vivo methodologies to design and execute hypothesis-driven experiments, enhancing the robustness of research findings
• Developed RNA sequencing analysis pipelines for the laboratory, incorporating advanced network analysis techniques such as Weighted Gene Co-expression Network Analysis (WGCNA) to derive meaningful insights
• Collaborated effectively with colleagues within the laboratory and across departments to drive interdisciplinary research initiatives and share knowledge
• Mentor and supervise 4 undergraduate student researchers in experiment setup, execution, and data analysis, enhancing their practical skills and research competencies

Responsibilities include:

• Leveraged biomedical expertise to assist in training machine learning models across various projects, enhancing predictive accuracy in healthcare applications
• Facilitated research on treatment entity annotation for breast cancer and diabetes, contributing to the development of datasets used in machine learning algorithms
• Reviewed and analyzed abstracts from PubMed research papers, meticulously identifying and extracting treatment references to create high-quality training data for machine learning applications
• Utilized the ‘Brat’ tool to annotate treatment entities, ensuring precise classification according to established thesis guidelines, demonstrating strong attention to detail
• Collaborated with interdisciplinary teams to advance research methodologies, contributing to the integration of machine learning techniques in biomedical studies

Responsibilities include:

• Proposed and completed master’s-level thesis research on the correlation between breast cancer and cholesterol
• Applied literature-based discovery (LBD) methodologies to extract and analyze data from scientific literature, uncovering potential mechanisms linking cholesterol and breast cancer through data-driven insights
• Utilized the Arrowsmith website and PubMed to perform comparative analysis of research studies, leveraging text mining techniques to aggregate relevant data on how cholesterol influences breast cancer progression
• Formulated and tested hypotheses regarding cholesterol and breast cancer associations, employing analytical reasoning and modeling to propose new research directions and inform future studies

Responsibilities include:

• Discovered gene interaction of the bacterial butyrate synthesis pathways (acetyl-CoA, glutarate, 4-aminobutyrate, and lysine pathways) between microbial species (Firmicutes, Proteobacteria, Fusobacteria, etc.) and their hosts through literature review
• Discovered gene interaction of the bacterial butyrate synthesis pathways (acetyl-CoA, glutarate, 4-aminobutyrate, and lysine pathways) between microbial species (Firmicutes, Proteobacteria, Fusobacteria, etc.) and their hosts through literature review
• Developed proficiency in Linux for managing gene sequence data, enhancing data processing capabilities and ensuring efficient handling of large genomic datasets in research projects