Research and technical experiences.

Selected as 1 of 30 students from 700+ applicants for MIT Beaver Works’ Medlytics program, where I applied machine learning to biomedical problems across medical imaging and clinical data. I worked on projects involving skin-lesion classification, mammogram abnormality detection, and hypothyroidism prediction, with skin-lesion classification serving as my final capstone.

My work involved preparing biomedical datasets, developing and evaluating machine-learning models, and exploring how computational approaches can be applied to medical problems.

Selected from 2,000+ applicants for Stanford’s iGEM apprenticeship program, where I conducted research focused on neurodegenerative diseases and approaches for detecting and understanding disease-related biological changes.

I contributed through scientific research, coding and computational analysis, and writing. Our work developed into a published paper investigating the use of AI to identify microglial activation from 3D brain imaging as an early indicator of neurodegenerative disease.

Through MIT BioBuilder, I have worked on research exploring how engineered biological systems can address environmental and health challenges. My team developed a bioengineered filtration system using genetically modified bacteria to remove heavy metals from contaminated water.

I contributed across the project through scientific research, wet-lab work, biological engineering, coding, experimental design, and scientific writing. The project developed into a peer-reviewed design brief published in BioTreks. The system explored E. coli, B. subtilis, and P. putida as engineered organisms for biosorption, bioaccumulation, and bioprecipitation.

Through ISLE, I work on the development of WeSpeak and WeListen, two connected platforms designed around clearer communication and turning user feedback into structured, actionable information.

Mentored by Professor Pat Langley, I have contributed to both the web and mobile applications, building interfaces, application workflows, authentication, database functionality, and communication-management features. My work includes features for message refinement, satisfaction inference, conversations, internal notes, issue categorization, status management, dashboards, and administrative tools.

Conduct research at the University of North Georgia applying computational methods to problems in logistics and supply-chain analysis.

My work includes developing machine-learning pipelines, processing and analyzing data, applying natural-language processing to operational information, and building automated workflows that help transform raw data into structured research insights and reports.