Developed a real-time, deep-learning/logistic regression hybrid model to monitor customer service chats and dynamically predict the probability of a positive outcome.
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Successfully flagged 75% of negative outcomes at the midway point of an ongoing conversation.
Constructed ETL and data cleaning pipelines for a national-scale dataset of Fire Department records. Then augmented the dataset with publicly available socio-economic, spatial, and temporal data.
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Developed an XGBoost regression model using the augmented dataset to predict emergency incident call volumes and help Fire Departments in their approach towards proactively mitigating community risk.
Maintained a liver cancer cell line and studied the molecular pathways linking liver cancer to the Hepatitis B virus.
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Developed gRNAs to perform CRISPR/Cas9 knock out of the FGFR2 gene in order to investigate drivers of bile duct cancer.
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Demonstrated the viability of a novel drug delivery system with the potential to help those who struggle with metabolic disorders such as dyslipidemia.
