• Optimized the hyperparameters of a Genetic Algorithm-based pipeline, resulting in >2% increase in chemical manufacturing throughput over baseline.

• Researched alternative approaches and made suggestions to improve the quality of recommendations made by the existing cross-sell model.

• Identified and fixed a “silent” bug preventing the proper removal of outliers.

• Developed a real-time, deep-learning/logistic regression hybrid model to monitor customer service chats and dynamically predict the probability of a positive outcome.

• 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.

• 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.

• Developed gRNAs to perform CRISPR/Cas9 knock out of the FGFR2 gene in order to investigate drivers of bile duct cancer.

• Demonstrated the viability of a novel drug delivery system with the potential to help those who struggle with metabolic disorders such as dyslipidemia.