• Conducted interviews with executives and experts, including vice presidents and medical researchers from leading biopharmaceutical companies such as Roche and Moderna, to gather insights on the machine learning models for virtual tissue staining to advance cancer research and diagnostics.• Analyzed data on biopharma algorithm development costs, providing Pictor Labs with benchmarking pricing for their machine learning solutions.• Drafted analyses of commercialization plans for virtual tissue staining in digital pathology for spatial biology; integrated interview outcomes and analyses into a comprehensive report for company executives.

Core team member of NLP project working in collaboration with the Priceline Group with focus on building supervised and unsupervised ML models as well as improving travel recommendation algorithms.

• Core team member of the machine learning project in collaboration with the technical directors/medical experts at MSK, concentrating on analyzing clinical and genomic data to develop survival analysis for cancer patients.• Built regression analyses on genomic data to pinpoint genes with significant impact on cancer detection results.• Constructed supervised machine learning models by utilizing clinical data for patient survival prediction.• Identified areas for model optimization and proposed research suggestions to medical researchers in the hospital.