• Led and managed complex Real-World Data (RWD) analysis, involving a dataset of over 27,000 unique patient records.• Utilized a diverse range of analytical approaches, including machine learning techniques, network analysis, and statistical methods such as chi-square tests, odds ratios, multivariate logistic regression, survival analysis, LASSO regression, and ANOVA, to investigate intra-cohort differences related to patients' pre-implantation risk factors and post-implantation complications.• Employed various statistical and inference techniques to gain valuable insights from the data, focusing on understanding the relationship between patient factors, particularly diagnoses, through the use of heatmaps and bi-plots.• Demonstrated expertise in handling databases like Global Unique Device Identification Database (GUDID), 510(k) Premarket Submission, Premarket Approval (PMA), and Healthcare Cost and Utilization Project (HCUP).• Designed and implemented data mining algorithms proficiently, enabling the effective extraction of alloy/metal information from the FDA database using fuzzy matching techniques.• Skillfully applied medical coding systems (ICD-10-CM/PCS, CPT, HCPCS) for comprehensive data analysis and research purposes.• Successfully fostered seamless collaboration with interdisciplinary teams, effectively communicating technical concepts and research findings to non-technical audiences, ensuring a thorough understanding across different stakeholder groups.

Active in a diverse set of research fields including subcellular trafficking and cellular dynamics, biomechanics, multifunctional cancer theragnostic, nanomedicine, and biomaterials.