Sakshi Thakar

Project Lead: Knee-bony Anatomy Segmentation

• Led a team of four researchers, including orthopedic surgeons, to implement and validate a detailed manual image segmentation plan, resulting in selection for manuscript presentation at the IEEE conference in Pittsburgh, October 2023.
• Supervised six research assistants in annotating 600+ X-ray images, leveraging Python image analysis packages. Collaborated with orthopedic surgeons to refine AI algorithm accuracy, showcasing effective cross-functional teamwork.
• ·Developed an ITK-SNAP software training guide for X-ray image annotation, ensuring seamless onboarding of new research assistants.

• Trained a team of 10 undergraduate students to proficiently utilize the Events Management Database system and Social Tables software, resulting in enhanced customer satisfaction through timely resolution of over 100 event inquiries.
• Developed a 150-slide PowerPoint guide for new incoming graduate students, improving their transition into university events management roles and enhancing operational efficiency and customer satisfaction.
• Increased Events Management Database (EMS) capacity by 20% during the fall 2023 semester by strategically deactivating dormant user accounts through proficient utilization of the PeopleSoft accounts management system.
• Formed a comprehensive troubleshooting guide for incoming graduate students, effectively addressing common user inquiries related to the events management database, resulting in a 20% reduction in IT tickets during the Fall 2023 semester.

• Processed and validated 1,000+ wound care clinical trial data points per Standard Operating Procedure (SOP) and Data Management Plan (DMP) criteria, ensuring data accuracy and integrity using advanced Excel formulas and database procedures.
• Issued 80+ queries in Electronic Case Record Forms (eCRFs) using the Viedoc database, enhancing data quality through complex data management techniques and data validation procedures
• Reduced data collection errors by 50% by proposing and implementing a checkbox feature in the Viedoc database, enhancing data quality and accuracy through collaboration with site coordinators
• Uncovered key trends, patterns, and inconsistencies in validated data through in-depth statistical analysis using Excel, generated reports outlining the key trends and presented three possible solutions to minimize data error at final project presentation
• Prepared FDA submission data for 50+ subjects by performing data quality checks and ensuring compliance with FDA standards for Pre-Market Approval (PMA), including database lock.