Rahul Gannu

Project: Recognition of Everyday Activities Through Wearable Sensors

Activity detection is one of the demanding fields of research where human positions and movements can be identified. Data are captured from wearable devices such as smartwatches and performed data pre-processing as per the requirement. Applied required Machine Learning classifiers on the data through which the detection of human activities can be done with good accuracy and effectiveness.

Responsibilities:

• Performed Literature Research about methodology and the data that researchers have used before.
• Selected required algorithms from Machine Learning of the Prior Research.
• Chosen the data as per the requirement from UCI Repository.
• Performed pre-processing, and data cleaning as per the requirement.
• Driven data Insights by using visualization.
• Applied required classifiers to detect the daily activity and store the performance results concerning the classification metrics such as Accuracy, Precision, Recall and F1-Score.
• Compared the Performances of the classifiers with the previous model and emphasis the improvement of the chosen best model.

Project:

As part of WGS Member Enrollment - SIT we have monthly releases which need to be tested by using the online/ Batch process. It includes testing of Member's creation thru Mainframes screens/EDI 834 Files for SC/WV/CA Medicaid States.

Responsibilities:

• Analyzing the functional & business requirements and involved in preparing test scenario creation, test case creation, test data setup, test execution and defect management activities.
• Prepared Daily Status Report.
• Involved in Requirement Traceability Matrix.
• Maintaining issue & clarification log.
• Analyzing the regression suite for each release.
• Given KT sessions for the new joiners in the project.
• Interacting with the business team on test cases and test results walkthroughs.