Ronak Pambhar

- End-to-End Integration and Sequence Testing. - Support at Bug Management and Process Automation. - Report Generation and Documentation using Project Management Tools - JIRA and Confluence. - Actively Supporting ORUNext Project in domain E2E Integration. - Flashing ECUS with newest Software Version. Skills: Manual Testing · CANoe · Jira · ReadyAPI · REST APIs · Confluence · Python (Programming Language)

- Design and implementation of a fully automated method into an existing software framework (Digital Twin). - Extending the available digital capabilities for additional edge shell requirements. - Addressing the lack of robustness for convergence issues. - Development of automated reporting capabilities. - V&V through automated testing. Skills: Git · Python (Programming Language) · Microsoft Word · Microsoft Excel

"Prediction of accident severity and restraint strategy using database approaches". - Performance of two-stage FEM simulations with CAE tool LS-Dyna for frontal impact, vehicle and occupant level. - Preparation of MATLAB scripts and extraction of data from the simulation. - Programming of machine learning and neural network algorithms to predict the activation of restraint systems and their time. Skills: Machine Learning · LS-DYNA · Python (Programming Language) · MATLAB

- Routine and necessary repairs. - Inspections to ensure the safe and efficient operation of equipment and machinery. - Maintenance of existing plant equipment. - Monitored operation in the machine control room.

- Estimate the cost of repair or maintenance of the vehicle. - Identify recurring faults, repair and maintenance work. - Check workshop activities, check completed work for compliance with the safety regulations.

- It was a holiday work experience for the student. I learned about car parts and how they work. - Lesson about car parts and their functions and how to treat a crashed car in the workshop.

Master project (grade: 1.3): "Prediction of crash severity using database approaches". - Defined the methodology and programmed the ML code for predicting crash severity in a frontal impact. - In addition, optimised the best-fit ML model for predicting head injury criteria. - Tools: Python, MATLAB, LS-dyna

Bachelor project (grade: 1.5): "Performance improvement of car radiator coolers by using nano-fluid". - The task was to use different nano-fluids as coolants in car radiators and then analyse the heat transfer properties. The parameters evaluated in this study were heat transfer coefficient, thermal conductivity, Reynolds number, volume concentration fraction and heat transfer rate. - Tools: Computational Fluid Dynamics (CFD) analyses, ultrasonic homogeniser, accurate weight machine.