Alankar Sinha

"Surrogate modelling of a high-fidelity Injection Moulding simulation." • Creation of a Python workflow that uses simulation input and output data to generate a surrogate/machine learning model using an active learning technique that iteratively updates the sampling method according to the importance of the input parameters. • Optimization of the simulation parameters using the surrogate-enabled analysis framework and the experimental data.

• Data wrangling and Data manipulation using Python’s Pandas and Numpy to extract knowledge from high-volume wind turbine load datasheets. • Created user interface using dash Plotly to visualize and perform data operations. • Performed internal force analysis on the rotor shaft.

• Led and assisted Post-market Quality Management project in Life Science by working and coordinating with representatives from different geographies. • Designed and developed an Excel-based Behavioral model to automate analysis and efficient management of key performance indicators (KPI)/Corporate metrics. • Well-acquainted with SAP Business Object to generate reports and perform analysis. • Performed root cause analysis for medical device/implant failure using historical data.