Vishwesh Bhagwat

• Project involved – I. Data collection and data preprocessing II. Deep Learning-based Anomaly detection method development III. real time implementation IV. Deployment on simulator using docker • Key characteristics – I. Compatible with any test benches II. Provides one-click solution for technician using test bench with no background in machine learning III. Can be used even remotely • Successful implementation will allow early stopping of anomalous test procedures which can save huge resources.

• Studied various deep Learning based multivariate time series anomaly detection approaches from literature. • Responsible for implementing the selected approaches in python using TensorFlow and optimizing those on powertrain test data. • Created a library of methods for multivariate time series anomaly detection which can be used for comparative study.

• Responsible for development of lecture, exercise content for the preparatory course in Mathematics for incoming master’s students

• Responsible for providing engineering support to assembly and sales department • Responsible for communicating with internal and external stakeholders to track the project status

• Experience of managing assembly lines and establishing new press shop in the company

Machine Learning, Advanced Machine Learning, Computer Vision, Computer science in Mechanical Engineering, Introduction to Artificial Intelligence, Artificial Intelligence and Data Analytics for Engineers