Vasu Chukka

• Developed a data-driven approach for modeling a Lithium-ion battery by using Neural Networks. • Built a data pipeline (Data collection, Preprocessing, Training, Validation) which represents pre-processing to actual training of NN’s and validating the results. • Validated models with reference measurements and compared with other model architectures and as well as to conventional battery models.

• Developed a simulation environment that provides a battery model from the data. • Implemented data pipeline which makes building models more efficient and simplified. • Trained models and created test data sets to validate the effectiveness of the algorithms and to ensure that the models are accurate and efficient.

• Deep Learning (Linear algorithms, Neural Networks, Deep Learning, RNN) & Neurocomputing • Computer Vision • Multicore-Programming • Realtime Systems • Software Platforms for Automotive Systems • Embedded software lab • Automotive Software Engineering (CAN, AUTOSAR, Test)