Prathik Kodanda Murthy
Angestellt, Machine Learning Engineer, Bosch Engineering GmbH
Karlsruhe, Deutschland
Über mich
I am an adept Mobility Systems Engineer with a specialized Master’s degree from Karlsruhe Institute of Technology, focused on ADAS and autonomous driving. My professional experience spans prominent roles within the automotive industry, including significant contributions to Bosch, where I have honed my skills in developing and implementing cutting-edge machine learning models to advance automotive systems. My technical proficiency is extensive, particularly in C, Python and machine learning frameworks essential for high-stakes data analysis and system enhancement in automotive applications. As an innovator, I am dedicated to leveraging artificial intelligence and bring a proven track record of pioneering solutions that push technological boundaries, making significant impacts on project outcomes and productivity. I thrive in dynamic environments, constantly seeking new challenges that allow me to drive forward the future of mobility with fresh, impactful ideas.
Werdegang
Berufserfahrung von Prathik Kodanda Murthy
Bis heute 6 Monate, seit Jan. 2024
Machine Learning Engineer
Bosch Engineering GmbH
Master Thesis : Generative Al for enhancement of simulation data from Ultrasonic sensor simulation A deep learning solution to enhance the simulated ultrasonic echo data to look more closer to a real sensor data from vehicles using a style transfer approach with Cycle GANs. The model will be deployed for testing Automated Parking functions.
Data Engineer for automotive power train sensors. Deployed machine learning algorithms with MS Azure , leveraging AutoML. Implementation of new NaN handler functional for automotive sensor data
Bis heute 6 Jahre und 11 Monate, seit Aug. 2017
Senior Software Engineer
Robert Bosch Engineering and Business Solutions LimitedDeveloper for Anomaly detection for power train sensors using Deep Learning techniques (Autoencoders , GRUs and LSTMs). Embedded Software Developer for exhaust after treatment sensors and components. Developed novel approaches for dosing AdBlue Recipient of multiple innovation awards aimed at solving niche mobility problems in development environment.