Yuvaraj Govindarajulu

About

Embedded Lead - Secure Embedded AI Research at Bosch, Bengaluru (India)

Areas of Interest include - Embedded AI, TinyML, Secure Firmware Update, Secure Boot, Timeseries data & Signal Processing.

Master of Science (INFOTECH - Embedded Systems), University of Stuttgart, Stuttgart (Germany), with focus on AI for Embedded Systems.

Embedded Software Engineer (HMI & Secure Bootloader), Lorch Schweisstechnik, Auenwald (Germany)
Tutor, Deep Learning - Master Laboratory course, Institute of Signals and System Theory, University of Stuttgart (Germany)
Working Student - Embedded Prototyping for Automotive ECUs, Robert Bosch GmbH, Schwieberdingen (Germany)
Senior Software Engineer - Complex Drivers Development - Fuel Injection Software for Automotive ECUs, Robert Bosch, Bengaluru (India)

Connect with me on LinkedIn or Xing. Write to me on yuvaraj.rajulu@gmail.com

Title: Human Activity Recognition and Study of Dynamic Filter Networks for Position-aware detection

Aim: To build a generic framework for Human activity recognition using smartphone Inertial sensors, use of Dynamic Filter generic networks to build a single activity recognition model for multiple positions
Building Recurrent Neural Network models for multi-variate time series data.
Signal pre-processing steps: Design and use of filters for noise and gravitation component removal, data normalization, sensor time-synchronization and sliding window techniques.
Study of multi-input, multi-output neural network architectures using concepts of Dynamic Filter Networks.
Libraries used: Tensorflow, Keras, Matplotlib, Scikit, Pandas among others.
Use of Tensorflow profiling to visualize tasks between CPU and GPU to identify performance bottlenecks.
Deployment of trained model on an Android smartphone using Tensorflow lite.