About

Jewel Jose is an experienced ADAS Perception Engineer at AVL with over 6 years of relevant experience. He has a Master's degree in Embedded Systems from Technische Universität Chemnitz, a PG Diploma in Embedded Systems from the National Institute of Electronics and Information Technology, Calicut, and a Bachelor's degree in Electronics and Communication Engineering from the University of Calicut. Jewel has hands-on experience with various Deep Learning frameworks such as Tensorflow and Keras and other Machine Learning libraries. He has implemented and tested state-of-the-art Deep Learning research papers and has experience in Computer Vision and Data Analysis. Jewel is also skilled in integrating Software Components with ROS (Robotic Operating System) and is proficient in tools such as Git and Docker. Jewel has worked with Fraunhofer IPA as a Master Thesis candidate where he worked on Human activity recognition for robots, using RGB-D images and gained experience in Deep Learning, ROS, Keras, Cpp, and Python. He has also worked with IAV GmbH as an Intern where he generated a wrapper for C++ functions so that it can be used by Python code and gained experience in SWIG, Cpp, Python, and Cmake. Currently, Jewel is working with AVL, where he is responsible for Software Development for ADAS & AD, Semantic Segmentation, Object Detection, and Lane-Line Detection. He is proficient in Deep learning, Tensorflow, Keras, ROS, OpenCV, Python, Cpp, Matlab, Git, and Docker. Jewel's tech stack includes Keras, Deep Learning, Python, Docker, Tensorflow, Object detection, Computer Vision, OpenCV, Object Detection, test, ML, Research Scientist, and Software Engineer. With his extensive experience in the field, Jewel is a valuable asset to any team he works with.