About

Rakesh Abothula is a Senior Software Engineer at Samsung Research in Bangalore, with over 4 years of relevant experience. He is a strong engineering professional who graduated from the prestigious Indian Institute of Technology, Guwahati. Rakesh is involved in the design and development of Intelligent Vision and AR Solutions for Augmented Reality use cases at Samsung Research. He is a perpetual learner and extremely patient in delivering research output. Rakesh enjoys working in a diverse team and is always on the lookout for challenges. Rakesh has worked as a Software Engineer at Samsung, where he developed AR-Emoji and Deco Pic applications. He has a decent end-to-end understanding of AR-emoji and Deco pic applications, from getting a preview to rendering the output. Rakesh has also worked on Intelligent Vision and AR Solutions to incorporate new features and improvise the AR-emoji and Deco pic Apps. Currently, his work involves designing and building end-to-end solutions in Augmented Reality/Virtual Reality for Camera Applications in premium mobile devices. He designs and develops niche Computer Vision Algorithms and Deep Learning solutions for Multimedia. His current area of expertise involves Semantic Segmentation, Multi-model object detection and tracking, and Geometric and Deep Learning approaches for Multiview 3D Reconstruction. During his Summer Research Internship at Samsung, Rakesh worked on a Recommendation Engine for a Content-Delivery-Network (CDN). He analysed data extracted and parsed from Google Big Query, visualised data, and identified and isolated various parameters for the prediction algorithm from the said order Statistical measurements. He labelled the given data according to some heuristics and business logs from the data logs which were accessible. He used 'Stratified sampling' to reduce the size of the data set to be suitable for the model training and trained two models for performing recommendations, one being a "Neural Network" based approach, and the second one being a "Decision Tree Classifier" based approach. Rakesh's TechStack includes Software Engineering, Research Science, Mobile, Deep Learning, Object detection, Flask, Computer Vision, Object Detection, Python, Java, C, MapReduce, Pandas, and Neural Networks.