Sourav Garg obtained his Bachelors in Electronics and Communication from Thapar University, India in 2012. He then worked as a researcher at Innovation Labs, Tata Consultancy Services (TCS), India, where he conducted research at the intersection of robotics and computer vision, solving problems like pedestrian detection and tracking, product counting in a retail shop environment, and developing a tea-serving robot for an office environment. During his PhD at Queensland University of Technology (QUT), Australia (2015-2019), he explored the research problem of visual place recognition and navigation, developing novel methods for image representation and image matching, particularly those based on semantic scene understanding. Sourav is currently a Research Fellow at QUT and working on large-scale localization - potentially involving billions of places - with sub-linear complexity in both space and time. He regularly publishes and reviews robotics research in top-tier conferences and journals like IJRR, RSS, ICRA, and IROS.