About

Ajay Charan is a Senior Autonomy Engineer with over 4 years of industry experience in writing production level code for real-time autonomous systems spanning across localization, mapping, and perception. He has worked in big companies as well as startup environments with efficiency and delivered key improvements to the software stack. Ajay received his Masters of Science from the University of Pennsylvania and was a summer researcher at National University of Singapore in UAV group. He worked on Visual Navigation for UAVs and developed an algorithm for collision avoidance based on COLREGS. Ajay is a hard worker and passionate about his work. He loves to solve problems and is not afraid to get his hands dirty in the process. He has done a fair share of both software and hardware debugging to get the system working. Ajay is a team player and would be glad to be a part of a team of like-minded people. He has patents in his name and is always looking for opportunities to learn and grow. Currently, Ajay is working at Caterpillar as a Senior Autonomy Engineer. He is working on developing software for autonomous vehicles' real-time perception using camera, radar, lidar for detection, tracking, obstacle grid creation, and ground surface estimation. He has migrated the code to a new build system and created middleware agnostic code and data structures. He is also helping with the deployment of the latest stack on the test platform. In the past, Ajay has worked with Cornami, Inc. as a Senior Software Engineer, where he used ML and other techniques for optimizing core placement/operation assignment on the compute fabric. He wrote C++ APIs for the end-users to ease in software development for the new chip, which enabled easier adoption of the product by users and reduced the learning curve by acting as a middleware between them and the custom codebase. He has also worked with Perceptive Automata as a Senior Software Engineer, where he was a member of DEI committee and developed and implemented Detection and Tracking of human pedestrians using sensor fusion in camera and lidar space. He leveraged Deep Learning and classical techniques like Kalman filter, semantic segmentation, object detection, and automated camera calibration and camera-lidar calibration to reduce operator time and improve data collection quality. He also implemented Localization and Odometry estimation of Autonomous Vehicle to enable a better position estimate for the car. Ajay's tech stack includes Computer Vision, ML, Python, Software Engineer, test, Research Scientist, Object detection, Object Detection, and Deep Learning. He