About

Laavanye Bahl is a highly skilled Senior ML Research Engineer with a focus on deploying state-of-the-art (SOTA) research to real-time robotics applications. Currently working with Motional's research team, Laavanye is solving various ML problems for self-driving robo taxis, with a primary focus on Lidar-based 3D object detection and tracking. Laavanye has extensive experience working with various robots, including consumer, home, self-driving vehicles, manipulators, and drones. During her time at Carnegie Mellon University, where she completed her Master of Science degree in Robotics, School of Computer Science, Robotics Institute, Laavanye worked on several robotics projects. Before joining Motional, Laavanye worked as a Perception Research Intern at Aptiv (nuTonomy), where she developed an autoregressive robust multi-sensor (cameras, LiDAR) 3D object tracker using deep learning. She also worked as a Research Engineer at Nanyang Technological University, where she automated a vehicle from scratch in just five months, developed a real-time object detection pipeline with distance measurement using stereo camera, and integrated NDT mapping for robust 3D SLAM with Velodyne LiDAR. Laavanye has a Bachelor of Technology degree in Computer Software Engineering from Delhi Technological University (formerly DCE) and completed high school from Modern School, Barakhamba Road. She is proficient in Python, PyTorch, C++, ROS, OpenCV, and TensorFlow, among other tech stacks. Overall, Laavanye has 4.12 years of relevant experience and is an expert in research science, ML, object detection, and deep learning. She can be contacted at laavanye.bahl@gmail.com.