About

Aditya Jain is an experienced researcher and computer vision engineer with a passion for building scalable technologies that can transform lives. With a Master's degree in Mechanical Engineering from Columbia University and a Bachelor of Technology in Mechanical Engineering from IIT Kharagpur, Aditya possesses a strong academic background and a wealth of technical expertise. Currently working as a Robotics Software Engineer at dorabot, Aditya has developed libraries for robotic perception, motion planning, robotic arm control, and sensor fusion using ROS2 & Gazebo in C++. He has optimized system architecture to improve cycle time by 8% by parallelizing planning, object detection, and scene monitoring. Aditya has also implemented OPC UA server and client communication to interface ROS2 services with PLC and network switches. Additionally, he has automated environment build and provisioning using virtualization and containerization through Docker. In his previous role as a Research Engineer at the Hospital for Special Surgery, Aditya designed a novel arthrometer mechanism using SolidWorks and validated its performance by conducting a human factor study and repeatability test. He developed tools to automate patient data extraction and visualization using Python and SQL, which reduced surgery planning time by 10% and presented insights to relevant stakeholders. Aditya also implemented statistical tools like Sensitivity Analysis in MATLAB to study the effect of surgical parameters on knee kinematics. As a Graduate Research Assistant at Columbia University in the City of New York, Aditya worked on the Learning-based Contact Reasoning and Blind Grasping Using Hand Proprioception project. He built an environment with a bin of objects, a 12-DOF robotic hand, and sensors to read proprioception data using Gym and MuJoCo. Aditya defined methods in Python to enable position control for the hand and collect & process the proprioception data & contact information. He also developed Deep Neural Network models using TensorFlow that take the proprioception data as the input and predict which fingers are in contact with the object and points of contact with an accuracy of 94% and 92% respectively. Aditya's technical expertise includes software engineering, computer vision, research science, object detection, SQL, Docker, Python, Reinforcement Learning, TensorFlow, and Neural Networks. With 2.94 years of relevant experience, Aditya has demonstrated his ability to apply himself in diverse and demanding situations and consistently deliver the right results through careful planning and collaboration.