Yathartha Tuladhar
About Yathartha Tuladhar
Yathartha Tuladhar is a Software Engineer specializing in autonomy at Torc Robotics, where he has worked since 2020. He has a background in robotics and machine learning, with experience in various research and engineering roles across multiple organizations.
Work at Torc Robotics
Yathartha Tuladhar has been employed at Torc Robotics as a Software Engineer in the Autonomy division since 2020. In this role, he focuses on developing autonomy software specifically for self-driving trucks. His work includes key areas such as behaviors, path planning, and control, which are essential for the functionality of autonomous vehicles. His expertise in machine learning frameworks and advanced simulation tools supports the development and testing of algorithms for autonomous systems.
Education and Expertise
Yathartha Tuladhar holds a Master of Science degree in Robotics from Oregon State University, where he studied from 2017 to 2019. Prior to that, he earned a Bachelor of Science in Electrical and Electronics Engineering from The University of Texas at Arlington, completing his studies from 2012 to 2016. His educational background provides a solid foundation in both robotics and engineering principles, which he applies in his professional roles.
Background
Before joining Torc Robotics, Yathartha Tuladhar gained diverse experience in the field of robotics and software engineering. He worked as an Undergraduate Research Assistant at The University of Texas at Arlington from 2015 to 2016. He also served as a Robotics Autonomy Intern at Danfoss Power Solutions for three months in 2018 and held positions as a Graduate Research Assistant at Oregon State University from 2017 to 2019. Additionally, he completed a six-month internship as a Software Engineer Intern at Intel Corporation in 2019.
Technical Skills
Yathartha Tuladhar is proficient in various technical skills relevant to robotics and software development. He utilizes machine learning frameworks like PyTorch for developing and testing algorithms for autonomous vehicles. He is experienced in using advanced simulation tools such as Gazebo and MuJoCo, which are important for robotics applications. Furthermore, he is skilled in both Robot Operating System (ROS1 and ROS2), as well as computer vision techniques using OpenCV, enhancing the perception capabilities of autonomous systems.