Ali Asmari, PhDProgram Manager- Robotics Roadwork and Excavation Systems ULC Robotics
Dr. Ali Asmari is currently supervising all the AI and Machine Learning development for ULC Robotics. In addition to leading the ML team, he is managing the Robotic Roadworks and Excavation System (RRES) at ULC. Dr. Asmari has an MS in the robotics and automation and a Ph.D. in Mechanical Engineering with specialization in Computer Vision and Machine Learning from Oklahoma State University. Since his graduation in 2014, he has been actively involved in the development of autonomous systems and robotic solutions. Prior to his work at ULC, Dr. Asmari has spent over fifteen years in the field of robotics, with experience in design and development, Automation and Control, Computer Vision, and Machine Learning and has led projects in a diverse set of industries.
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Utilizing Machine Learning to Solve the Challenges of the Energy Industry
ULC Robotics assists gas and electric companies and the broader energy industry to keep up with the increasing need to repair and maintain their infrastructure while causing less disruption to the public, reducing the greenhouse gas emissions and lowering costs by developing and deploying innovative robotic repair solutions and advanced inspection systems.
Through the deployment of advanced robotics, ULC gathers an abundance of data for different inspection purposes every year. With the acquisition of data comes the time-consuming challenge of processing and interpreting the data which requires highly trained experts. By developing customized deep learning models that learn over time and are tailored to specific applications, ULC can process all of the acquired data and produce reliable, repeatable, and accurate reports to serve different sectors of the industry.
In this talk, Dr. Asmari will present a diverse set of applications of Machine Learning and Artificial Intelligence in the energy industry that has been developed and deployed by ULC Robotics. These methods cover a broad range of applications such as identification of whales in aerial images to protect the endangered species, and development of an autonomous inspection system for mapping and monitoring electric and gas networks to improve maintenance and repair operations.