Research Projects

Meta and Multimodal Learning for Smart Visual Borescope Inspection

Develop an AI-driven video borescope by introducing a graph network-enabled meta-learning framework.

Sponsor: Oklahoma Center for the Advancement of Science and Technology (OCAST) and Baker Hughes


Towards AI-Enabled Autonomy of Robotics Inspection Platforms for Sustainability of Energy Infrastructure

Develop an integrated AI-driven robotic visual platform with autonomous dynamic path planning and safe navigation capability for inspection data collection and real time defect identification.

Sponsor: Department of Energy (DOE)


Development of Control Interface Components for Autonomous Vehicle Systems

Develop a super-resolution generative adversarial network (SRGAN) enabled vehicle seat pressure sensing system that can accurately sense and locate surface pressure. 

Sponsor: Institute for Advanced Engineering, Korea

Ubicomp2022_DemoVideo.mp4

Remote-controlled Robotic Arm based on Human Motions 

Develop a secure real-time remotely-controlled robotic arm platform using deep learning algorithm

Sponsors