Bao Thach is a Ph.D. Computer Science student at the University of Utah, advised by Prof. Alan Kuntz and Prof. Tucker Hermans. He is broadly interested in robot learning, a field at the intersection of machine learning and robotics. Bao is a full-stack roboticist with extensive experience in robot motion planning, control, learning, and perception.
Ph.D. in Computer Science -- Machine Learning and Robotics
University of Utah
B.S. in Electrical Engineering
Summa Cum Laude -- Texas Christian University
We initiate the first method for solving the impractical goal specification problem in robotic deformable object shape servoing, by architecting a neural network that predicts the object’s goal shapes using human demonstrations.
We pioneer a novel machine learning pipeline for robotic manipulation of deformable objects in surgery and warehouses, by developing a novel neural network that predicts robot actions based on point cloud observation. My work outperforms the previous learning-based method by 240% in terms of Chamfer distance.