Dr. Xiao Pengdong
Dr. Xiao Pengdong holds two Ph.D. degrees: one in information engineering (major in computer vision and robotics) from The Australian National University, Australia; and the other in mechanical engineering from the State Key Laboratory of Mechanical Transmission (SKLMT) at Chongqing University, China. He also has two master’s degrees, the first in computer science and the second in robotics. Prior to his faculty position at DigiPen (Singapore), he was a Research Fellow at Nanyang Technological University, Singapore, focusing on research in computer vision and deep learning for smart digital towers in air traffic management (ATM). Previously, he had many years of experience in both academia and the software industries in the U.S., Australia, and Singapore, including the University of North Carolina at Chapel Hill, Data61, A*Star I2R, Sybase, and Motorola.
Pengdong’s research interests include computer vision, machine learning, medical image analysis, computer graphics and robotics. He is actively exploring the applications of artificial intelligence (AI) and computing in 1) biology, medicine, and dentistry: cell tracking, human brain (hippocampus) and craniofacial shape analysis, and feature tracking in cardiovascular diagnosis; 2) finance, banking, and gaming; and 3) the mechanical, automotive, and aerospace engineering fields: robotics, autonomous driving, and ATM. At the same time, he is also actively investigating the intersection and interplay of AI (vision and learning), video games, and augmented reality (AR) and virtual reality (VR). Beyond these, his other strong interests include vision-based perception in mobile robots/autonomous driving/unmanned aerial vehicles (UAV) and ATM with deep learning: object detection and tracking (2D computer vision) and visual SLAM (3D computer vision). Some of his research has been published in IEEE Transactions on Image Processing (TIP), IEEE Journal of Translational Engineering in Health and Medicine (JTEHM), and Nature Methods.
Pengdong enjoys interacting with students and sharing his knowledge and experience acquired during his research career while working in academic institutions and industry. Currently, he teaches courses in computer vision and machine learning.