Ph.D
The development of safe and reliable autonomous vehicles (AVs) hinges on robust computer vision (CV) systems. This research project explores novel CV techniques for enabling AVs to perceive their surroundings and make informed decisions. The successful candidate will delve into various aspects of computer vision for autonomous driving, including:
The candidate will be involved in:
Sarah Thomas is a Professor of Computer Science at Stanford University. She received her PhD in Computer Science from MIT in 2004. Her research interests include machine learning, artificial intelligence, computer vision, robotics, and natural language processing. She has published over 100 papers in top academic conferences and journals. She has also received several awards for his research, including the ACM SIGKDD Innovation Award, the NSF CAREER Award, and the Google Faculty Research Award. Professor Thomas is a passionate teacher and has won numerous teaching awards. She is also an active member of the computer science community and has served on several program committees and editorial boards. She is a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) and the Institute of Electrical and Electronics Engineers (IEEE).
• Strong foundation in computer science with a focus on computer vision and deep learning. • Experience with computer vision libraries like OpenCV or PyTorch. • Programming skills in Python and familiarity with robotics platforms (desirable). • Understanding of sensor fusion techniques and machine learning for autonomous systems. • Excellent written and verbal communication skills. • Strong foundation in computer vision algorithms and deep learning architectures for CV tasks.