Faculty Directory

Biography

Kaveh Fathian is an Assistant Professor of Computer Science at the Colorado School of Mines. Before joining Mines, Dr. Fathian was a research scientist at MIT. He received his PhD degree in Electrical Engineering, MS degree in Mathematics, and MS degree in Electrical Engineering from UT Dallas. His research is focused on robotics and computer vision topics such as robust perception, visual navigation, simultaneous localization and mapping (SLAM), multi-robot SLAM, and multi-agent systems.

Dr. Fathian leads the Autonomy, Robotics, and Intelligent Algorithms (ARIA) lab at Mines. The mission of the lab is to pioneer algorithmic technologies for robust and resilient robotic perception and autonomy, such as certifiable perception, novel relaxation techniques for computationally challenging optimization problems with optimality guarantees, and data association algorithms robust to extreme outlier ratios (>99%). His research is further extending these technologies to multi-robot teams to create a resilient cyber-physical internet of robots that communicate and compute on the edge and the cloud.

Personal web page

Education

• PhD degree in Electrical Engineering from UT Dallas (2018)
• MS degree in Mathematics from UT Dallas (2013)
• MS degree in Electrical Engineering from UT Dallas (2013)
• BS degree in Electrical Engineering from IKIU, Iran (2010)

Research

Kaveh Fathian is an Assistant Professor of Computer Science at the Colorado School of Mines. Before joining Mines, Dr. Fathian was a research scientist at MIT. He received his PhD degree in Electrical Engineering, MS degree in Mathematics, and MS degree in Electrical Engineering from UT Dallas. His research focuses on robotics and computer vision topics such as robust perception, visual navigation, simultaneous localization and mapping (SLAM), multi-robot SLAM, and multi-agent systems. Dr. Fathian leads the Autonomy, Robotics, and Intelligent Algorithms (ARIA) lab at Mines. The ARIA lab's mission is to pioneer algorithmic technologies for robust robotic perception and autonomy, such as certifiable perception, novel relaxation techniques for computationally challenging optimization problems with optimality guarantees, and data association algorithms robust to extreme outlier ratios. ARIA lab is further expanding these technologies to multi-robot teams to create a resilient cyber-physical internet of robots that communicate and compute on the edge and the cloud.

• Simultaneous Localization and Mapping (SLAM)
• Certifiable, Robust, and Resiliant Algorithms
• Multi-Agent Systems and Multi-Robot SLAM
• Field Robotics and Applied Machine Learning

Labs & Research Centers

Autonomy, Robotics, & Intelligent Algorithms (ARIA) Lab