Assistant Professor, Harvey Mudd College

Department of Engineering

Ph.D, Aerospace Engineering, Stanford University

 Machine learning for scientific visualization and analysis, with emphasis on simulation development, computer vision, image processing, and human-computer interaction systems using biometric data. 

Research related to improving the relationship between people and robots. This ranges from using novel sensors to create more complex control structures to developments in soft robotics to prevent any physical injury to anyone interacting with the robot.

Sensor fusion and the integration of diverse sensor technologies;  intersection of computer science and electrical/computer engineering, as it relates to sensor systems

Fusion of mechanical engineering principles with cutting-edge computational techniques to improve GNSS positioning accuracy in smartphones.

Autonomous drone technology, particularly, the mechanical aspects of drones, and how to utilize sensors to allow autonomous precision and drone safety.

Embedded systems, computer vision, and machine learning.

Machine learning applications for navigation and state estimation, including graph neural networks and vision models.

Broad interests in robotics and autonomous systems; applying them to creative and innovative solutions for the future.

Computer vision and reinforcement learning for UAV applications.

Machine learning and algorithms for various applications ranging from GPS navigation to brain research.

Computer vision and its applications to autonomous navigation in space.

Intersections of Deep Learning, Computer Vision, and Natural Language Processing for research and industry applications.