Courses at CU Boulder
Course Offerings
MCEN 5228-010
Geometry and Learning-based Methods in Computer Vision
This is an advanced graduate course that deals with classical geometric and deep-learning methods in computer vision. The course begins with the mathematical foundations of computer vision and advances to recent deep-learning methods. It introduces formal perception tools for students interested in robot autonomy and 3D perception.
Course DetailsCourse Offerings
MCEN 5228-003
This advanced cross-listed undergraduate and graduate course develops the mathematical foundations and engineering practice of classical machine learning through modern deep learning. Topics span perception, language, optimization, responsible AI, vision, NLP and LLMs, generative modeling, and reinforcement learning.
Course DetailsCourse Offerings
MCEN 5228-009
Geometry and Learning-based Methods in Computer Vision
This is an advanced graduate course that deals with classical geometric and deep-learning methods in computer vision. The course begins with the mathematical foundations of computer vision and advances to recent deep-learning methods. It introduces formal perception tools for students interested in robot autonomy and 3D perception.
Course DetailsCourse Offerings
Senior Design
with Prof. Michael Hannigan
The University of Colorado Boulder's HAQ Lab is developing RALPH-E 3, an autonomous rover designed to monitor methane emissions in landfills while navigating challenging terrain. The capstone project emphasizes robust mobility, reliable sensor integration, and autonomous operation.
Course Details
Senior Design
with Medtronic plc
Touchless camera-based registration enhances surgical accuracy by reducing reliance on multiple 3D scans and minimizing patient contact. The project focuses on single-snapshot stereo methods using optical-target and geometry-based approaches.
Course DetailsCourse Offerings
MCEN 5228-005
Geometry and Learning-based Methods in Computer Vision
This is an advanced graduate course that deals with classical geometric and deep-learning methods in computer vision. The course begins with the mathematical foundations of computer vision and advances to recent deep-learning methods. It introduces formal perception tools for students interested in robot autonomy and 3D perception.
Course Details