The field of Geometric Algorithms studies the design, analysis, and implementation of algorithms and data structures for geometric problems. These problems arise in a wide range of areas, including robotics, computer graphics, molecular biology, GIS, spatial databases, sensor networks, and machine learning. In addition to the tools developed in computer science, the study of geometric algorithms also requires ideas from various mathematical disciplines, including combinatorics, topology, and algebra.
The goal of this course is to provide an overview of the techniques developed in geometric algorithms as well as some of its application areas. The topics covered in the course will include:
The main textbook for this course: M. de Berg, O. Cheong, M. van Kreveld, and M. Overmars, Computational Geometry: Algorithms and Applications. Springer-Verlag, 3rd ed., 2008.
Assignments: 40% weight
Four assignments will be given during the semester, which each student has to complete individually without searching the material online.
Lecture Scribe: 10% weight
Each student will scribe one lecture.
Research Project: 50% weight
Intended to produce a work of publishable quality, the project should consist of a comprehensive survey on a topic plus new research work. Due on April 20, 2022.
Accessed here. This works as the hub to Gradescope and Ed. Any course resources (e.g. lecture notes, solutions) will be hosted on Sakai under Resources.
Accessed via Sakai. All assignments and project documents will be submitted here. See Assignments for more info.
Accessed via Sakai. Ed is a questions-and-answers message board (similar to Piazza) that is easy to use and allows for all participants to help answer each other's questions. Please ask all course-related questions on Ed by creating a new post, not only those about assignments.