The REU is a six-week summer program offered by the Geometry and Topology group at
UCLA and is funded by a NSF Research and Training Grant (RTG).
Topic
The research topic will be Topological Data Analysis (TDA). This program provides students with the
opportunity to immerse themselves in active research projects in TDA, an important branch of applied topology,
under the mentorship of senior and junior researchers in the field. During the final week of the program,
students will showcase the results of their research through a written report and an oral presentation. During
the project, students will also be asked to write code. The mentors will outline the expected outcomes at the
beginning of the summer and will work closely with the students to ensure the successful completion of the final
project. In addition to hands-on research, the REU will feature informative sessions run by the mentors and
other researchers on career-development topics, such as how to do research in mathematics, career prospects in
mathematics, preparing for graduate school, and writing graduate-school applications.
Date and Location
The program dates are 12 August through 20 September. The expected workload is 40hr/week for 6 weeks. The REU
program will be conducted in a hybrid format, requiring participants to be physically present in Los Angeles and
available during business hours (10 AM - 5 PM) to fully participate. Some weekdays will use a remote format
with Zoom.
Funding
Each student will be provided a $5000 stipend for 6 weeks of REU at the end of the program. No additional
funding is available for lodging or transportation. Because the students are supposed to be local, they are
expected to commute to campus.
Mentors
The REU mentors are Troy Kling (PhD student, UCSB), Sarah Tymochko (Hedrick Assistant Adjunct Professor, UCLA),
and Sidhanth Raman (PhD student, UCI). The program will be overseen by Mason Porter (Professor, UCLA).
Schedule
The tentative schedule is as follows:
- Week 1-2: Introduction to algebraic topology, topological data analysis, and persistent homology (including
use of TDA software with Python)
- Week 3-4: Analysis of a data set using persistent homology
- Week 5: Finalizing the analysis and conclusions
- Week 6: Present the results in both a written report and an oral presentation