Department faculty is engaged in active research and is committed to involving undergraduates in their work.
Who leads research projects? Who can be apart of these projects?
All students are encouraged to engage in research. Students may begin research projects as early as freshmen year. The research projects are lead by Ursinus faculty and often faculty from surround institutions. Visit the faculty page to see published articles by Ursinus faculty and students.
How does research count for credit?
Research can be carried out for 1 credit (3 hours/week), 2 credits (6 hours/week) or 4 credits (12 hours/week). A 4 credit research fulfills the requirement for an independent learning experience.
Where will I complete research?
Research may be completed in the department Mac lab. However, most research is done throughout campus in various meeting rooms.
When can I participate in research projects?
Students may complete research in the Fall and Spring semesters. Students also have the opportunity to stay over the summer and work on research projects. This program is a competitive program called Summer Fellows.
When and where my research be presented?
Each year, many student researchers present their work at the Ursinus College Annual Celebration of Student Achievement Day, as well as at regional, national, and international science meetings. Students publish their research in undergraduate research journals on a regular basis and have the opportunity to publish with faculty in professional scientific journals.
What types of research are students engaged in?
Research opportunities are available in various disciplines within the department.Topics of research are listed below.
- Vertex operator algebras
- Kac-Moody Lie algebras
- Relations to q-series, partitions, combinatorics, and number theory
- Luternik-Schnirelmann category
- Discrete Morse Theory
- Applied Math to System Biology
- Wireless Sensor Networks
- Social Networks
- Sematic Web
- App Development
- Data Mining
- Detection and prevention of Cyberbullying and Internet Predation
- Machine Learning
- Information Retrieval
- Statistical Genetics
- Computational molecular evolution
- Games of chance
- Statistics education