Collaborative Research: Conference: Prairie Analysis Seminar 2026-2027
- Institution
- Kansas State University, KS
- Principal investigator
- Virginia M Naibo
- Funding
- $25K
- Duration
- 2026–2028
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Abstract
This award supports participation in the 2026 and 2027 editions of the Prairie Analysis Seminar to be held at University of Kansas and Kansas State University, respectively. Established in 2001, the Prairie Analysis Seminar is a long-running joint initiative of the mathematics departments at Kansas State University and the University of Kansas. The seminar brings together researchers working in analysis and partial differential equations to exchange ideas, present recent advances, and foster new collaborations. A central objective of the program is to support the professional development of graduate students, postdoctoral researchers, and other early-career mathematicians by providing opportunities to present their research, interact closely with established experts, and build professional connections. The seminar also seeks to broaden participation in the mathematical sciences by encouraging attendance from researchers at smaller colleges and universities. Each edition features internationally recognized researchers whose work has significantly influenced contemporary developments in analysis and partial differential equations. The program consists of a series of invited lectures, including a principal lecturer who delivers two one-hour presentations and two additional invited speakers who each present a one-hour lecture. Complementing these invited talks are contributed presentations by graduate students, postdoctoral scholars, and other early-career participants, as well as a collaborative session devoted to the discussion of open research problems proposed by attendees. Additional information about the Prairie Analysis Seminar is available at the conference website: https://www.math.ksu.edu/about/events/conference/pas/ This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Research team
- Virginia M NaiboPI
- Diego M Maldonado
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