There are a number of mathematics-related colloquia and seminar series on campus. Some can be taken for credit.

### Broad Audience Talks (open to the general public)

The **UW-PIMS Colloquium** is a quarterly series of talks sponsored by the UW Department of Mathematics and the Pacific Institute for the Mathematical Sciences.

The **Milliman Lectures** are an annual series of talks held by distinguished figures in the field of mathematics made possible through the Wendell Alfred Milliman Endowed Fund.

**MathAcrossCampus** is a quarterly colloquium series showcasing the application of mathematics and is currently supported by UW's College of Arts and Sciences and the Pacific Institute for the Mathematical Sciences.

### Research seminars

For specific information about receiving credit for any of these seminars, contact advising@math.washington.edu.

**Algebra and Algebraic Geometry Seminar** meets on Tuesdays at 2:30pm in PDL C-38. This seminar may be taken for credit as Math 510A. For specific information about receiving credit, contact Sándor Kovács.

**AWM Speaker Series** is a once per quarter event sponsored by the UW Association for Women in Mathematics chapter.

**Career Transition Series**** **are talks aimed at UW Math graduate students about some of the different phases of the process of transitioning from student to professional mathematician working in academia, industry or government.

**Combinatorics and Geometry Seminar** meets in Padelford C-401 on Wednesdays. The pre-seminar is from 3:30-4:00pm and the main seminar is from 4:10-5:00pm.

**Current Topics Seminar** will meet only in Autumn quarter on Thursdays from 4:30-5:30pm in PDL C-38.

**Differential Geometry/Partial Differential Equations (DG/PDE) Seminar** meets on Wednesdays at 4pm in PDL C-38 (unless otherwise noted). This seminar may be taken for credit as Math 550A. For specific information about receiving credit, contact Yu Yuan.

**Distinguished Seminar in Optimization & Data** meets Mondays at 3:30pm.

**Graduate Student Seminars** are a rotating series of student-led research seminar groups.

**Inverse Problems Seminar** Winter 2020 meets on Tuesdays from 4:00-5:00pm in PDL C-401.

**Number Theory Seminar** meets on Tuesdays from 11-11:50am in PDL C-401.

**Pacific Northwest Seminar on Topology, Algebra, and Geometry in Data Science (TAG-DS)** meets on Thursdays from 1-2pm.

**Postdoc Seminar** meets on Thursdays at 2pm in PDL C-38.

**Probability Seminar** meets in SMI 405 in Autumn Quarter 2024. This seminar may be taken for credit as Math 590. For specific information about receiving credit, contact advising@math.washington.edu.

**Rainwater Seminar** meets on Tuesdays at 1:30 in PDL C-401. This seminar may be taken for credit.

**Topology Seminar** meets most Thursdays 3:30-4:30pm in PDL C-401.

### Undergraduate research

**Washington Experimental Mathematics Lab (WXML)** is a group of mathematical explorers, with faculty, graduate students, undergraduates, and community members coming together for a journey of discovery. We showcase mathematics as a creative discipline, via experimental, computational, and especially visual mathematics.

### Other Research Activities

**Cascade Topology Seminar** is a semi-annual gathering of topologists from the Pacific Northwest and Southwestern Canada.

**Pacific Northwest Geometry Seminar (PNGS)** is a regional meeting for geometers of all kinds.

### Mathematical Centers

**Mathematical Sciences Research Institute (MSRI)** is one of the world’s preeminent centers for collaborative research. Researchers—some 2,000 per year—come to MSRI to work in an environment that promotes creativity and the effective interchange of ideas and techniques.

**Pacific Institute for the Mathematical Sciences (PIMS)** is a community of mathematical scientists in Alberta, British Columbia, Washington State, Saskatchewan and Manitoba. PIMS has built an international reputation for excellence and transformed the conditions of mathematical research in Canada.

**Machine Learning and Optimization Group at Microsoft Research** focuses on designing new algorithms to enable the next generation of AI systems and applications and on answering foundational questions in learning, optimization, algorithms, and mathematics.