Math Dept 2022-2023 Newsletter 5
Monday, 7 November 2022
Past newsletters can now be reached via the department website.
[Click on “About” and then “News and Events”].
Newsletter is sent out when there is something new.
Please send entries by the end of the workweek–Ed.
---------------------------------------------------------------------------------------------
MEETINGS AND SEMINARS IN THE DEPARTMENT
TUESDAYS
Statistics Seminar
Tuesdays 2pm, on zoom.
Contact coordinator Saraleesan Nadarajah for zoom link.
----------------------------------------------------------------------------
Combinatorics Seminar
TBA
Contact coordinator Lou Shapiro for zoom link.
WEDNESDAYS
Graduate Student Seminar
1pm, wednesday.
Contact Shakuan Frankson for more information.
------------------------------------------------------------------
Applied Math Reading Seminar
TBA
Students will get to practice studying papers and working on research problems.
Please write the coordinator for original handouts or for the recording link.
Contact coordinator for zoom link as well.
Coordinator: Katie Gurski, Yeona Kang
-----------------------------------------------------------
Math team/Math Club meetings
Organizer: Jill McGowan
-----------------------------------------------------------
THURSDAYS
Seminar on Topological Semigroups
The seminar will include applications to Ramsey theory.
11 am on zoom on Thursdays.
Dr. Dilip Raghavan of the National University of Singapore has been speaking on “Stable ordered union versus selective ultrafilters.”
Contact coordinator for zoom invite.
Coordinator Dennis Davenport
---------------------------------------------------------------
FRIDAYS
Mathematics Department Colloquium
Fridays, 4.10 to 5pm.
Friday, 18 November
Stephen McKeown, University of Texas, Dallas.
Title TBA.
On Friday, 4 November, Fang-Ting Tu of Louisiana State University talked about Hypergeometric Functions over Finite Fields.
TALKS AND WORKSHOPS OUTSIDE DEPARTMENT
1. Clifton-Bailey Statistics Seminar Series (GMU)
On Friday, Nov 11, Zhigang Yao of the National University of Singapore will speak on “Principal Fkow, Sub-Manifold and Boundary.”
For more information contact Saralees Nadarajah.
ANNOUNCEMENTS
1. Math Department in the news for groundbreaking College Algebra program
Our department is expanding a College Algebra course developed with Khan Academy to historically underserved schools nationwide, as reported in this news release.
SCHOLARSHIP AND FELLOWSHIP OPPORTUNITIES
(from various sources)
1. Michigan Program in Survey and Data Science (MPSDS)
MPSDS is a graduate program in University of Michigan. They will have an information session on Nov 10.
https://surveydatascience.isr.umich.edu/mpsds-informational-session-webinar
2. US Dept of Energy (DOE) Scholars Program
Opportunity to exlplore federal career with DOE. Recently graduated undergrads and grad students are eligible to apply. Program will provide stipends and travel funds.
Applications due by January 23, 2023.
https://orise.orau.gov/doescholars/
3. USC summer program (thanks to Dennis Davenport)
The University of Southern California has a summer program titled LA's best, from June 20 to July 28, 2023. Applications are invited from US citizens in STEM programs to do research in quantitative methods for health issues and are due by February 3rd.
4. Help school students learn coding and gain work experience
Help students from K to 8 in schools in the DC area learn coding, robotics and other STEM topics and get them excited about programming and learn CS fundamentals.
Competitive pay, training and supplies provided. Must be vaccinated and US citizens.
If interested write to hr at codeadvantage.org.
In previous newsletters:
Mickey Leland Energy Fellowship
Dept of Homeland Security (DHS) Educational Programs
U.Mass graduate program in energy transition and sustainibility
INTERESTING ARTICLES AND WEBSITES
1. How artificial intelligence helps in astrophysics, ocean exploration and earthquake monitoring
In Caltech Exchange experts in these fields describe the use of machine learning when big data sets are involved. For example, the Rubin Observatory's survey of space and time has 40 billion objects. Even if statistically, you find an interesting object once in a million searches, this data set will contain 40,000 of those. By training AI programs to look for specific patterns, we can find these faster and more effectively. Previously such work was done by undergrads and grad students.