We will be hosting a "virtual ISNET" meeting this December. This is not a replacement for the full meeting we still plan on hosting at MSU in 2021. Instead, the purpose is to maintain ISNET's mission of bringing the nuclear physics as statistical sciences communities together to report on the latest progress and to provide a vehicle for educating and enlightening the nuclear physics community in regards to the application of statistical methodologies that enable nuclear physics to reach more quantitatively rigorous scientific conclusions.
The dates of the virtual meeting are Monday, December 14th - Thursday, December 17th 2020.
For the first day (Monday, the 14th) the BAND Collaboration will host a series of pedagogical lectures, aimed at students and postdocs. These lectures will introduce nuclear physicists to the fundamentals and approaches of statistical science, and provide statisticians a picture of the challenges facing nuclear science that would benefit from more sophisticated statistical analysis. This might also include lectures on computational approaches, e.g. machine learning, that will play a role in these analyses.
The last three days, Tuesday the 15th through Thursday 17th, we plan to host three 45+ minute lectures each day. In addition to the lectures, a student discussion period will be scheduled each day based on topics covered in the day's lectures.
A few ideas for lectures are:
1. Bayesian Basics
2. Model Emulation
3. Model Mixing
4. ML techniques for statistical analysis
5. Advanced Statistics Techniques for Analyzing Experimental Data
6. Resampling Techniques (e.g. bootstrap)
Please contact us should you have any questions or ideas at firstname.lastname@example.org