It means anyone can be a mentor on a topic of their expertise! Upon entering the Icebreaker link, you will be asked to indicate if you want to be a mentor or mentee. The Icebreaker platform will distribute mentors among groups as much as possible. There will be a series of mentoring sessions, both 1:1s and in small groups. Read more about the mentoring prompts below.

Who can mentor? Mentoring topics will range from general life-work balance to general research questions, thus we encourage a larger number of participants, ranging from mid-PhD to senior levels, to participate as mentors. Mentors can be of any gender.

It means anyone can be a mentor on a topic of their expertise! Upon entering the Icebreaker link, you will be asked to indicate if you want to be a mentor or mentee. The Icebreaker platform will distribute mentors among groups as much as possible. There will be a series of mentoring sessions, both 1:1s and in small groups. Read more about the mentoring prompts below.

Who can mentor? Mentoring topics will range from general life-work balance to general research questions, thus we encourage a larger number of participants, ranging from mid-PhD to senior levels, to participate as mentors. Mentors can be of any gender.

The panel, moderated by Sinead Williamson (University of Texas at Austin) with panelists Bin Yu (UC Berkeley), Tomi Mori (St. Jude Children’s Research Hospital), Po-Ling Loh (University of Cambridge), Jessica Kohlschmidt (Ohio State University), is on the topic of “Reviewing and Publishing”. The rapid growth of the machine learning and statistics community has made the reviewing process of peer-reviewed conferences more challenging. Besides sharing their experiences, panelists will discuss publishing venues in ML and Statistics, as well as take questions from the audience. Read more about the panelists below.