Notes and report-out pics can be found here
- What is happening regarding diversity/inclusion in your lab or institution?
- What can you do to contribute?
- Why is this important and what are the benefits?
- How are you using machine learning in your research?
- What tools/methods do you use? How are they useful for others?
- How do you visualize your data? What tools do you like?
- What tools are available and how is accessibility for the non-expert?
- What have been your experiences thus far looking in academic and non-academic sectors?
- If you have recently accepted a position, what did the process look like?
- What alternative metrics are you aware of?
- What do you want credit for that you aren’t getting?
- How do incentives work for or against you re. tenure/promotion/jobs?
- What is the balance between reusing existing and collecting new data?
- How do you share your data/code?
- What are your experiences with licensing and sharing data?
- What have been your experiences and lessons learned?
- What resources are most useful for training?
- Best practices for interacting with different audiences?