Pro Bono Work for Research Teams

Here at Hop, we’re big believers in the potential for machine learning to have a positive impact on humanity. The creativity and energy across the machine learning research community is extraordinary.

Here are some machine learning projects that inspire us:

For these (and other) research teams working on important problems, we want to support them in doing their best work. If you’re trying to improve the standard of care for a complex medical condition, or sifting through mountains of environmental data, or even if you’re just making an important point about the state of facial recognition — you deserve access to the best tools!

To this end, Hop will donate time towards helping your research team set up the infrastructure and tooling necessary to accelerate your insights. These contributions get us all closer to our shared goal of robust and reproducible research, but are easy to skip in the rush to get a paper or a demo out. Some examples of things we’d love to set up for your team are:

• test harnesses and reporting, so that it’s easy to refactor your code and verify your results

• CI / CD pipelines to ensure that last-minute changes don’t invalidate prior results

• experiment frameworks that enable you to scale up your experiments and explore hyperparameters while managing cost

• visualization stacks to make your results or your models (or both) interpretable

• standardized experiment patterns, so that your code is not littered with conditionals that can be hard to reason about

• whatever else you need that is useful

If you’re interested in the above, and you’re part of a non-commercial research team, reach out to us at mlforgood@hoplabs.com. We’re able to work with one team a month — please apply for our next available slot.

Can’t wait to see what results you come up with!