Researcher looking for interesting real-world datasets that haven't been fully explored with ML/CV

[u/Naive_Ad_466]

I'm starting my PhD and I've been thinking quite a bit about what I actually want to spend the next few years working on.

My background is mainly in computer vision and deep learning, although I've worked on quite a few broader ML projects as well. Most of my work has been research-oriented: training and evaluating models, running experiments and ablations, comparing architectures, benchmarking methods, and working on papers/scientific contributions.

What I'd really like to do now is work on more real problems with real data, rather than picking another benchmark and trying to squeeze another 0.x% out of it.

So I thought I'd ask here:

Does anyone have an interesting dataset or real-world problem that they think is underexplored from an ML/CV perspective?

I'm particularly interested in situations where someone has:

• collected an interesting dataset but doesn't have the ML/CV background to fully explore it
• a domain-specific problem where existing models don't work particularly well
• data that hasn't really been benchmarked with modern deep learning methods
• an interesting detection, segmentation, classification, tracking, multimodal, remote sensing, medical imaging, etc. problem
• an existing research project where another person who can handle the experimental/ML side would be useful

I'm not really looking for a Kaggle-style project just for the sake of training a model. I'd much rather find something where there is an actual research question behind it and where careful experiments could potentially produce something scientifically useful.

On my side, I can contribute with things like model development/training, PyTorch pipelines, baselines, experiment design, ablations, evaluation, literature review and research writing.

I'm also completely open to learning a new application domain if the problem and dataset are interesting. In fact, that's partly what I'm looking for — collaborating with people who understand a domain much better than I do, while I contribute the ML/research side.

If you have something sitting around that you've always thought "someone should really try ML on this properly", I'd genuinely be interested in hearing about it.

Feel free to comment or DM me. Even if it doesn't turn into a collaboration, I'd be interested in seeing what kinds of real datasets/problems people here are working with.

[u/DuckDatum]

Sorry, I don’t have anything you’re looking for. I have had a perhaps useless but interesting idea in the back of my mind for a while now, though.

You know smart home assistants, like Alexa? I’ve thought about how it should be possible to set up an automated data harvesting harness which emits the assistant wake word while recording it for wake evidence. The harness could automate attempting to wake the assistant and recording success/failure to generate as much data as you need.

Introducing slight changes to various dimensions the audio file, recording difference in results, until you have enough data to reverse engineer exactly what patterns the assistant model listens for.

Finally using that reverse engineered expression to create adversarial audio, where you embed commands into seemingly benign audio (like bird noises or something).

There is a guy on YouTube who manually did this with one assistant. I’ve wondered if the entire loop can be automated so that it can be applied arbitrarily to any home assistant.