Hi! I'm Aspen.

I'm a PhD student in the MIT Visualization Group. I'm interested in machine learning, data vis + HCI, femme in STEM, and how tech impacts the human experience. Check out my random ramblings here.

research

* * * responsible ml * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *

ml practices outside big tech

Support for the democratization of machine learning is growing rapidly, but responsible ML development outside Big Tech is poorly understood. As more organizations turn to ML, what challenges do they face in creating fair and ethical ML?

We explore these challenges, highlighting future research directions for the ML community in our AIES 2021 paper!

designing data for ML

The ML pipeline includes data collection and iteration. But what data should you collect, how should you collect it, and how do you evaluate it after training? We're exploring this in an ongoing project! Soon to be submitted~

socializing data

Labeled datasets are historically treated as authoritative sources of ground truth. But how is that ground truth determined, and how can we build historical contexts for these systems? This project focuses on collaborative sensemaking and label provenance. Soon to be submitted!

* * * visualizations * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *

misleading visualizations

Misinformation comes in many forms--including in charts and graphs. So we built a spell-check equivalent for visualizations! We hope that by pointing out ineffectiveness in visualizations, we can ensure best practices in design and increase data literacy. Just as importantly, we can encourage accuracy and critique in public domains.

So what is the red wavy line analogue for graphs? Read more in our EuroVis 2020 paper here!

visualizations for the public

Air quality, like many environmental and health considerations, is important to communicate to the public.

But how do you effectively communicate important information to lay readers, particularly in context of uncertainty and statistical model outputs? We discuss challenges here, and design considerations here.

See the outcome and explore air quality here.

teaching

data crafting

While the value of play is scientifically grounded, the benefits of play in the context of data are underexplored. Our workshop encouraged novices to explore data and 'made new' mundane notions for experienced practitioners by utilizing crafting materials and techniques.

wanna chat?

Aspen

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