Hi, I am
Abhraneel
Sarma.
I am a PhD candidate in Computer Science at Northwestern University, advised by Professor Matthew Kay and Professor Jessica Hullman.
I am interested in helping people make good data-driven decisions by developing tools and visualisations which allow them to make sense of all forms of uncertainty that arise during data analysis, which includes both easily quantifiable probabilistic forms of uncertainty as well as hard-to-quantify, non-probabilistic uncertainty.
My work involves both building systems—I developed (and actively maintain) multiverse, an R library which surfaces the sensitivity of the result of an analysis due to reasonable, but subjective choices made during the analysis; I have developed Milliways, an interactive visualisation system which allows analysts to perform a principled interpretation and validation of the results of multiverse analysis— and conducting rigorous empirical studies on how to best communicate uncertainty (beyond standard errors and probability estimates).
Selected Publications
See the full list of pubclications here
Odds and Insights: Decision Quality in Visual Analytics Under Uncertainty
CHI 2024 ●
BEST PAPER HONORABLE MENTION ●
PDF
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OSF
Milliways: Taming Multiverses through Principled Evaluation of Data Analysis Paths
CHI 2024 ●
PDF
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OSF
multiverse: Multiplexing Alternative Data Analyses in R Notebooks
CHI 2023 ●
BEST PAPER HONORABLE MENTION ●
PDF
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OSF
Evaluating the Use of Uncertainty Visualisations for Imputations of Data Missing At Random in Scatterplots
VIS 2022 ●
BEST PAPER HONORABLE MENTION ●
PDF
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OSF
Prior Setting In Practice: Strategies and rationales used in choosing prior distributions for Bayesian analysis
CHI 2020 ●
PDF ●
GITHUB
Increasing the transparency of research papers with Explorable Multiverse Analyses
CHI 2019 ●
BEST PAPER AWARD ●
PDF ●
GITHUB ●
OSF