Hi, I am

Abhraneel
Sarma.

I am a PhD student in Computer Science at Northwestern University, advised by Professor Jessica Hullman. Previously, I have worked as a researcher at the University of Michigan School of Information, advised by Professor Matthew Kay.

Broadly—I am interested in studying how people make sense of uncertainty information which arise in a typical data analysis pipeline. Specifically—I have developed tools which help analysts to surface the uncertainty in their data analysis process itself (the multiverse R library), or studying how users interpret uncertainty visualisations in missing data contexts or multiple comparison scenarios.

CV

Publications

Evaluating the Use of Uncertainty Visualisations for Imputations of Data Missing At Random in Scatterplots
Abhraneel Sarma, Shunan Guo, Jane Hoffswell, Ryan Rossi, Fan Du, Eunyee Koh and Matthew Kay
VIS 2022 ● BEST PAPER HONORABLE MENTIONPDFOSF

Prior Setting In Practice: Strategies and rationales used in choosing prior distributions for Bayesian analysis
Abhraneel Sarma and Matthew Kay
CHI 2020 ● PDFGITHUB

Increasing the transparency of research papers with Explorable Multiverse Analyses
Pierre Dragicevic, Yvonne Jansen, Abhraneel Sarma, Matthew Kay, and Fanny Chevalier
CHI 2019 ● BEST PAPER AWARDPDFGITHUB

Projects

The Effect of Explanatory Narratives and Exploratory Interactivity on learning through recall
Abhraneel Sarma and Matthew Kay
Master's Thesis Project ● 2018

Visualizing Inter-generational Wealth Mobility and Racial Inequality
Involved in developing the visualization (D3.js and reGL) and exploratory statistical modelling of the data.

Courses

I've been involved in organising the following courses as an instructor:

Transparent Practices for Quantitative Empirical Research
Chat Wacharamanotham, Fumeng Yang, Xiaoying Pu, Abhraneel Sarma and Lace Padilla
ACM Human Factors in Computing Systems (CHI) 2022