VLDB 2026 Research / reviewers in the wild / expert
Arnav Verma
dblp:344/8887
· DBLP profile ↗
6ranked-venue papers
3as first author
6since 2021 · last 2025
0000-0002-4018-9296ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 5 · 2 first-author · 5 since 2021Applied, interdisciplinary, general and emerging computing · 5 · 2 first-author · 5 since 2021Human-computer interaction and ubiquitous computing · 1 · 1 first-author · 1 since 2021
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Minds in the Making: Cognitive Science and Design Thinking
Junyi Chu, Arnav Verma, Guy Davidson, Robbie Fraser, Judith E. Fan |
CogSci | 2 |
| 2025 | Measuring and predicting variation in the difficulty of questions about data visualizations
Arnav Verma, Judith E. Fan |
CogSci | 1 |
| 2025 | Investigating children's performance on object- and picture-based vocabulary assessments in global contexts: Evidence from Kisumu, Kenya
Rebecca Zhu, Tabitha Nduku, Joab Ochieng Arieda, Arnav Verma, Judith E. Fan, Michael C. Frank |
CogSci | 4 |
| 2024 | COGGRAPH: Building bridges between cognitive science and computer graphics
Kartik Chandra, Anne H. K. Harrington, Katie Collins, Christopher J. Kymn, Kushin Mukherjee, Sean P. Anderson, Arnav Verma, Judith E. Fan |
CogSci | 7 |
| 2024 | Evaluating human and machine understanding of data visualizations
Arnav Verma, Kushin Mukherjee, Christopher Potts, Elisa Kreiss, Judith E. Fan |
CogSci | 1 |
| 2023 | Designing Resource Allocation Tools to Promote Fair Allocation: Do Visualization and Information Framing Matter?abstractStudies on human decision-making focused on humanitarian aid have found that cognitive biases can hinder the fair allocation of resources. However, few HCI and Information Visualization studies have explored ways to overcome those cognitive biases. This work investigates whether the design of interactive resource allocation tools can help to promote allocation fairness. We specifically study the effect of presentation format (using text or visualization) and a specific framing strategy (showing resources allocated to groups or individuals). In our three crowdsourced experiments, we provided different tool designs to split money between two fictional programs that benefit two distinct communities. Our main finding indicates that individual-framed visualizations and text may be able to curb unfair allocations caused by group-framed designs. This work opens new perspectives that can motivate research on how interactive tools and visualizations can be engineered to combat cognitive biases that lead to inequitable decisions. Arnav Verma, Luiz Augusto de Macêdo Morais, Pierre Dragicevic, Fanny Chevalier |
CHI | 1 |