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researcher

Sheng Long

Northwestern University

4 papers hereh-index 240 citations8 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author3
  • middle author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.HC4
affiliations
  • Northwestern University
ORCID 0009-0000-9752-5898
same name
  • Sheng Long — 6 papers, h 7
  • Sheng Long — 4 papers, h 2
  • Sheng Long — 1 paper, h 5
  • Sheng Long — 1 paper, h 2
  • Sheng Long — 1 paper, h 2
  • Sheng Long — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

collaborators

4 papers

cs.HC2026

Should We Dangle a Carrot? The Effect of Performance-based Incentives in Visualization Experiments

Abhraneel Sarma, Matthew Kay, Sheng Long +2

A perennial research question in visualization involves identifying which visual encodings for a particular dataset are most effective for users in performing a specific task. The…

cs.HC2026

Visual Decoding Operators: Towards a Compositional Theory of Visualization Perception

Sheng Long, Remco Chang, Eugene Wu +2

Prior work on perceptual effectiveness has decomposed visualizations into smaller common units (e.g., channels such as angle, position, and length) to establish rankings. While use…

cs.HC2026

LoopLens: Supporting Search as Creation in Loop-Based Music Composition

Sheng Long, Atsuya Kobayashi, Kei Tateno

Creativity support tools (CSTs) typically frame search as information retrieval, yet in practices like electronic dance music production, search serves as a creative medium for col…

cs.HC2025

Seeing Eye to AI? Applying Deep-Feature-Based Similarity Metrics to Information Visualization

Sheng Long, Angelos Chatzimparmpas, Emma Alexander +2

Judging the similarity of visualizations is crucial to various applications, such as visualization-based search and visualization recommendation systems. Recent studies show deep-f…

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