World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
38
Citations
5687
World Ranking
10294
National Ranking
4318

Overview

Remco Chang is affiliated with Tufts University in the United States and specializes in computer science, with a focus on computer vision and pattern recognition, artificial intelligence, information systems and management, sociology and political science, and signal processing.

Their main research topics encompass data visualization and analytics, multimedia communication and technology, scientific computing and data management, image and video quality assessment, data management and algorithms, data analysis with R, and computer graphics and visualization techniques.

Remco Chang has published extensively, with recent notable papers including:

  • Composition and Configuration Patterns in Multiple-View Visualizations (2020), IEEE Transactions on Visualization and Computer Graphics
  • Survey on the Analysis of User Interactions and Visualization Provenance (2020), Computer Graphics Forum
  • CAVA: A Visual Analytics System for Exploratory Columnar Data Augmentation Using Knowledge Graphs (2020), IEEE Transactions on Visualization and Computer Graphics
  • Knowledge Graphs in Practice: Characterizing their Users, Challenges, and Visualization Opportunities (2023), IEEE Transactions on Visualization and Computer Graphics
  • The gamification of nutrition labels to encourage healthier food selection in online grocery shopping: A randomized controlled trial (2023), Appetite

Their frequent co-authors include Gabriel Appleby, Ashley Suh, Dylan Cashman, Michael Gleicher, and Alex Endert.

Remco Chang has contributed to a range of publication venues, primarily:

  • arXiv (Cornell University)
  • IEEE Transactions on Visualization and Computer Graphics
  • IEEE Computer Graphics and Applications
  • Computer Graphics Forum
  • Current Developments in Nutrition

Their academic contributions also include book publications, notably a work published by Springer Science+Business Media titled Advances in Visual Computing from 2022.

Best Publications

  • Dis-function: Learning distance functions interactively

    Eli T. Brown;Jingjing Liu;Carla E. Brodley;Remco Chang

  • The science of interaction

    William A. Pike;John Stasko;Remco Chang;Theresa A. O'Connell

  • iPCA: an interactive system for PCA-based visual analytics

    Dong Hyun Jeong;Caroline Ziemkiewicz;Brian Fisher;William Ribarsky

  • Ranking visualizations of correlation using Weber's law

    Lane Harrison;Fumeng Yang;Steven Franconeri;Remco Chang

  • Defining Insight for Visual Analytics

    R. Chang;C. Ziemkiewicz;T.M. Green;W. Ribarsky

  • Dynamic Prefetching of Data Tiles for Interactive Visualization

    Leilani Battle;Remco Chang;Michael Stonebraker

  • Infographic Aesthetics: Designing for the First Impression

    Lane Harrison;Katharina Reinecke;Remco Chang

  • Dynamic difficulty using brain metrics of workload

    Daniel Afergan;Evan M. Peck;Erin T. Solovey;Andrew Jenkins

  • WireVis: Visualization of Categorical, Time-Varying Data From Financial Transactions

    R. Chang;M. Ghoniem;R. Kosara;W. Ribarsky

  • Finding Waldo: Learning about Users from their Interactions

    Eli T Brown;Alvitta Ottley;Helen Zhao;Quan Lin

  • Recovering Reasoning Processes from User Interactions

    Wenwen Dou;Dong Hyun Jeong;F. Stukes;W. Ribarsky

  • ParallelTopics: A probabilistic approach to exploring document collections

    Wenwen Dou;Xiaoyu Wang;Remco Chang;William Ribarsky

  • Learn Piano with BACh: An Adaptive Learning Interface that Adjusts Task Difficulty Based on Brain State

    Beste F. Yuksel;Kurt B. Oleson;Lane Harrison;Evan M. Peck

  • Using fNIRS brain sensing to evaluate information visualization interfaces

    Evan M M. Peck;Beste F. Yuksel;Alvitta Ottley;Robert J.K. Jacob

  • Analytic provenance: process+interaction+insight

    Chris North;Remco Chang;Alex Endert;Wenwen Dou

  • Improving Bayesian Reasoning: The Effects of Phrasing, Visualization, and Spatial Ability

    Alvitta Ottley;Evan M. Peck;Lane T. Harrison;Daniel Afergan

  • Composition and Configuration Patterns in Multiple-View Visualizations

    Xi Chen;Wei Zeng;Yanna Lin;Hayder Mahdi AI-maneea

  • Beagle: Automated Extraction and Interpretation of Visualizations from the Web

    Leilani Battle;Peitong Duan;Zachery Miranda;Dana Mukusheva

  • Dynamic reduction of query result sets for interactive visualizaton

    Leilani Battle;Michael Stonebraker;Remco Chang

  • Survey on the Analysis of User Interactions and Visualization Provenance

    Kai Xu;Alvitta Ottley;Conny Walchshofer;Marc Streit

  • Interactive Coordinated Multiple-View Visualization of Biomechanical Motion Data

    D. Keefe;M. Ewert;W. Ribarsky;R. Chang

  • Legible Cities: Focus-Dependent Multi-Resolution Visualization of Urban Relationships

    Remco Chang;G. Wessel;R. Kosara;E. Sauda

Frequent Co-Authors

William Ribarsky
William Ribarsky University of North Carolina at Charlotte
Alex Endert
Alex Endert Georgia Institute of Technology
Eugene Wu
Eugene Wu Columbia University
Robert J. K. Jacob
Robert J. K. Jacob Tufts University
Carlos Scheidegger
Carlos Scheidegger University of Arizona
Michael Gleicher
Michael Gleicher University of Wisconsin–Madison
John Stasko
John Stasko Georgia Institute of Technology
Steven Franconeri
Steven Franconeri Northwestern University
Alice H. Lichtenstein
Alice H. Lichtenstein Tufts University

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