Visualizing virus population variability from next generation sequencing data. - Michael Correll; Subhadip Ghosh; David H. O'Connor; Michael Gleicher (BioVis, 2011)

Exploring Collections of Tagged Text for Literary Scholarship. - Michael Correll; Michael Witmore; Michael Gleicher (Comput. Graph. Forum, 2011)

Comparing averages in time series data. - Michael Correll; Danielle Albers; Steven Franconeri; Michael Gleicher (CHI, 2012)

Quantity estimation in visualizations of tagged text. - Michael Correll; Eric C. Alexander; Michael Gleicher (CHI, 2013)

Perception of Average Value in Multiclass Scatterplots. - Michael Gleicher; Michael Correll; Christine Nothelfer; Steven Franconeri (IEEE Trans. Vis. Comput. Graph., 2013)

Navigating reductionism and holism in evaluation. - Michael Correll; Eric C. Alexander; Danielle Albers; Alper Sarikaya 001; Michael Gleicher (BELIV, 2014)

Task-driven evaluation of aggregation in time series visualization. - Danielle Albers; Michael Correll; Michael Gleicher (CHI, 2014)

Error Bars Considered Harmful: Exploring Alternate Encodings for Mean and Error. - Michael Correll; Michael Gleicher (IEEE Trans. Vis. Comput. Graph., 2014)

LayerCake: a tool for the visual comparison of viral deep sequencing data. - Michael Correll; Adam L. Bailey; Alper Sarikaya 001; David H. O'Connor; Michael Gleicher (Bioinform., 2015)

The semantics of sketch: Flexibility in visual query systems for time series data. - Michael Correll; Michael Gleicher (VAST, 2016)

Regression by Eye: Estimating Trends in Bivariate Visualizations. - Michael Correll; Jeffrey Heer (CHI, 2017)

Designing for Uncertainty in HCI: When Does Uncertainty Help? - Miriam Greis; Jessica Hullman; Michael Correll; Matthew Kay 001; Orit Shaer (CHI Extended Abstracts, 2017)

Surprise! Bayesian Weighting for De-Biasing Thematic Maps. - Michael Correll; Jeffrey Heer (IEEE Trans. Vis. Comput. Graph., 2017)

Ross-Chernoff Glyphs Or: How Do We Kill Bad Ideas in Visualization? - Michael Correll (CHI Extended Abstracts, 2018)

Value-Suppressing Uncertainty Palettes. - Michael Correll; Dominik Moritz; Jeffrey Heer (CHI, 2018)

Ethical Dimensions of Visualization Research. - Michael Correll (CHI, 2019)

Designing Animated Transitions to Convey Aggregate Operations. - Younghoon Kim; Michael Correll; Jeffrey Heer (Comput. Graph. Forum, 2019)

Looks Good To Me: Visualizations As Sanity Checks. - Michael Correll; Mingwei Li; Gordon L. Kindlmann; Carlos Scheidegger (IEEE Trans. Vis. Comput. Graph., 2019)

In Pursuit of Error: A Survey of Uncertainty Visualization Evaluation. - Jessica Hullman; Xiaoli Qiao; Michael Correll; Alex Kale; Matthew Kay 001 (IEEE Trans. Vis. Comput. Graph., 2019)

What Do We Talk About When We Talk About Dashboards? - Alper Sarikaya 001; Michael Correll; Lyn Bartram; Melanie Tory; Danyel Fisher (IEEE Trans. Vis. Comput. Graph., 2019)

What Do We Actually Learn from Evaluations in the "Heroic Era" of Visualization? : Position Paper. - Michael Correll (BELIV, 2020)

Truncating the Y-Axis: Threat or Menace? - Michael Correll; Enrico Bertini; Steven Franconeri (CHI, 2020)

Divining Insights: Visual Analytics Through Cartomancy. - Andrew M. McNutt; Anamaria Crisan; Michael Correll (CHI Extended Abstracts, 2020)

Surfacing Visualization Mirages. - Andrew M. McNutt; Gordon L. Kindlmann; Michael Correll (CHI, 2020)

Why Shouldn't All Charts Be Scatter Plots? Beyond Precision-Driven Visualizations. - Enrico Bertini; Michael Correll; Steven Franconeri (IEEE VIS (Short Papers), 2020)

VisuaLint: Sketchy In Situ Annotations of Chart Construction Errors. - Aspen K. Hopkins; Michael Correll; Arvind Satyanarayan (Comput. Graph. Forum, 2020)

What Do We Actually Learn from Evaluations in the "Heroic Era" of Visualization? - Michael Correll (CoRR, 2020)

Improving the Robustness of Scagnostics. - Yunhai Wang; Zeyu Wang 005; Tingting Liu; Michael Correll; Zhanglin Cheng; Oliver Deussen; Michael Sedlmair (IEEE Trans. Vis. Comput. Graph., 2020)

User Ex Machina : Simulation as a Design Probe in Human-in-the-Loop Text Analytics. - Anamaria Crisan; Michael Correll (CHI, 2021)

Data-Driven Mark Orientation for Trend Estimation in Scatterplots. - Tingting Liu; Xiaotong Li; Chen Bao; Michael Correll; Changhe Tu; Oliver Deussen; Yunhai Wang (CHI, 2021)

Vis Ex Machina: An Analysis of Trust in Human versus Algorithmically Generated Visualization Recommendations. - Rachael Zehrung; Astha Singhal; Michael Correll; Leilani Battle (CHI, 2021)

Illegible Semantics: Exploring the Design Space of Metal Logos. - Gerrit J. Rijken; René Cutura; Frank Heyen; Michael Sedlmair; Michael Correll; Jason Dykes; Noeska N. Smit (CoRR, 2021)

Towards a Theory of Bullshit Visualization. - Michael Correll (CoRR, 2021)

Position Paper: Are We Making Progress In Visualization Research? - Michael Correll (BELIV, 2022)

Recommendations for Visualization Recommendations: Exploring Preferences and Priorities in Public Health. - Calvin S. Bao; Siyao Li; Sarah G. Flores; Michael Correll; Leilani Battle (CHI, 2022)

Oscar: A Semantic-based Data Binning Approach. - Vidya Setlur; Michael Correll; Sarah Battersby (IEEE VIS (Short Papers), 2022)

Are We Making Progress In Visualization Research? - Michael Correll (CoRR, 2022)

Untidy Data: The Unreasonable Effectiveness of Tables. - Lyn Bartram; Michael Correll; Melanie Tory (IEEE Trans. Vis. Comput. Graph., 2022)

Troubling Collaboration: Matters of Care for Visualization Design Study. - Derya Akbaba; Devin Lange; Michael Correll; Alexander Lex; Miriah Meyer (CHI, 2023)

Teru Teru Bōzu: Defensive Raincloud Plots. - Michael Correll (CoRR, 2023)

Toward a Scalable Census of Dashboard Designs in the Wild: A Case Study with Tableau Public. - Joanna Purich; Arjun Srinivasan; Michael Correll; Leilani Battle; Vidya Setlur; Anamaria Crisan (CoRR, 2023)

Teru Teru Bōzu: Defensive Raincloud Plots. - Michael Correll (Comput. Graph. Forum, 2023)

Fitting Bell Curves to Data Distributions Using Visualization. - Eric Newburger; Michael Correll; Niklas Elmqvist (IEEE Trans. Vis. Comput. Graph., 2023)

Tasks and Telephones: Threats to Experimental Validity due to Misunderstandings of Visualisation Tasks and Strategies Position Paper. - Abhraneel Sarma; Sheng Long; Michael Correll; Matthew Kay 001 (BELIV, 2024)

Complexity as Design Material Position Paper. - Florian Windhager; Alfie Abdul-Rahman; Mark-Jan Bludau; Nicole Hengesbach; Houda Lamqaddam; Isabel Meirelles; Bettina Speckmann; Michael Correll (BELIV, 2024)

When the Body Became Data: Historical Data Cultures and Anatomical Illustration. - Michael Correll; Laura A. Garrison (CHI, 2024)

Toward a More Comprehensive Understanding of Visualization Literacy. - Lily W. Ge; Maryam Hedayati; Yuan Cui; Yiren Ding; Karen Bonilla; Alark Joshi; Alvitta Ottley; Benjamin Bach; Bum Chul Kwon; David N. Rapp; Evan M. Peck; Lace M. K. Padilla; et al. (CHI Extended Abstracts, 2024)

Odds and Insights: Decision Quality in Exploratory Data Analysis Under Uncertainty. - Abhraneel Sarma; Xiaoying Pu; Yuan Cui; Michael Correll; Eli T. Brown; Matthew Kay 001 (CHI, 2024)

The Data-Wink Ratio: Emoji Encoder for Generating Semantically-Resonant Unit Charts. - Matthew Brehmer; Vidya Setlur; Zoe; Michael Correll (GEN4DS@VIS, 2024)

Data Guards: Challenges and Solutions for Fostering Trust in Data. - Nicole Sultanum; Dennis Bromley; Michael Correll (IEEE VIS, 2024)

Complexity as Design Material. - Florian Windhager; Alfie Abdul-Rahman; Mark-Jan Bludau; Nicole Hengesbach; Houda Lamqaddam; Isabel Meirelles; Bettina Speckmann; Michael Correll (CoRR, 2024)

Heuristics for Supporting Cooperative Dashboard Design. - Vidya Setlur; Michael Correll; Arvind Satyanarayan; Melanie Tory (IEEE Trans. Vis. Comput. Graph., 2024)

The Many Tendrils of the Octopus Map. - Eduardo Puerta; Shani Claire Spivak; Michael Correll (CHI, 2025)

From Dashboard Zoo to Census: A Case Study With Tableau Public. - Arjun Srinivasan; Joanna Purich; Michael Correll; Leilani Battle; Vidya Setlur; Anamaria Crisan (IEEE Trans. Vis. Comput. Graph., 2025)