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ORCIDAndrew M. McNutt
Person information
- affiliation: University of Utah, Salt Lake City, UT, USA
- affiliation (former): University of Chicago, IL, USA
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2020 – today
- 2024
[j6]Nicolas Kruchten, Andrew M. McNutt
, Michael J. McGuffin:
Metrics-Based Evaluation and Comparison of Visualization Notations. IEEE Trans. Vis. Comput. Graph. 30(1): 425-435 (2024)- 2023
- [j5]Victor Schetinger, Sara Di Bartolomeo, Mennatallah El-Assady, Andrew M. McNutt, Matthias Miller, J. P. A. Passos, Jane Lydia Adams:
Doom or Deliciousness: Challenges and Opportunities for Visualization in the Age of Generative Models. Comput. Graph. Forum 42(3): 423-435 (2023) - [j4]Andrew M. McNutt:
No Grammar to Rule Them All: A Survey of JSON-style DSLs for Visualization. IEEE Trans. Vis. Comput. Graph. 29(1): 160-170 (2023) - [c9]Andrew M. McNutt, Anton Outkine, Ravi Chugh:
A Study of Editor Features in a Creative Coding Classroom. CHI 2023: 121:1-121:15 - [c8]Andrew M. McNutt, Chenglong Wang, Robert A. DeLine, Steven Mark Drucker:
On the Design of AI-powered Code Assistants for Notebooks. CHI 2023: 434:1-434:16 - [c7]Andrew M. McNutt, Ravi Chugh:
Projectional Editors for JSON-Based DSLs. VL/HCC 2023: 60-70 - [i12]Andrew M. McNutt, Chenglong Wang, Robert A. DeLine, Steven Mark Drucker:
On the Design of AI-powered Code Assistants for Notebooks. CoRR abs/2301.11178 (2023) - [i11]Andrew M. McNutt, Anton Outkine, Ravi Chugh:
A Study of Editor Features in a Creative Coding Classroom. CoRR abs/2301.13302 (2023) - [i10]Andrew M. McNutt, Ravi Chugh:
Projectional Editors for JSON-Based DSLs. CoRR abs/2307.11260 (2023) - [i9]Nicolas Kruchten, Andrew M. McNutt, Michael J. McGuffin:
Metrics-Based Evaluation and Comparison of Visualization Notations. CoRR abs/2308.16353 (2023) - [i8]Ken Gu, Madeleine Grunde-McLaughlin, Andrew M. McNutt, Jeffrey Heer, Tim Althoff:
How Do Data Analysts Respond to AI Assistance? A Wizard-of-Oz Study. CoRR abs/2309.10108 (2023) - 2022
- [j3]Agatha Seo-Hyun Kim, Andrew M. McNutt:
Goethe and Candolle: National forms of scientific writing? Theory Biosci. 141(3): 321-338 (2022) - [i7]Andrew M. McNutt:
No Grammar to Rule Them All: A Survey of JSON-style DSLs for Visualization. CoRR abs/2207.07998 (2022) - 2021
- [j2]Andrew M. McNutt:
What are Table Cartograms Good for Anyway? An Algebraic Analysis. Comput. Graph. Forum 40(3): 61-73 (2021) - [c6]Andrew M. McNutt, Ravi Chugh:
Integrated Visualization Editing via Parameterized Declarative Templates. CHI 2021: 17:1-17:14 - [c5]Will Brackenbury, Andrew M. McNutt, Kyle Chard, Aaron J. Elmore, Blase Ur:
KondoCloud: Improving Information Management in Cloud Storage via Recommendations Based on File Similarity. UIST 2021: 69-83 - [c4]Andrew M. McNutt:
On the Potential of Zines as a Medium for Visualization. IEEE VIS (Short Papers) 2021: 176-180 - [i6]Andrew M. McNutt, Ravi Chugh:
Integrated Visualization Editing via Parameterized Declarative Templates. CoRR abs/2101.07902 (2021) - [i5]Andrew M. McNutt:
What are Table Cartograms Good for Anyway? An Algebraic Analysis. CoRR abs/2104.04042 (2021) - [i4]Andrew M. McNutt:
On the Potential of Zines as a Medium for Visualization. CoRR abs/2108.02177 (2021) - [i3]Andrew M. McNutt, Lilian Huang, Kathryn Koenig:
Visualization for Villainy. CoRR abs/2109.06007 (2021) - 2020
- [c3]Andrew M. McNutt, Anamaria Crisan, Michael Correll:
Divining Insights: Visual Analytics Through Cartomancy. CHI Extended Abstracts 2020: 1-16 - [c2]Andrew M. McNutt, Gordon L. Kindlmann, Michael Correll:
Surfacing Visualization Mirages. CHI 2020: 1-16 - [i2]Andrew M. McNutt, Gordon L. Kindlmann, Michael Correll:
Surfacing Visualization Mirages. CoRR abs/2001.02316 (2020) - [i1]Andrew M. McNutt, Agatha Kim, Sergio Elahi, Kazutaka Takahashi:
Supporting Expert Close Analysis of Historical Scientific Writings: A Case Study for Near-by Reading. CoRR abs/2009.02384 (2020)
2010 – 2019
- 2019
- [c1]Andrew M. McNutt, Gordon L. Kindlmann:
Improving the Scalability of Interactive Visualization Systems for Exploring Threaded Conversations. EuroVis (Posters) 2019: 53-55 - 2015
- [j1]Alex M. Clark, Krishna Dole, Anna Coulon-Spektor, Andrew M. McNutt, George Grass, Joel S. Freundlich, Robert C. Reynolds, Sean Ekins:
Open Source Bayesian Models. 1. Application to ADME/Tox and Drug Discovery Datasets. J. Chem. Inf. Model. 55(6): 1231-1245 (2015)
Coauthor Index
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last updated on 2024-04-02 22:38 CEST by the dblp team
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