Lynn Miller

567 total citations · 1 hit paper
12 papers, 264 citations indexed

About

Lynn Miller is a scholar working on Human-Computer Interaction, Information Systems and Global and Planetary Change. According to data from OpenAlex, Lynn Miller has authored 12 papers receiving a total of 264 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Human-Computer Interaction, 4 papers in Information Systems and 4 papers in Global and Planetary Change. Recurrent topics in Lynn Miller's work include Usability and User Interface Design (6 papers), Persona Design and Applications (4 papers) and Software Engineering Techniques and Practices (4 papers). Lynn Miller is often cited by papers focused on Usability and User Interface Design (6 papers), Persona Design and Applications (4 papers) and Software Engineering Techniques and Practices (4 papers). Lynn Miller collaborates with scholars based in Australia, Canada and China. Lynn Miller's co-authors include Geoffrey I. Webb, Germain Forestier, Mahsa Salehi, Navid Mohammadi Foumani, Chang Wei Tan, Marta Yebra, Liujun Zhu, Charlotte Pelletier, François Petitjean and Christoph Rüdiger and has published in prestigious journals such as ACM Computing Surveys, ISPRS Journal of Photogrammetry and Remote Sensing and Environmental Modelling & Software.

In The Last Decade

Lynn Miller

12 papers receiving 248 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Deep Learning for Time Series Classification and Extrinsic Regression: A Current Survey

2024 80 citations Navid Mohammadi Foumani, Lynn Miller et al. ACM Computing Surveys profile →

Peers

Lynn Miller

IS

AI

HI

GPC

SP

Pragya Agarwal India

José M. Noguera Spain

Ilyes Jenhani Saudi Arabia

Hazra Imran Canada

Radha Senthilkumar India

Zdena Dobešová Czechia

Jérôme Gensel France

S. Margret Anouncia India

Damjan Strnad Slovenia

Khyrina Airin Fariza Abu Samah Malaysia

Pragya Agarwal India

Lynn Miller

83 ×0.9

IS

60 ×1.0

AI

13 ×0.2

HI

42 ×0.9

GPC

65 ×1.6

SP

Citations per year, relative to Lynn Miller Lynn Miller (= 1×) peers Pragya Agarwal

Countries citing papers authored by Lynn Miller

Since Specialization

Citations

This map shows the geographic impact of Lynn Miller's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Lynn Miller with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lynn Miller more than expected).

Fields of papers citing papers by Lynn Miller

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lynn Miller. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Lynn Miller. The network helps show where Lynn Miller may publish in the future.

Co-authorship network of co-authors of Lynn Miller

This figure shows the co-authorship network connecting the top 25 collaborators of Lynn Miller. A scholar is included among the top collaborators of Lynn Miller based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Lynn Miller. Lynn Miller is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

12 of 12 papers shown

1.

Foumani, Navid Mohammadi, Lynn Miller, Chang Wei Tan, et al.. (2024). Deep Learning for Time Series Classification and Extrinsic Regression: A Current Survey. ACM Computing Surveys. 56(9). 1–45. 80 indexed citations breakdown →

2.

Miller, Lynn, Charlotte Pelletier, & Geoffrey I. Webb. (2024). Deep Learning for Satellite Image Time-Series Analysis: A review. IEEE Geoscience and Remote Sensing Magazine. 12(3). 81–124. 20 indexed citations

3.

Miller, Lynn, Liujun Zhu, Marta Yebra, Christoph Rüdiger, & Geoffrey I. Webb. (2023). Projecting live fuel moisture content via deep learning. International Journal of Wildland Fire. 32(5). 709–727. 8 indexed citations

4.

Miller, Lynn, Liujun Zhu, Marta Yebra, Christoph Rüdiger, & Geoffrey I. Webb. (2022). Multi-modal temporal CNNs for live fuel moisture content estimation. Environmental Modelling & Software. 156. 105467–105467. 13 indexed citations

5.

Zhu, Liujun, et al.. (2021). Live fuel moisture content estimation from MODIS: A deep learning approach. ISPRS Journal of Photogrammetry and Remote Sensing. 179. 81–91. 33 indexed citations

6.

Miller, Lynn, Michael Mintrom, Ann E. Nicholson, et al.. (2020). AI for monitoring the Sustainable Development Goals and supporting and promoting action and policy development. 180–185. 10 indexed citations

7.

Miller, Lynn, et al.. (2009). Agile user experience SIG. 2751–2754. 10 indexed citations

8.

Miller, Lynn, et al.. (2008). Extreme usability. 2269–2272. 12 indexed citations

9.

Miller, Lynn, et al.. (2008). Optimizing agile user-centred design. 3897–3900. 18 indexed citations

10.

Miller, Lynn. (2006). Case study of customer input for a successful product. 225–234. 41 indexed citations

11.

Miller, Lynn. (2006). Interaction Designers and Agile Development: A Partnership. 5 indexed citations

12.

Sharp, Helen, et al.. (2006). Agile development. 32–35. 14 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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