Heidi Lam

821 citations
17 papers · 508 indexed · h-index 10

Heidi Lam

17 papers receiving 489 citations

Peers

Heidi Lam
Comparison fields: 5 of 68
  • Computer Vision and Pattern Recognition 370
  • Human-Computer Interaction 67
  • Signal Processing 92
  • Information Systems and Management 46
  • Ecological Modeling 23
Replace Matt McKeon with:
Matt McKeon United States
H. Lam Canada
Nicholas Kong United States
Keith Andrews Austria
Mei C. Chuah United States
Purvi Saraiya United States
Eli T. Brown United States
Bahador Saket United States
Daniela Oelke Germany
Charles D. Stolper United States
Heidi Lam relative to Matt McKeon United States Matt McKeon's profile →
Citations per field
00.5×2.8×
Matt McKeon · 1×
Citations per year

Countries citing papers authored by Heidi Lam

Since Specialization
Citations

This map shows the geographic impact of Heidi Lam'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 Heidi Lam with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Heidi Lam more than expected).

Fields of papers citing papers by Heidi Lam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Heidi Lam. 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 Heidi Lam. The network helps show where Heidi Lam may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Heidi Lam, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Heidi Lam Line = papers co-authored together Heidi Lam links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1 201721
2 201751
3 2015110
4 20135
5
Big Data Storytelling Through Interactive Maps
20129
6 20114
7 20115
8 201014
9 20102
10 20082
11 200811
12 200740
13 200745
14 200613
15 200664
16 20065
17 2005107

About Heidi Lam

Heidi Lam is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction, Geography, Planning and Development, Signal Processing and Health Information Management, having authored 17 papers that have together received 508 indexed citations. Recurring topics across this work include Data Visualization and Analytics (14 papers), Multimedia Communication and Technology (4 papers), Data Management and Algorithms (3 papers), Geographic Information Systems Studies (2 papers), Image and Video Quality Assessment (2 papers), Data Analysis with R (2 papers), Interactive and Immersive Displays (2 papers) and Complex Network Analysis Techniques (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (370 citations), Human-Computer Interaction (67 citations), Signal Processing (92 citations), Information Systems and Management (46 citations) and Ecological Modeling (23 citations). Heidi Lam has collaborated with scholars based in Canada, United States and South Korea. Frequent co-authors include Tamara Munzner, Patrick Baudisch, Robert Kincaid, Sung-Hee Kim, Younah Kang, Sukwon Lee, Ji Soo Yi, Melanie Tory, Diane Tang and Daniel M. Russell. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, International Journal of Human-Computer Interaction, Computer Graphics Forum, Information Visualization and Open Collections.

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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