Mathew Laibowitz

427 citations
13 papers · 237 · h-index 7

Impact in

Papers in

Mathew Laibowitz

13 papers receiving 224 citations

Peers

Mathew Laibowitz
Comparison fields: 5 of 55
  • Human-Computer Interaction 64
  • Computer Vision and Pattern Recognition 94
  • Computer Networks and Communications 89
  • Computer Science Applications 21
  • Information Systems and Management 19
Replace Jonathan Gips with:
Jonathan Gips United States
Masayasu Futakawa Japan
Heikki Keränen Finland
Stavros Antifakos Switzerland
Esko Strömmer Finland
Séamus McLoone Ireland
Alexander Nelson United States
Anindya Maiti United States
Senaka Buthpitiya United States
Casey J. Helfrich United States
Mathew Laibowitz relative to Jonathan Gips United States Jonathan Gips's profile →
Citations per field
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Jonathan Gips · 1×
Citations per year

Countries citing papers authored by Mathew Laibowitz

Since Specialization
Citations

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

Fields of papers citing papers by Mathew Laibowitz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 10 scholars most cited alongside Mathew Laibowitz, 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 Mathew Laibowitz Line = papers co-authored together Mathew Laibowitz links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1 200767
2 200948
3 200641
4 200932
5
THE UBER-BADGE - A VERSATILE PLATFORM AT THE JUNCTURE BETWEEN WEARABLE AND SOCIAL COMPUTING
200415
6 20099
7 20068
8
Wearable Wireless Transceivers
20046
9 20104
10 20093
11 20102
12 20091
13 20121

About Mathew Laibowitz

Mathew Laibowitz is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction, Computer Networks and Communications, Information Systems and Management and Computer Science Applications, having authored 13 papers that have together received 237 indexed citations. Recurring topics across this work include Context-Aware Activity Recognition Systems (5 papers), Interactive and Immersive Displays (4 papers), Innovative Human-Technology Interaction (4 papers), Personal Information Management and User Behavior (3 papers), Mobile Crowdsensing and Crowdsourcing (3 papers), Augmented Reality Applications (2 papers), Music Technology and Sound Studies (2 papers) and Complex Network Analysis Techniques (1 paper). The work is most often cited by research in Human-Computer Interaction (64 citations), Computer Vision and Pattern Recognition (94 citations), Computer Networks and Communications (89 citations), Computer Science Applications (21 citations) and Information Systems and Management (19 citations). Mathew Laibowitz has collaborated with scholars based in United States and Finland. Frequent co-authors include Joseph A. Paradiso, Nan‐Wei Gong, Alex Pentland, Jonathan Gips, Mark Feldmeier, Joshua Lifton, Drew Harry, David Merrill, Pattie Maes and Ronald Azuma. Their work appears in journals such as IEEE Pervasive Computing, Personal and Ubiquitous Computing and DSpace@MIT (Massachusetts Institute of Technology).

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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