Walter S. Lasecki

4.2k citations
113 papers · 2.6k indexed · 1 hit paper · h-index 27
Topics
Mobile Crowdsensing and Crowdsourcing (76 papers)Data Stream Mining Techniques (21 papers)Personal Information Management and User Behavior (17 papers)

In The Last Decade

Walter S. Lasecki

110 papers receiving 2.5k citations

Hit Papers

Beyond Accuracy: The Role of Mental Models in Human-AI Te...2019202620212023201950100150200

Peers

Walter S. Lasecki
Comparison fields: 5 of 113
  • Computer Science Applications 1.2k
  • Artificial Intelligence 1.1k
  • Computer Vision and Pattern Recognition 466
  • Human-Computer Interaction 365
  • Information Systems 305
Replace Lydia B. Chilton with:
Lydia B. Chilton United States
Andrew Begel United States
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Juho Kim South Korea
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Citations per field
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Citations per year

Countries citing papers authored by Walter S. Lasecki

Since Specialization
Citations

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

Fields of papers citing papers by Walter S. Lasecki

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Walter S. Lasecki. 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 Walter S. Lasecki. The network helps show where Walter S. Lasecki may publish in the future.

Co-authorship network of co-authors of Walter S. Lasecki

This figure shows the co-authorship network connecting the top 25 collaborators of Walter S. Lasecki. A scholar is included among the top collaborators of Walter S. Lasecki 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 Walter S. Lasecki. Walter S. Lasecki is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 28
2 10
3 0
4 0
5 15
6 1
7
A Study on Interaction in Human-in-the-Loop Machine Learning for Text Analytics.
9
8
Analyzing Assumptions in Conversation Disentanglement Research Through the Lens of a New Dataset and Model.
4
9 2
10 13
11
The Cost of Asking Crowd Workers to Behave Maliciously
6
12
Preserving Privacy in Crowd-Powered Systems
3
13
Generating real-time crowd advice to improve reinforcement learning agents
2
14 3
15 9
16 61
17 16
18 40
19 3
20
Text Alignment for Real-Time Crowd Captioning
17

About Walter S. Lasecki

Walter S. Lasecki is a scholar working on Computer Science Applications, Information Systems and Management and Human-Computer Interaction, having authored 113 papers that have together received 2.6k indexed citations. Recurring topics across this work include Mobile Crowdsensing and Crowdsourcing (76 papers), Data Stream Mining Techniques (21 papers) and Personal Information Management and User Behavior (17 papers). The work is most often cited by research in Computer Science Applications (1.2k citations), Human-Computer Interaction (365 citations) and Health Informatics (88 citations). Walter S. Lasecki has collaborated with scholars based in United States, South Korea and United Kingdom. Frequent co-authors include Jeffrey P. Bigham, Ece Kamar, Eric Horvitz, Daniel S. Weld, Raja Kushalnagar, Gagan Bansal, Besmira Nushi, Christopher D. Miller, Juho Kim and Michael S. Bernstein. Their work appears in journals such as PLoS ONE, Communications of the ACM and interactions.

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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