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.
This map shows the geographic impact of Eric Horvitz'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 Eric Horvitz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric Horvitz more than expected).
This network shows the impact of papers produced by Eric Horvitz. 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 Eric Horvitz. The network helps show where Eric Horvitz may publish in the future.
Co-authorship network of co-authors of Eric Horvitz
This figure shows the co-authorship network connecting the top 25 collaborators of Eric Horvitz.
A scholar is included among the top collaborators of Eric Horvitz 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 Eric Horvitz. Eric Horvitz is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Kamar, Ece, Ashish Kapoor, & Eric Horvitz. (2013). Lifelong learning for acquiring the wisdom of the crowd. International Joint Conference on Artificial Intelligence. 2313–2320.20 indexed citations
8.
Bohus, Dan, Ece Kamar, & Eric Horvitz. (2012). Towards Situated Collaboration. North American Chapter of the Association for Computational Linguistics. 13–14.3 indexed citations
Weld, Daniel S., Eytan Adar, Lydia B. Chilton, et al.. (2012). Personalized Online Education — A Crowdsourcing Challenge. National Conference on Artificial Intelligence. 159–163.43 indexed citations
11.
Shahaf, Dafna & Eric Horvitz. (2009). Investigations of continual computation. International Joint Conference on Artificial Intelligence. 285–291.3 indexed citations
12.
Kamar, Ece & Eric Horvitz. (2009). Collaboration and shared plans in the open world: studies of ridesharing. International Joint Conference on Artificial Intelligence. 187–194.100 indexed citations
13.
Kapoor, Ashish & Eric Horvitz. (2009). Breaking Boundaries Between Induction Time and Diagnosis Time Active Information Acquisition. Neural Information Processing Systems. 22. 898–906.2 indexed citations
14.
Ruan, Yongshao, Eric Horvitz, & Henry Kautz. (2003). Hardness-Aware Restart Policies. International Joint Conference on Artificial Intelligence.4 indexed citations
15.
Paek, Tim & Eric Horvitz. (1999). Uncertainty, Utility, and Misunderstanding: A Decision-Theoretic Perspective on Grounding in Conversational Systems. National Conference on Artificial Intelligence.39 indexed citations
16.
Toyama, Kentaro & Eric Horvitz. (1999). Bayesian Modality Fusion: Probabilistic Integration of Multiple Vision Algorithms for Head Tracking.49 indexed citations
17.
Horvitz, Eric. (1999). Uncertainty, Action, and Interaction: In Pursuit of Mixed-Initiative Computing. 17–20.40 indexed citations
18.
Horvitz, Eric & Michael Shwe. (1995). Handsfree Decision Support: Toward a Non-invasive Human-Computer Interface*.. PubMed Central. 955–955.4 indexed citations
19.
Shwe, Michael, Blackford Middleton, David Heckerman, et al.. (1990). A Probabilistic Reformulation of the Quick Medical Reference System. PubMed Central. 790–794.7 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.