Eugene Ie

1.8k citations
23 papers · 900 · h-index 15

Impact in

Papers in

Eugene Ie

23 papers receiving 866 citations

Peers

Eugene Ie
Comparison fields: 5 of 76
  • Computer Vision and Pattern Recognition 357
  • Artificial Intelligence 382
  • Signal Processing 88
  • Management Science and Operations Research 57
  • Molecular Biology 304
Replace Liang Huang with:
Liang Huang China
Zexuan Zhong United States
Bokai Cao United States
Xuefeng Li China
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Varun Manjunatha United States
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Eugene Ie relative to Liang Huang China Liang Huang's profile →
Citations per field
00.5×2.6×
Liang Huang · 1×
Citations per year

Countries citing papers authored by Eugene Ie

Since Specialization
Citations

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

Fields of papers citing papers by Eugene Ie

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Eugene Ie, 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 Eugene Ie Line = papers co-authored together Eugene Ie links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005147
2 2020132
3 2005128
4 201966
5 200866
6 200455
7 201949
8 200740
9 200729
10 202125
11 200525
12 201022
13 201919
14 202017
15 201915
16 202014
17
Effective and General Evaluation for Instruction Conditioned Navigation using Dynamic Time Warping
201912
18 202010
19 202310
20 202110

About Eugene Ie

Eugene Ie is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology, Signal Processing and Management Science and Operations Research, having authored 23 papers that have together received 900 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (7 papers), Machine Learning in Bioinformatics (7 papers), Topic Modeling (5 papers), Genomics and Phylogenetic Studies (5 papers), Speech and dialogue systems (4 papers), Natural Language Processing Techniques (4 papers), Algorithms and Data Compression (3 papers) and Domain Adaptation and Few-Shot Learning (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (357 citations), Artificial Intelligence (382 citations), Signal Processing (88 citations), Management Science and Operations Research (57 citations) and Molecular Biology (304 citations). Eugene Ie has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Christina S. Leslie, Jason Baldridge, William Stafford Noble, Jason Weston, Alexander Ku, Rui Kuang, Vihan Jain, Yoav Freund, Peter Anderson and Roma Patel. Their work appears in journals such as Bioinformatics, Nucleic Acids Research, Journal of Bioinformatics and Computational Biology, Journal of Machine Learning Research and BMC Bioinformatics.

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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