Austin Waters

660 total citations
10 papers, 381 citations indexed

About

Austin Waters is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Austin Waters has authored 10 papers receiving a total of 381 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 4 papers in Signal Processing and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Austin Waters's work include Speech Recognition and Synthesis (5 papers), Music and Audio Processing (4 papers) and Natural Language Processing Techniques (4 papers). Austin Waters is often cited by papers focused on Speech Recognition and Synthesis (5 papers), Music and Audio Processing (4 papers) and Natural Language Processing Techniques (4 papers). Austin Waters collaborates with scholars based in United States and United Kingdom. Austin Waters's co-authors include Yevgen Chebotar, Risto Miikkulainen, Pedro J. Moreno, Zhongdi Qu, Parisa Haghani, Neeraj Gaur, Raymond J. Mooney, Joseph Reisinger, Jason Baldridge and Arun Narayanan and has published in prestigious journals such as AI Magazine, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and International Conference on Machine Learning.

In The Last Decade

Austin Waters

10 papers receiving 345 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Austin Waters United States	8	308	102	76	24	21	10	381
Mohammad Al-Rubaie United States	4	226 0.7×	35 0.3×	46 0.6×	22 0.9×	20 1.0×	5	307
Dingfan Chen Germany	5	271 0.9×	40 0.4×	73 1.0×	7 0.3×	10 0.5×	9	311
Mourad Khayati Switzerland	8	126 0.4×	88 0.9×	14 0.2×	5 0.2×	8 0.4×	19	188
Wangchunshu Zhou China	14	382 1.2×	16 0.2×	174 2.3×	7 0.3×	3 0.1×	37	476
Christopher A. Choquette-Choo United States	6	302 1.0×	33 0.3×	84 1.1×	14 0.6×	12 0.6×	10	406
Shuhuai Ren China	8	404 1.3×	106 1.0×	99 1.3×	5 0.2×	3 0.1×	14	477
Max Bartolo United Kingdom	6	398 1.3×	13 0.1×	164 2.2×	13 0.5×	4 0.2×	13	486
Andrew Trask United Kingdom	5	262 0.9×	18 0.2×	38 0.5×	11 0.5×	14 0.7×	6	354
Hongyang Zhang China	7	178 0.6×	17 0.2×	56 0.7×	11 0.5×	4 0.2×	29	227

Countries citing papers authored by Austin Waters

Since Specialization

Citations

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

Fields of papers citing papers by Austin Waters

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Austin Waters

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

All Works

Sort: Min cites: Since: Top N: Style:

10 of 10 papers shown

1.

Wang, Su, Vighnesh Birodkar, Aleksandra Faust, et al.. (2022). Less is More: Generating Grounded Navigation Instructions from Landmarks. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 15407–15417. 24 indexed citations

2.

Sanabria, Ramon, Austin Waters, & Jason Baldridge. (2021). Talk, Don’t Write: A Study of Direct Speech-Based Image Retrieval. 7 indexed citations

3.

Parekh, Zarana, Jason Baldridge, Daniel Cer, Austin Waters, & Yinfei Yang. (2021). Crisscrossed Captions: Extended Intramodal and Intermodal Semantic Similarity Judgments for MS-COCO. 2855–2870. 26 indexed citations

4.

Waters, Austin, Neeraj Gaur, Parisa Haghani, Pedro J. Moreno, & Zhongdi Qu. (2019). Leveraging Language ID in Multilingual End-to-End Speech Recognition. 928–935. 20 indexed citations

5.

Haghani, Parisa, Arun Narayanan, Michiel Bacchiani, et al.. (2018). From Audio to Semantics: Approaches to End-to-End Spoken Language Understanding. 720–726. 77 indexed citations

6.

Chebotar, Yevgen & Austin Waters. (2016). Distilling Knowledge from Ensembles of Neural Networks for Speech Recognition. 3439–3443. 99 indexed citations

7.

Elfeky, Mohamed, et al.. (2016). Towards acoustic model unification across dialects. 624–628. 18 indexed citations

8.

Waters, Austin & Risto Miikkulainen. (2014). GRADE: Machine‐Learning Support for Graduate Admissions. AI Magazine. 35(1). 64–75. 55 indexed citations

9.

Waters, Austin & Risto Miikkulainen. (2013). GRADE: Machine Learning Support for Graduate Admissions. Proceedings of the AAAI Conference on Artificial Intelligence. 27(2). 1479–1486. 6 indexed citations

10.

Reisinger, Joseph, et al.. (2010). Spherical Topic Models. International Conference on Machine Learning. 903–910. 49 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.

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