Tri Dao

2.8k total citations
12 papers, 74 citations indexed

About

Tri Dao is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Tri Dao has authored 12 papers receiving a total of 74 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Computer Vision and Pattern Recognition, 4 papers in Artificial Intelligence and 2 papers in Signal Processing. Recurrent topics in Tri Dao's work include Advanced Image and Video Retrieval Techniques (2 papers), Multimodal Machine Learning Applications (2 papers) and Advanced Neural Network Applications (2 papers). Tri Dao is often cited by papers focused on Advanced Image and Video Retrieval Techniques (2 papers), Multimodal Machine Learning Applications (2 papers) and Advanced Neural Network Applications (2 papers). Tri Dao collaborates with scholars based in United States, United Kingdom and Denmark. Tri Dao's co-authors include Albert Gu, Cristina Re, Christopher Ré, Christopher De, Atri Rudra, Aaron Gokaslan, Beidi Chen, Alexander Ratner, Volodymyr Kuleshov and Zhao Song and has published in prestigious journals such as PubMed, arXiv (Cornell University) and neural information processing systems.

In The Last Decade

Tri Dao

10 papers receiving 72 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Tri Dao United States	6	37	20	18	9	5	12	74
Samuel Chapman United States	5	54 1.5×	18 0.9×	18 1.0×	18 2.0×	5 1.0×	7	113
Will Grathwohl Canada	4	48 1.3×	31 1.6×	14 0.8×	7 0.8×	5 1.0×	7	90
Leonardo O. Iheme Türkiye	5	54 1.5×	16 0.8×	8 0.4×	26 2.9×	5 1.0×	13	82
Yonghui Wu China	6	32 0.9×	56 2.8×	9 0.5×	15 1.7×	2 0.4×	27	129
Zachary Nado United States	3	74 2.0×	33 1.6×	6 0.3×	6 0.7×	2 0.4×	3	102
Mozhdeh Gheini United States	2	31 0.8×	22 1.1×	7 0.4×	8 0.9×	1 0.2×	5	74
Yuxuan Sun China	6	74 2.0×	37 1.9×	8 0.4×	15 1.7×	4 0.8×	17	120
Mateo Rojas-Carulla Germany	4	74 2.0×	25 1.3×	35 1.9×	2 0.2×	2 0.4×	5	125

Countries citing papers authored by Tri Dao

Since Specialization

Citations

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

Fields of papers citing papers by Tri Dao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tri Dao

This figure shows the co-authorship network connecting the top 25 collaborators of Tri Dao. A scholar is included among the top collaborators of Tri Dao 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 Tri Dao. Tri Dao 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:

12 of 12 papers shown

1.

Dao, Tri, et al.. (2024). Hydra: Bidirectional State Space Models Through Generalized Matrix Mixers. arXiv (Cornell University). 110876–110908. 1 indexed citations

2.

Gokaslan, Aaron, et al.. (2024). Caduceus: Bi-Directional Equivariant Long-Range DNA Sequence Modeling. PubMed. 235. 43632–43648. 17 indexed citations

3.

Adams, Sally, Quentin Anthony, Ben Athiwaratkun, et al.. (2024). RedPajama: an Open Dataset for Training Large Language Models. 116462–116492.

4.

Chen, Beidi, et al.. (2021). Scatterbrain: Unifying Sparse and Low-rank Attention. neural information processing systems. 34. 14 indexed citations

5.

Chen, Beidi, Zichang Liu, Zhaozhuo Xu, et al.. (2021). MONGOOSE: A Learnable LSH Framework for Efficient Neural Network Training. International Conference on Learning Representations. 5 indexed citations

6.

Davis, Jared Quincy, Albert Gu, Krzysztof Choromański, et al.. (2021). Catformer: Designing Stable Transformers via Sensitivity Analysis. 2489–2499.

7.

Dao, Tri, et al.. (2019). Adaptive Hashing for Model Counting.. Uncertainty in Artificial Intelligence. 271–280. 1 indexed citations

8.

Zhang, Jian, et al.. (2019). On the Downstream Performance of Compressed Word Embeddings.. PubMed. 32. 11782–11793. 6 indexed citations

9.

Dao, Tri, et al.. (2019). Approximating the Permanent by Sampling from Adaptive Partitions. arXiv (Cornell University). 32. 8858–8869. 1 indexed citations

10.

Dao, Tri, et al.. (2019). A Kernel Theory of Modern Data Augmentation.. PubMed. 97. 1528–1537. 19 indexed citations

11.

Dao, Tri, et al.. (2019). Learning Fast Algorithms for Linear Transforms Using Butterfly Factorizations.. PubMed. 97. 1517–1527. 7 indexed citations

12.

Dao, Tri, Christopher De, & Cristina Re. (2017). Gaussian Quadrature for Kernel Features.. PubMed. 30. 6109–6119. 3 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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