Brody Huval
- Artificial Intelligence top 1%
- Computer Vision and Pattern Recognition top 2%
- Electrical and Electronic Engineering
- Information Systems top 10%
- Computer Networks and Communications top 10%
- Co-authors
- Richard SocherAndrew Y. NgChristopher D. ManningDavid J. WuBryan CatanzaroAndrew NgTao WangAdam Coates
- Topics
- Advanced Image and Video Retrieval Techniques (1 paper)Industrial Vision Systems and Defect Detection (1 paper)Text and Document Classification Technologies (1 paper)
- Journals
- Empirical Methods in Natural Language ProcessingNeural Information Processing SystemsInternational Conference on Machine Learning
- Partner nations
- United States
In The Last Decade
Brody Huval
3 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 107
- Artificial Intelligence 986
- Computer Vision and Pattern Recognition 516
- Electrical and Electronic Engineering 111
- Information Systems 103
- Computer Networks and Communications 70
Countries citing papers authored by Brody Huval
This map shows the geographic impact of Brody Huval'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 Brody Huval with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Brody Huval more than expected).
Fields of papers citing papers by Brody Huval
This network shows the impact of papers produced by Brody Huval. 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 Brody Huval. The network helps show where Brody Huval may publish in the future.
Co-authorship network of co-authors of Brody Huval
This figure shows the co-authorship network connecting the top 25 collaborators of Brody Huval. A scholar is included among the top collaborators of Brody Huval 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 Brody Huval. Brody Huval is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Deep learning with COTS HPC systemsbreakdown → | 370 |
| 2 | Semantic Compositionality through Recursive Matrix-Vector Spacesbreakdown → | 767 |
| 3 | Convolutional-Recursive Deep Learning for 3D Object Classificationbreakdown → | 358 |
About Brody Huval
Brody Huval is a scholar working on Hardware and Architecture, Industrial and Manufacturing Engineering and Computer Vision and Pattern Recognition, having authored 3 papers that have together received 1.5k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (1 paper), Industrial Vision Systems and Defect Detection (1 paper) and Text and Document Classification Technologies (1 paper). The work is most often cited by research in Artificial Intelligence (986 citations), Computer Vision and Pattern Recognition (516 citations) and Computational Mathematics (7 citations). Brody Huval has collaborated with scholars based in United States. Frequent co-authors include Richard Socher, Andrew Y. Ng, Christopher D. Manning, David J. Wu, Bryan Catanzaro, Andrew Ng, Tao Wang and Adam Coates. Their work appears in journals such as Empirical Methods in Natural Language Processing, Neural Information Processing Systems and International Conference on Machine Learning.
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.