Ian McGraw
- Artificial Intelligence top 2%
- Signal Processing top 2%
- Computer Vision and Pattern Recognition top 10%
- Computer Science Applications top 5%
- Electrical and Electronic Engineering
- Co-authors
- Alexander GruensteinRohit PrabhavalkarKanishka RaoJames GlassGal ElidanStephanie SeneffYanzhang HeDaphne Koller
- Topics
- Speech and dialogue systems (16 papers)Speech Recognition and Synthesis (16 papers)Music and Audio Processing (12 papers)
- Journals
- Journal of Machine Learning ResearchInjuryIEEE Transactions on Audio Speech and Language Processing
- Partner nations
- United StatesNetherlandsUnited Kingdom
In The Last Decade
Ian McGraw
32 papers receiving 826 citations
Hit Papers
Peers
Comparison fields: 5 of 77
- Artificial Intelligence 777
- Signal Processing 388
- Computer Vision and Pattern Recognition 93
- Computer Science Applications 75
- Electrical and Electronic Engineering 63
Countries citing papers authored by Ian McGraw
This map shows the geographic impact of Ian McGraw'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 Ian McGraw with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ian McGraw more than expected).
Fields of papers citing papers by Ian McGraw
This network shows the impact of papers produced by Ian McGraw. 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 Ian McGraw. The network helps show where Ian McGraw may publish in the future.
Co-authorship network of co-authors of Ian McGraw
This figure shows the co-authorship network connecting the top 25 collaborators of Ian McGraw. A scholar is included among the top collaborators of Ian McGraw 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 Ian McGraw. Ian McGraw is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 4 | |
| 3 | 19 | |
| 4 | 6 | |
| 5 | 7 | |
| 6 | Streaming End-to-end Speech Recognition for Mobile Devicesbreakdown → | 345 |
| 7 | 7 | |
| 8 | 53 | |
| 9 | 97 | |
| 10 | 31 | |
| 11 | 11 | |
| 12 | 25 | |
| 13 | 9 | |
| 14 | FastInf: An Efficient Approximate Inference Library | 8 |
| 15 | Collecting Voices from the Cloud | 41 |
| 16 | 5 | |
| 17 | 32 | |
| 18 | 8 | |
| 19 | Speech-enabled card games for language learners | 5 |
| 20 | 10 |
About Ian McGraw
Ian McGraw is a scholar working on Signal Processing, Artificial Intelligence and Computer Science Applications, having authored 33 papers that have together received 966 indexed citations. Recurring topics across this work include Speech and dialogue systems (16 papers), Speech Recognition and Synthesis (16 papers) and Music and Audio Processing (12 papers). The work is most often cited by research in Signal Processing (388 citations), Artificial Intelligence (777 citations) and Computer Science Applications (75 citations). Ian McGraw has collaborated with scholars based in United States, Netherlands and United Kingdom. Frequent co-authors include Alexander Gruenstein, Rohit Prabhavalkar, Kanishka Rao, James Glass, Gal Elidan, Stephanie Seneff, Yanzhang He, Daphne Koller, Raziel Álvarez and David Rybach. Their work appears in journals such as Journal of Machine Learning Research, Injury and IEEE Transactions on Audio Speech and Language Processing.
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.