Johann Hauswald
- Computer Networks and Communications top 1%
- Computer Vision and Pattern Recognition top 1%
- Artificial Intelligence top 2%
- Electrical and Electronic Engineering top 10%
- Information Systems top 5%
- Co-authors
- Trevor MudgeLingjia TangJason MarsAustin RovinskiYiping KangCao GaoRonald DreslinskiMichael A. Laurenzano
- Topics
- IoT and Edge/Fog Computing (11 papers)Advanced Neural Network Applications (5 papers)Caching and Content Delivery (4 papers)
- Cited by
- Computer Networks and CommunicationsComputer Vision and Pattern RecognitionHardware and Architecture
- Partner nations
- United StatesBrazilChina
In The Last Decade
Johann Hauswald
14 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 71
- Computer Networks and Communications 860
- Computer Vision and Pattern Recognition 755
- Artificial Intelligence 482
- Electrical and Electronic Engineering 372
- Information Systems 235
Countries citing papers authored by Johann Hauswald
This map shows the geographic impact of Johann Hauswald'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 Johann Hauswald with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Johann Hauswald more than expected).
Fields of papers citing papers by Johann Hauswald
This network shows the impact of papers produced by Johann Hauswald. 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 Johann Hauswald. The network helps show where Johann Hauswald may publish in the future.
Co-authorship network of co-authors of Johann Hauswald
This figure shows the co-authorship network connecting the top 25 collaborators of Johann Hauswald. A scholar is included among the top collaborators of Johann Hauswald 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 Johann Hauswald. Johann Hauswald is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 12 | |
| 2 | 19 | |
| 3 | 111 | |
| 4 | Neurosurgeonbreakdown → | 449 |
| 5 | Neurosurgeonbreakdown → | 527 |
| 6 | 17 | |
| 7 | 13 | |
| 8 | 4 | |
| 9 | 127 | |
| 10 | 5 | |
| 11 | 26 | |
| 12 | 135 | |
| 13 | 13 | |
| 14 | 41 |
About Johann Hauswald
Johann Hauswald is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications and Hardware and Architecture, having authored 14 papers that have together received 1.5k indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (11 papers), Advanced Neural Network Applications (5 papers) and Caching and Content Delivery (4 papers). The work is most often cited by research in Computer Networks and Communications (860 citations), Computer Vision and Pattern Recognition (755 citations) and Hardware and Architecture (125 citations). Johann Hauswald has collaborated with scholars based in United States, Brazil and China. Frequent co-authors include Trevor Mudge, Lingjia Tang, Jason Mars, Austin Rovinski, Yiping Kang, Cao Gao, Ronald Dreslinski, Michael A. Laurenzano, Quan Chen and Vinícius Petrucci. Their work appears in journals such as Proceedings of the VLDB Endowment, ACM Transactions on Computer Systems and ACM SIGPLAN Notices.
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.