Justin Whitehouse
- Artificial Intelligence
- Molecular Biology
- Statistical and Nonlinear Physics
- Computer Vision and Pattern Recognition
- Signal Processing
- Co-authors
- M. R. EvansSatya N. MajumdarJunfeng YangSuman JanaShiqi WangKexin PeiYinzhi CaoWeina Wang
- Topics
- Adversarial Robustness in Machine Learning (3 papers)Cloud Computing and Resource Management (2 papers)Parallel Computing and Optimization Techniques (2 papers)
- Journals
- Journal of Physics D Applied PhysicsACM SIGOPS Operating Systems ReviewACM SIGMETRICS Performance Evaluation Review
- Partner nations
- United StatesUnited KingdomFrance
In The Last Decade
Justin Whitehouse
6 papers receiving 146 citations
Peers
Comparison fields: 5 of 40
- Artificial Intelligence 88
- Molecular Biology 60
- Statistical and Nonlinear Physics 28
- Computer Vision and Pattern Recognition 21
- Signal Processing 19
Countries citing papers authored by Justin Whitehouse
This map shows the geographic impact of Justin Whitehouse'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 Justin Whitehouse with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Justin Whitehouse more than expected).
Fields of papers citing papers by Justin Whitehouse
This network shows the impact of papers produced by Justin Whitehouse. 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 Justin Whitehouse. The network helps show where Justin Whitehouse may publish in the future.
Co-authorship network of co-authors of Justin Whitehouse
This figure shows the co-authorship network connecting the top 25 collaborators of Justin Whitehouse. A scholar is included among the top collaborators of Justin Whitehouse 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 Justin Whitehouse. Justin Whitehouse 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 | 1 | |
| 3 | 3 | |
| 4 | Formal Security Analysis of Neural Networks using Symbolic Intervals | 48 |
| 5 | 47 | |
| 6 | 59 | |
| 7 | 1 | |
| 8 | 2 |
About Justin Whitehouse
Justin Whitehouse is a scholar working on Instrumentation, Hardware and Architecture and Software, having authored 8 papers that have together received 161 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (3 papers), Cloud Computing and Resource Management (2 papers) and Parallel Computing and Optimization Techniques (2 papers). The work is most often cited by research in Software (17 citations), Artificial Intelligence (88 citations) and Statistical and Nonlinear Physics (28 citations). Justin Whitehouse has collaborated with scholars based in United States, United Kingdom and France. Frequent co-authors include M. R. Evans, Satya N. Majumdar, Junfeng Yang, Suman Jana, Shiqi Wang, Kexin Pei, Yinzhi Cao, Weina Wang, Mor Harchol‐Balter and Carl Vondrick. Their work appears in journals such as Journal of Physics D Applied Physics, ACM SIGOPS Operating Systems Review and ACM SIGMETRICS Performance Evaluation Review.
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.