Citations per year, relative to Soheil Feizi Soheil Feizi (= 1×)
peers
Shu Wang
Countries citing papers authored by Soheil Feizi
Since
Specialization
Citations
This map shows the geographic impact of Soheil Feizi'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 Soheil Feizi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Soheil Feizi more than expected).
This network shows the impact of papers produced by Soheil Feizi. 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 Soheil Feizi. The network helps show where Soheil Feizi may publish in the future.
Co-authorship network of co-authors of Soheil Feizi
This figure shows the co-authorship network connecting the top 25 collaborators of Soheil Feizi.
A scholar is included among the top collaborators of Soheil Feizi 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 Soheil Feizi. Soheil Feizi is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Feizi, Soheil, et al.. (2021). Deep Partition Aggregation: Provable Defenses against General Poisoning Attacks. arXiv (Cornell University).7 indexed citations
6.
Feizi, Soheil, et al.. (2020). Wasserstein Smoothing: Certified Robustness against Wasserstein Adversarial Attacks. International Conference on Artificial Intelligence and Statistics. 3938–3947.6 indexed citations
7.
Lin, Wei-An, et al.. (2020). Dual Manifold Adversarial Robustness: Defense against Lp and non-Lp Adversarial Attacks. Neural Information Processing Systems. 33. 3487–3498.1 indexed citations
8.
Ismail, Aya Abdelsalam, et al.. (2020). Benchmarking Deep Learning Interpretability in Time Series Predictions. Neural Information Processing Systems. 33. 6441–6452.4 indexed citations
9.
Feizi, Soheil, et al.. (2020). De)Randomized Smoothing for Certifiable Defense against Patch Attacks. arXiv (Cornell University). 33. 6465–6475.7 indexed citations
10.
Goldstein, Tom, et al.. (2020). Curse of Dimensionality on Randomized Smoothing for Certifiable Robustness. International Conference on Machine Learning. 1. 5458–5467.2 indexed citations
11.
Daskalakis, Constantinos, et al.. (2020). GANs with Conditional Independence Graphs: On Subadditivity of Probability Divergences. arXiv (Cornell University).
12.
Feizi, Soheil, et al.. (2020). Certifying Confidence via Randomized Smoothing. Neural Information Processing Systems. 33. 5165–5177.1 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.