Vikash Sehwag

659 total citations
12 papers, 109 citations indexed

About

Vikash Sehwag is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Vikash Sehwag has authored 12 papers receiving a total of 109 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 2 papers in Signal Processing. Recurrent topics in Vikash Sehwag's work include Adversarial Robustness in Machine Learning (6 papers), Anomaly Detection Techniques and Applications (6 papers) and Advanced Neural Network Applications (2 papers). Vikash Sehwag is often cited by papers focused on Adversarial Robustness in Machine Learning (6 papers), Anomaly Detection Techniques and Applications (6 papers) and Advanced Neural Network Applications (2 papers). Vikash Sehwag collaborates with scholars based in United States, Switzerland and Taiwan. Vikash Sehwag's co-authors include Prateek Mittal, Mung Chiang, Arjun Nitin Bhagoji, Cristian Canton Ferrer, Chawin Sitawarin, Caner Hazırbaş, Albert Gordo, Tianhao Wang, Daniel Cullina and Tong Wu and has published in prestigious journals such as SHILAP Revista de lepidopterología, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and USENIX Security Symposium.

In The Last Decade

Vikash Sehwag

8 papers receiving 105 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Vikash Sehwag United States	5	76	33	20	11	11	12	109
Jinmian Ye China	6	91 1.2×	79 2.4×	13 0.7×	12 1.1×	17 1.5×	7	160
Yutaro Yamada Japan	5	152 2.0×	54 1.6×	29 1.4×	5 0.5×	23 2.1×	9	197
Florian Scheidegger Switzerland	6	47 0.6×	39 1.2×	7 0.3×	6 0.5×	16 1.5×	12	99
Mary Phuong Austria	4	113 1.5×	78 2.4×	9 0.5×	16 1.5×	12 1.1×	6	159
Kyoji Shibutani Taiwan	4	109 1.4×	81 2.5×	14 0.7×	13 1.2×	11 1.0×	10	124
Zijian Huang China	7	86 1.1×	13 0.4×	22 1.1×	25 2.3×	11 1.0×	19	136
M. Krishnamurthy India	7	51 0.7×	16 0.5×	16 0.8×	27 2.5×	13 1.2×	34	149
Kerem Varıcı Belgium	4	97 1.3×	69 2.1×	24 1.2×	16 1.5×	12 1.1×	12	116
Jaejun Lee South Korea	6	175 2.3×	86 2.6×	15 0.8×	12 1.1×	26 2.4×	22	233
Gabriele Ciravegna Italy	7	88 1.2×	20 0.6×	13 0.7×	13 1.2×	5 0.5×	21	138

Countries citing papers authored by Vikash Sehwag

Since Specialization

Citations

This map shows the geographic impact of Vikash Sehwag'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 Vikash Sehwag with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vikash Sehwag more than expected).

Fields of papers citing papers by Vikash Sehwag

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Vikash Sehwag. 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 Vikash Sehwag. The network helps show where Vikash Sehwag may publish in the future.

Co-authorship network of co-authors of Vikash Sehwag

This figure shows the co-authorship network connecting the top 25 collaborators of Vikash Sehwag. A scholar is included among the top collaborators of Vikash Sehwag 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 Vikash Sehwag. Vikash Sehwag is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

12 of 12 papers shown

1.

Chen, Chen, Zhizhong Li, Jingtao Li, et al.. (2025). Argus: A Compact and Versatile Foundation Model for Vision. 4418–4429.

2.

Sehwag, Vikash, et al.. (2025). Differentially Private Image Classification by Learning Priors from Random Processes. SHILAP Revista de lepidopterología. 15(1).

3.

Sehwag, Vikash, et al.. (2025). Stretching Each Dollar: Diffusion Training from Scratch on a Micro-Budget. 28596–28608. 1 indexed citations

4.

Ren, Jie, et al.. (2025). Self-Comparison for Dataset-Level Membership Inference in Large (Vision-)Language Model. 910–920.

5.

Andriushchenko, Maksym, Francesco Croce, Edgar Dobriban, et al.. (2024). JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models. 55005–55029.

6.

Sehwag, Vikash, et al.. (2023). A Light Recipe to Train Robust Vision Transformers. 225–253. 12 indexed citations

7.

Wu, Tong, Tianhao Wang, Vikash Sehwag, Saeed Mahloujifar, & Prateek Mittal. (2022). Just Rotate it: Deploying Backdoor Attacks via Rotation Transformation. 91–102. 20 indexed citations

8.

Sehwag, Vikash, et al.. (2022). Generating High Fidelity Data from Low-density Regions using Diffusion Models. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 11482–11491. 24 indexed citations

9.

Xiang, Chong, Arjun Nitin Bhagoji, Vikash Sehwag, & Prateek Mittal. (2021). PatchGuard: A provably robust defense against adversarial patches via small receptive fields and masking. USENIX Security Symposium. 2237–2254. 2 indexed citations

10.

Sehwag, Vikash, Mung Chiang, & Prateek Mittal. (2021). SSD: A Unified Framework for Self-Supervised Outlier Detection. arXiv (Cornell University). 17 indexed citations

11.

Sehwag, Vikash, Arjun Nitin Bhagoji, Liwei Song, et al.. (2019). Analyzing the Robustness of Open-World Machine Learning. 105–116. 29 indexed citations

12.

Sehwag, Vikash, Chawin Sitawarin, Arjun Nitin Bhagoji, et al.. (2018). Not All Pixels are Born Equal. 2285–2287. 4 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.

Explore authors with similar magnitude of impact