Mohammad Samragh

617 total citations
23 papers, 264 citations indexed

About

Mohammad Samragh is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering. According to data from OpenAlex, Mohammad Samragh has authored 23 papers receiving a total of 264 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Artificial Intelligence, 7 papers in Computer Vision and Pattern Recognition and 5 papers in Electrical and Electronic Engineering. Recurrent topics in Mohammad Samragh's work include Adversarial Robustness in Machine Learning (11 papers), Anomaly Detection Techniques and Applications (6 papers) and Advanced Neural Network Applications (5 papers). Mohammad Samragh is often cited by papers focused on Adversarial Robustness in Machine Learning (11 papers), Anomaly Detection Techniques and Applications (6 papers) and Advanced Neural Network Applications (5 papers). Mohammad Samragh collaborates with scholars based in United States and United Kingdom. Mohammad Samragh's co-authors include Farinaz Koushanfar, Mojan Javaheripi, Tara Javidi, Mohammad Ghasemzadeh, M. Sadegh Riazi, Bita Darvish Rouhani, Behnam Khaleghi, Mohsen Imani, Tajana Rosing and Sahand Salamat and has published in prestigious journals such as IEEE Journal of Selected Topics in Signal Processing, IEEE Transactions on Dependable and Secure Computing and IEEE Security & Privacy.

In The Last Decade

Mohammad Samragh

18 papers receiving 258 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Mohammad Samragh United States	9	170	116	56	49	27	23	264
Coleman Hooper United States	6	92 0.5×	92 0.8×	52 0.9×	46 0.9×	17 0.6×	11	215
Barış Ege Netherlands	7	123 0.7×	86 0.7×	36 0.6×	86 1.8×	48 1.8×	10	188
Sumit Singh Dhanda India	4	105 0.6×	145 1.3×	77 1.4×	27 0.6×	40 1.5×	16	310
Bing Sun China	9	192 1.1×	64 0.6×	102 1.8×	24 0.5×	20 0.7×	65	303
Marco Donato United States	10	80 0.5×	146 1.3×	62 1.1×	58 1.2×	19 0.7×	24	249
Bilgiday Yuce United States	11	229 1.3×	83 0.7×	46 0.8×	191 3.9×	79 2.9×	21	286
Irwin O. Kennedy United Kingdom	6	228 1.3×	171 1.5×	58 1.0×	39 0.8×	68 2.5×	13	314
Pieter Robyns Belgium	9	166 1.0×	168 1.4×	38 0.7×	34 0.7×	58 2.1×	12	293
Josef Danial United States	10	242 1.4×	85 0.7×	94 1.7×	211 4.3×	84 3.1×	11	313
Utsav Banerjee United States	8	159 0.9×	52 0.4×	48 0.9×	50 1.0×	18 0.7×	24	237

Countries citing papers authored by Mohammad Samragh

Since Specialization

Citations

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

Fields of papers citing papers by Mohammad Samragh

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mohammad Samragh

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

All Works

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20 of 20 papers shown

Samragh, Mohammad, et al.. (2023). I See What You Hear: A Vision-Inspired Method to Localize Words. 1–5. 1 indexed citations

Zhang, Xinqiao, Mohammad Samragh, Siam U. Hussain, Ke Huang, & Farinaz Koushanfar. (2023). Scalable Binary Neural Network Applications in Oblivious Inference. ACM Transactions on Embedded Computing Systems. 23(3). 1–18.

Samragh, Mohammad, et al.. (2023). HEiMDaL: Highly Efficient Method for Detection and Localization of Wake-Words. 1–5.

Javaheripi, Mojan, Mohammad Samragh, & Farinaz Koushanfar. (2021). AutoRank: Automated Rank Selection for Effective Neural Network Customization. IEEE Journal on Emerging and Selected Topics in Circuits and Systems. 11(4). 611–619.

Hussain, Siam U., Mojan Javaheripi, Mohammad Samragh, & Farinaz Koushanfar. (2021). COINN: Crypto/ML Codesign for Oblivious Inference via Neural Networks. 3266–3281. 17 indexed citations

Samragh, Mohammad, Siam U. Hussain, Xinqiao Zhang, Ke Huang, & Farinaz Koushanfar. (2021). On the Application of Binary Neural Networks in Oblivious Inference. 4625–4634. 8 indexed citations

Samragh, Mohammad, Hossein Hosseini, Kambiz Azarian, & Joseph B. Soriaga. (2021). Private Split Inference of Deep Networks. 1 indexed citations

Javaheripi, Mojan, Mohammad Samragh, Tara Javidi, & Farinaz Koushanfar. (2020). AdaNS: Adaptive Non-Uniform Sampling for Automated Design of Compact DNNs. IEEE Journal of Selected Topics in Signal Processing. 14(4). 750–764. 5 indexed citations

Samragh, Mohammad, Mojan Javaheripi, & Farinaz Koushanfar. (2020). EncoDeep. ACM Transactions on Embedded Computing Systems. 19(6). 1–29. 7 indexed citations

10.

Javaheripi, Mojan, Mohammad Samragh, Bita Darvish Rouhani, Tara Javidi, & Farinaz Koushanfar. (2020). CuRTAIL: ChaRacterizing and Thwarting AdversarIal Deep Learning. IEEE Transactions on Dependable and Secure Computing. 18(2). 736–752. 6 indexed citations

11.

Javaheripi, Mojan, Mohammad Samragh, Tara Javidi, & Farinaz Koushanfar. (2020). GeneCAI: Genetic Evolution for Acquiring Compact AI. arXiv (Cornell University). 350–358. 2 indexed citations

12.

Riazi, M. Sadegh, Mohammad Samragh, Hao Chen, et al.. (2019). XONN: XNOR-based oblivious deep neural network inference. USENIX Security Symposium. 1501–1518. 36 indexed citations

13.

Imani, Mohsen, Sahand Salamat, Behnam Khaleghi, et al.. (2019). SparseHD: Algorithm-Hardware Co-optimization for Efficient High-Dimensional Computing. 190–198. 44 indexed citations

14.

Samragh, Mohammad, et al.. (2019). Safe Machine Learning and Defeating Adversarial Attacks. IEEE Security & Privacy. 17(2). 31–38. 30 indexed citations

15.

Rouhani, Bita Darvish, Mohammad Samragh, Tara Javidi, & Farinaz Koushanfar. (2018). Safe Machine Learning and Defeating Adversarial Attacks. 2 indexed citations

16.

Rouhani, Bita Darvish, Mohammad Samragh, Mojan Javaheripi, Tara Javidi, & Farinaz Koushanfar. (2018). DeepFense. 1–8. 26 indexed citations

17.

Ghasemzadeh, Mohammad, Mohammad Samragh, & Farinaz Koushanfar. (2017). ResBinNet: Residual Binary Neural Network.. arXiv (Cornell University). 1 indexed citations

18.

Rouhani, Bita Darvish, Mohammad Samragh, Tara Javidi, & Farinaz Koushanfar. (2017). CuRTAIL: ChaRacterizing and Thwarting AdversarIal deep Learning. 4 indexed citations

19.

Samragh, Mohammad, Mohammad Ghasemzadeh, & Farinaz Koushanfar. (2017). Customizing Neural Networks for Efficient FPGA Implementation. 85–92. 41 indexed citations

20.

Riazi, M. Sadegh, Mohammad Samragh, & Farinaz Koushanfar. (2017). CAMsure. ACM Transactions on Embedded Computing Systems. 16(5s). 1–20. 21 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.

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