Mohammad Malekzadeh
Impact in
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- Privacy-Preserving Technologies in Data
- Adversarial Robustness in Machine Learning
- Cryptography and Data Security
- Anomaly Detection Techniques and Applications
- Stochastic Gradient Optimization Techniques
- Internet Traffic Analysis and Secure E-voting
Papers in
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- Privacy-Preserving Technologies in Data 3
- Adversarial Robustness in Machine Learning 2
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- Digital Games and Media 1
- Privacy, Security, and Data Protection 1
- Co-authors
- Anastasia Borovykh (2 shared papers)Denız Gündüz (1 shared paper)Fahim Kawsar (4 shared papers)Ali Farhadi (1 shared paper)Ali Shahin Shamsabadi (1 shared paper)Dimitris Spathis (1 shared paper)Flora D. Salim (1 shared paper)Andrea Cavallaro (1 shared paper)
- Journals
- Royal Society Open Science (1 paper)Virology Journal (1 paper)International Journal of Advanced Computer Science and Applications (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- United KingdomIranUnited States
In The Last Decade
Mohammad Malekzadeh
8 papers receiving 49 citations
Peers
Comparison fields: 5 of 28
- Artificial Intelligence 33
- Health Informatics 1
- Computer Science Applications 4
- Computer Vision and Pattern Recognition 10
- Applied Psychology 2
Countries citing papers authored by Mohammad Malekzadeh
This map shows the geographic impact of Mohammad Malekzadeh'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 Malekzadeh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohammad Malekzadeh more than expected).
Fields of papers citing papers by Mohammad Malekzadeh
This network shows the impact of papers produced by Mohammad Malekzadeh. 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 Malekzadeh. The network helps show where Mohammad Malekzadeh may publish in the future.
Co-authors
The 16 scholars most cited alongside Mohammad Malekzadeh, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 23 | |
| 2 | 2024 | 8 | |
| 3 | 2020 | 5 | |
| 4 | 2024 | 4 | |
| 5 | 2020 | 3 | |
| 6 | 2025 | 2 | |
| 7 | 2024 | 2 | |
| 8 | 2017 | 2 | |
| 9 | 2025 | 0 | |
| 10 | 2025 | 0 |
About Mohammad Malekzadeh
Mohammad Malekzadeh is a scholar working on Artificial Intelligence, Sociology and Political Science, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Molecular Biology, having authored 10 papers that have together received 49 indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (3 papers), Adversarial Robustness in Machine Learning (2 papers), Digital Games and Media (1 paper), Educational Games and Gamification (1 paper), Recommender Systems and Techniques (1 paper), Human Pose and Action Recognition (1 paper), RNA Interference and Gene Delivery (1 paper) and Privacy, Security, and Data Protection (1 paper). The work is most often cited by research in Artificial Intelligence (33 citations), Health Informatics (1 citation), Computer Science Applications (4 citations), Computer Vision and Pattern Recognition (10 citations) and Applied Psychology (2 citations). Mohammad Malekzadeh has collaborated with scholars based in United Kingdom, Iran and United States. Frequent co-authors include Anastasia Borovykh, Denız Gündüz, Fahim Kawsar, Ali Farhadi, Ali Shahin Shamsabadi, Dimitris Spathis, Flora D. Salim, Andrea Cavallaro, Seth Flaxman and Hamed Haddadi. Their work appears in journals such as Royal Society Open Science, Virology Journal, International Journal of Advanced Computer Science and Applications and arXiv (Cornell University).
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.