Alexander Robey

640 citations
14 papers · 82 · 1 hit paper · h-index 6

Impact in

Papers in

Alexander Robey

13 papers receiving 77 citations

Alexander Robey's Hit Papers

Jailbreaking Black Box Large Language Models in Twenty Queries 2025 · 24 citations
240Years since publication5101520

Peers

Alexander Robey
Comparison fields: 5 of 46
  • Artificial Intelligence 39
  • Acoustics and Ultrasonics 1
  • Radiation 8
  • Health Informatics 1
  • Structural Biology 1
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Majid Janzamin United States
Chao Chang China
Seiya Tokui Japan
Kofi P. Adragni United States
Qiyang Han United States
N. V. Tran United States
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Yonathan Efroni Israel
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Citations per field
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Citations per year

Countries citing papers authored by Alexander Robey

Since Specialization
Citations

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

Fields of papers citing papers by Alexander Robey

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Alexander Robey, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Alexander Robey Line = papers co-authored together Alexander Robey links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1
Jailbreaking Black Box Large Language Models in Twenty Queries
Hit paper breakdown →
202524
2 201816
3 202410
4
Model-Based Robust Deep Learning.
20208
5
Optimal Algorithms for Submodular Maximization with Distributed Constraints
20216
6 20235
7 20234
8 20222
9 20242
10 20252
11
Learning Hybrid Control Barrier Functions from Data
20201
12 20021
13 20261
14 20210

About Alexander Robey

Alexander Robey is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Control and Systems Engineering, Atomic and Molecular Physics, and Optics and Signal Processing, having authored 14 papers that have together received 82 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (6 papers), Anomaly Detection Techniques and Applications (4 papers), Machine Learning and Algorithms (3 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Advanced Malware Detection Techniques (2 papers), Advanced Control Systems Optimization (1 paper), Color Science and Applications (1 paper) and Optical measurement and interference techniques (1 paper). The work is most often cited by research in Artificial Intelligence (39 citations), Acoustics and Ultrasonics (1 citation), Radiation (8 citations), Health Informatics (1 citation) and Structural Biology (1 citation). Alexander Robey has collaborated with scholars based in United States and Australia. Frequent co-authors include Hamed Hassani, George J. Pappas, Vidya Ganapati, Edgar Dobriban, Eric Wong, Lars Lindemann, Nikolai Matni, Stephen Tu, Clark Barrett and Corina S. Păsăreanu. Their work appears in journals such as IEEE Transactions on Information Theory, Optics Express, IEEE Robotics and Automation Letters, 2022 IEEE 61st Conference on Decision and Control (CDC) and Deakin Research Online (Deakin 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.

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