Anastasios Kyrillidis

1.8k total citations · 1 hit paper
58 papers, 717 citations indexed

About

Anastasios Kyrillidis is a scholar working on Artificial Intelligence, Computational Mechanics and Computer Vision and Pattern Recognition. According to data from OpenAlex, Anastasios Kyrillidis has authored 58 papers receiving a total of 717 indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Artificial Intelligence, 27 papers in Computational Mechanics and 25 papers in Computer Vision and Pattern Recognition. Recurrent topics in Anastasios Kyrillidis's work include Sparse and Compressive Sensing Techniques (27 papers), Stochastic Gradient Optimization Techniques (9 papers) and Advanced Neural Network Applications (8 papers). Anastasios Kyrillidis is often cited by papers focused on Sparse and Compressive Sensing Techniques (27 papers), Stochastic Gradient Optimization Techniques (9 papers) and Advanced Neural Network Applications (8 papers). Anastasios Kyrillidis collaborates with scholars based in United States, Switzerland and Greece. Anastasios Kyrillidis's co-authors include Volkan Cevher, Nicholas D. Sidiropoulos, C. Wolfe, Chen Dun, Advait Balaji, Richard G. Baraniuk, Nicolae Sapoval, Ruth Dannenfelser, Zhi Yan and Stephen Becker and has published in prestigious journals such as Nature Communications, IEEE Transactions on Signal Processing and IEEE Transactions on Communications.

In The Last Decade

Anastasios Kyrillidis

53 papers receiving 691 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Current progress and open challenges for applying deep learning across the biosciences

2022 171 citations Nicolae Sapoval, Amirali Aghazadeh et al. Nature Communications profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Anastasios Kyrillidis United States	13	272	217	139	121	118	58	717
Penghang Yin United States	13	455 1.7×	166 0.8×	77 0.6×	276 2.3×	66 0.6×	29	843
Mátyás A. Sustik United States	7	233 0.9×	272 1.3×	63 0.5×	228 1.9×	125 1.1×	10	749
Aarti Singh United States	18	190 0.7×	436 2.0×	54 0.4×	141 1.2×	87 0.7×	66	947
Zhihua Zhang China	16	186 0.7×	460 2.1×	34 0.2×	267 2.2×	76 0.6×	80	981
Roummel F. Marcia United States	14	499 1.8×	91 0.4×	69 0.5×	221 1.8×	89 0.8×	94	895
Po‐Ling Loh United States	12	169 0.6×	214 1.0×	90 0.6×	57 0.5×	43 0.4×	36	703
Jeremias Sulam United States	15	161 0.6×	142 0.7×	282 2.0×	226 1.9×	63 0.5×	43	935
Adel Javanmard United States	13	219 0.8×	198 0.9×	48 0.3×	51 0.4×	119 1.0×	33	1.0k
Mihai Cucuringu United Kingdom	14	67 0.2×	100 0.5×	42 0.3×	57 0.5×	66 0.6×	68	568
Behnam Neyshabur United States	11	104 0.4×	346 1.6×	341 2.5×	230 1.9×	37 0.3×	17	867

Countries citing papers authored by Anastasios Kyrillidis

Since Specialization

Citations

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

Fields of papers citing papers by Anastasios Kyrillidis

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anastasios Kyrillidis

This figure shows the co-authorship network connecting the top 25 collaborators of Anastasios Kyrillidis. A scholar is included among the top collaborators of Anastasios Kyrillidis 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 Anastasios Kyrillidis. Anastasios Kyrillidis 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

Miller, Mitchell D., et al.. (2025). Completion of partial structures using Patterson maps with the CrysFormer machine-learning model. Acta Crystallographica Section D Structural Biology. 81(12). 668–677.

Paredes, Roger, Bhuvanesh Sundar, Anastasios Kyrillidis, et al.. (2024). Grover-QAOA for 3-SAT: quadratic speedup, fair-sampling, and parameter clustering. Quantum Science and Technology. 10(1). 15022–15022. 5 indexed citations

Wolfe, C. & Anastasios Kyrillidis. (2024). Better schedules for low precision training of deep neural networks. Machine Learning. 113(6). 3569–3587. 1 indexed citations

Wolfe, C., Jingkang Yang, Arindam Chowdhury, et al.. (2023). GIST: distributed training for large-scale graph convolutional networks. 8(5). 1363–1415. 5 indexed citations

Kyrillidis, Anastasios, et al.. (2023). Using non-convex optimization in quantum process tomography: Factored gradient descent is tough to beat. 1–10. 1 indexed citations

Sapoval, Nicolae, Amirali Aghazadeh, Michael Nute, et al.. (2022). Current progress and open challenges for applying deep learning across the biosciences. Nature Communications. 13(1). 1728–1728. 171 indexed citations breakdown →

Kyrillidis, Anastasios, et al.. (2021). Solving hybrid Boolean constraints in continuous space via multilinear Fourier expansions. Artificial Intelligence. 299. 103559–103559. 1 indexed citations

Chen, John, Samarth Sinha, & Anastasios Kyrillidis. (2021). ImCLR: Implicit Contrastive Learning for Image Classification. arXiv (Cornell University). 3 indexed citations

Quintero, Carlos, Anastasios Kyrillidis, & Lydia E. Kavraki. (2021). Robust Optimization-based Motion Planning for high-DOF Robots under Sensing Uncertainty. 9724–9730. 6 indexed citations

10.

Chen, John, et al.. (2020). Negative Sampling in Semi-Supervised learning. International Conference on Machine Learning. 1. 1704–1714. 2 indexed citations

11.

Kyrillidis, Anastasios, et al.. (2020). Low-rank regularization and solution uniqueness in over-parameterized matrix sensing.. International Conference on Artificial Intelligence and Statistics. 930–940. 2 indexed citations

12.

Chen, John & Anastasios Kyrillidis. (2019). Decaying momentum helps neural network training. arXiv (Cornell University). 3 indexed citations

13.

Kyrillidis, Anastasios, et al.. (2019). Compressing Gradient Optimizers via Count-Sketches. International Conference on Machine Learning. 5946–5955. 1 indexed citations

14.

Kyrillidis, Anastasios. (2018). Simple and practical algorithms for 𝓁 p -norm low-rank approximation.. Uncertainty in Artificial Intelligence. 414–424. 1 indexed citations

15.

Khanna, Rajiv & Anastasios Kyrillidis. (2018). IHT dies hard: Provable accelerated Iterative Hard Thresholding. International Conference on Artificial Intelligence and Statistics. 188–198. 8 indexed citations

16.

Kyrillidis, Anastasios, et al.. (2018). Minimum norm solutions do not always generalize well for over-parameterized problems. arXiv (Cornell University). 3 indexed citations

17.

Kyrillidis, Anastasios, Amir Kalev, Dohyung Park, et al.. (2018). Provable compressed sensing quantum state tomography via non-convex methods. npj Quantum Information. 4(1). 33 indexed citations

18.

Kyrillidis, Anastasios, et al.. (2016). Learning Sparse Additive Models with Interactions in High Dimensions. International Conference on Artificial Intelligence and Statistics. 111–120. 2 indexed citations

19.

Asteris, Megasthenis, Dimitris Papailiopoulos, Anastasios Kyrillidis, & Alexandros G. Dimakis. (2015). Sparse PCA via bipartite matchings. Neural Information Processing Systems. 28. 766–774. 3 indexed citations

20.

Baldassarre, Luca, et al.. (2013). Tractability of Interpretability via Selection of Group-Sparse Models. arXiv (Cornell University). 2 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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