Amir F. Atiya

11.9k total citations · 9 hit papers
130 papers, 8.0k citations indexed

About

Amir F. Atiya is a scholar working on Artificial Intelligence, Control and Systems Engineering and Management Science and Operations Research. According to data from OpenAlex, Amir F. Atiya has authored 130 papers receiving a total of 8.0k indexed citations (citations by other indexed papers that have themselves been cited), including 74 papers in Artificial Intelligence, 26 papers in Control and Systems Engineering and 24 papers in Management Science and Operations Research. Recurrent topics in Amir F. Atiya's work include Neural Networks and Applications (41 papers), Fault Detection and Control Systems (21 papers) and Forecasting Techniques and Applications (13 papers). Amir F. Atiya is often cited by papers focused on Neural Networks and Applications (41 papers), Fault Detection and Control Systems (21 papers) and Forecasting Techniques and Applications (13 papers). Amir F. Atiya collaborates with scholars based in Egypt, United States and Australia. Amir F. Atiya's co-authors include A.G. Parlos, Abbas Khosravi, Saeid Nahavandi, Dina Elreedy, Hisham El‐Shishiny, Pierre Baldi, Yaser S. Abu‐Mostafa, Souhaib Ben Taieb, Hatem A. Fayed and Mohamed Aly and has published in prestigious journals such as SHILAP Revista de lepidopterología, European Journal of Operational Research and IEEE Transactions on Image Processing.

In The Last Decade

Amir F. Atiya

125 papers receiving 7.6k citations

Hit Papers

5 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.

Lower Upper Bound Estimation Method for Construction of Neural Network-Based Prediction Intervals

2010 564 citations Abbas Khosravi, Saeid Nahavandi et al. IEEE Transactions on Neural Networks profile →
An Empirical Comparison of Machine Learning Models for Time Series Forecasting

2010 506 citations Amir F. Atiya et al. profile →
Comprehensive Review of Neural Network-Based Prediction Intervals and New Advances

2011 471 citations Abbas Khosravi, Saeid Nahavandi et al. IEEE Transactions on Neural Networks profile →
A review and comparison of strategies for multi-step ahead time series forecasting based on the NN5 forecasting competition

2012 467 citations Amir F. Atiya et al. profile →
A Comprehensive Analysis of Synthetic Minority Oversampling Technique (SMOTE) for handling class imbalance

2019 422 citations Dina Elreedy, Amir F. Atiya Information Sciences profile →
Learning with kernels : Support vector machines, regularization, optimization, and beyond

2005 398 citations Amir F. Atiya IEEE Transactions on Neural Networks profile →
Epileptic Seizures Detection Using Deep Learning Techniques: A Review

2021 263 citations Afshin Shoeibi, Marjane Khodatars et al. profile →
ASTD: Arabic Sentiment Tweets Dataset

2015 260 citations Mahmoud Nabil, Mohamed Aly et al. profile →
A theoretical distribution analysis of synthetic minority oversampling technique (SMOTE) for imbalanced learning

2023 142 citations Dina Elreedy, Amir F. Atiya et al. Machine Learning profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Amir F. Atiya Egypt	37	3.4k	1.8k	1.5k	873	677	130	8.0k
Felix A. Gers Switzerland	10	2.4k 0.7×	1.1k 0.6×	532 0.4×	503 0.6×	822 1.2×	21	6.3k
Pãnos M. Pardalos United States	60	2.7k 0.8×	1.7k 0.9×	1.3k 0.9×	2.0k 2.3×	604 0.9×	516	15.0k
Shie Mannor Israel	42	3.9k 1.2×	1.7k 0.9×	1.6k 1.1×	950 1.1×	707 1.0×	252	8.7k
Abbas Khosravi Australia	64	5.3k 1.6×	4.8k 2.6×	1.3k 0.9×	1.9k 2.2×	498 0.7×	351	14.8k
Thomas Bäck Netherlands	39	6.4k 1.9×	1.1k 0.6×	800 0.5×	1.1k 1.3×	395 0.6×	315	12.3k
Javier Del Ser Spain	47	6.6k 2.0×	1.6k 0.9×	597 0.4×	1.2k 1.4×	632 0.9×	314	14.9k
José A. Lozano Spain	45	4.4k 1.3×	687 0.4×	550 0.4×	730 0.8×	786 1.2×	292	10.4k
Paul J. Werbos United States	26	5.9k 1.7×	1.9k 1.1×	511 0.3×	2.8k 3.2×	901 1.3×	79	10.7k
Bart Kosko United States	40	8.2k 2.4×	1.2k 0.6×	2.0k 1.3×	1.6k 1.8×	496 0.7×	119	12.0k
William G. Macready United States	19	6.2k 1.9×	1.3k 0.7×	702 0.5×	951 1.1×	256 0.4×	35	10.6k

Countries citing papers authored by Amir F. Atiya

Since Specialization

Citations

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

Fields of papers citing papers by Amir F. Atiya

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Amir F. Atiya. 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 Amir F. Atiya. The network helps show where Amir F. Atiya may publish in the future.

Co-authorship network of co-authors of Amir F. Atiya

This figure shows the co-authorship network connecting the top 25 collaborators of Amir F. Atiya. A scholar is included among the top collaborators of Amir F. Atiya 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 Amir F. Atiya. Amir F. Atiya 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:

20 of 20 papers shown

Kamalov, Firuz, et al.. (2025). Analytical formulation of synthetic minority oversampling technique (SMOTE) for imbalanced learning. Gulf Journal of Mathematics. 19(1). 400–415. 2 indexed citations

Elreedy, Dina, Amir F. Atiya, & Firuz Kamalov. (2023). A theoretical distribution analysis of synthetic minority oversampling technique (SMOTE) for imbalanced learning. Machine Learning. 113(7). 4903–4923. 142 indexed citations breakdown →

Shoeibi, Afshin, Navid Ghassemi, Marjane Khodatars, et al.. (2020). Epileptic seizure detection using deep learning techniques: A Review. arXiv (Cornell University). 24 indexed citations

Elreedy, Dina & Amir F. Atiya. (2019). A Comprehensive Analysis of Synthetic Minority Oversampling Technique (SMOTE) for handling class imbalance. Information Sciences. 505. 32–64. 422 indexed citations breakdown →

Nabil, Mahmoud, Mohamed Aly, & Amir F. Atiya. (2015). ASTD: Arabic Sentiment Tweets Dataset. 2515–2519. 260 indexed citations breakdown →

Nabil, Mahmoud, Mohamed Aly, & Amir F. Atiya. (2014). LABR: A Large Scale Arabic Book Reviews Dataset. arXiv (Cornell University). 7 indexed citations

Atiya, Amir F., et al.. (2009). Symbolic function network. Neural Networks. 22(4). 395–404. 1 indexed citations

Atiya, Amir F. & S. D. Wall. (2009). An analytic approximation of the likelihood function for the Heston model volatility estimation problem. Quantitative Finance. 9(3). 289–296. 5 indexed citations

Hefny, Ahmed, et al.. (2008). Cerberus: Applying Supervised and Reinforcement Learning Techniques to Capture the Flag Games. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 4(1). 179–184. 6 indexed citations

10.

Atiya, Amir F.. (2005). Learning with kernels : Support vector machines, regularization, optimization, and beyond. IEEE Transactions on Neural Networks. 16(3). 781. 398 indexed citations breakdown →

11.

Atiya, Amir F., et al.. (2003). Lowering frame-buffering requirements of 3-D wavelet transform coding of interactive video. 3. 852–856. 2 indexed citations

12.

Magdon‐Ismail, Malik & Amir F. Atiya. (1998). Neural Networks for Density Estimation. CaltechAUTHORS (California Institute of Technology). 11. 522–528. 11 indexed citations

13.

Abu‐Mostafa, Yaser S. & Amir F. Atiya. (1996). Introduction to financial forecasting. Applied Intelligence. 6(3). 205–213. 281 indexed citations

14.

Atiya, Amir F. & A.G. Parlos. (1995). Identification of nonlinear dynamics using a general spatio-temporal network. Mathematical and Computer Modelling. 21(1-2). 53–71. 6 indexed citations

15.

Parlos, A.G., et al.. (1994). Incipient Fault Detection and Identification in Process Systems Using Accelerated Neural Network Learning. Nuclear Technology. 105(2). 145–161. 32 indexed citations

16.

Parlos, A.G., M. Jayakumar, & Amir F. Atiya. (1992). Early detection of incipient faults in power plants using accelerated neural network learning. Transactions of the American Nuclear Society. 66. 3 indexed citations

17.

Parlos, A.G., Amir F. Atiya, & Kil To Chong. (1991). Dynamic gradient descent learning algorithms for enhanced empirical modeling of power plants. Transactions of the American Nuclear Society. 64(1). 1–8. 1 indexed citations

18.

Atiya, Amir F. & Yaser S. Abu‐Mostafa. (1989). A Method for the Associative Storage of Analog Vectors. CaltechAUTHORS (California Institute of Technology). 2. 590–595. 6 indexed citations

19.

Bower, James M. & Amir F. Atiya. (1987). Optimal Neural Spike Classification. Neural Information Processing Systems. 95–102. 1 indexed citations

20.

Atiya, Amir F.. (1987). Learning on a General Network. CaltechAUTHORS (California Institute of Technology). 22–30. 32 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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