Sajad Mousavi

1.4k total citations · 1 hit paper
17 papers, 587 citations indexed

About

Sajad Mousavi is a scholar working on Artificial Intelligence, Cardiology and Cardiovascular Medicine and Computer Networks and Communications. According to data from OpenAlex, Sajad Mousavi has authored 17 papers receiving a total of 587 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 5 papers in Cardiology and Cardiovascular Medicine and 4 papers in Computer Networks and Communications. Recurrent topics in Sajad Mousavi's work include Adversarial Robustness in Machine Learning (5 papers), ECG Monitoring and Analysis (4 papers) and EEG and Brain-Computer Interfaces (3 papers). Sajad Mousavi is often cited by papers focused on Adversarial Robustness in Machine Learning (5 papers), ECG Monitoring and Analysis (4 papers) and EEG and Brain-Computer Interfaces (3 papers). Sajad Mousavi collaborates with scholars based in United States, Malaysia and Singapore. Sajad Mousavi's co-authors include Fatemeh Afghah, U. Rajendra Acharya, Jonathan Ashdown, Aliya G. Feroe, Alba Gutiérrez‐Sacristán, Nishant Uppal, Isaac S. Kohane, Paul Avillach, Ashwin Ramesh Babu and Antonio Guillén and has published in prestigious journals such as PLoS ONE, Computer Networks and JAMA Pediatrics.

In The Last Decade

Sajad Mousavi

14 papers receiving 572 citations

Hit Papers

align trajectories sort by overperformance

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.

SleepEEGNet: Automated sleep stage scoring with sequence to sequence deep learning approach

2019 334 citations Sajad Mousavi, Fatemeh Afghah et al. PLoS ONE profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Sajad Mousavi United States	7	425	182	113	101	84	17	587
Takashi Nakamura United Kingdom	10	334 0.8×	93 0.5×	86 0.8×	70 0.7×	189 2.3×	19	534
Binish Fatimah India	10	233 0.5×	195 1.1×	36 0.3×	58 0.6×	163 1.9×	27	554
Khaldon Lweesy Jordan	8	412 1.0×	92 0.5×	104 0.9×	74 0.7×	145 1.7×	25	619
Ankit A. Bhurane India	10	252 0.6×	104 0.6×	81 0.7×	52 0.5×	61 0.7×	38	452
Haitham M. Al-Angari United Arab Emirates	11	189 0.4×	268 1.5×	57 0.5×	153 1.5×	265 3.2×	20	702
Nicola Michielli Italy	6	249 0.6×	59 0.3×	92 0.8×	51 0.5×	68 0.8×	12	445
Remo Mueller United States	5	410 1.0×	116 0.6×	285 2.5×	378 3.7×	150 1.8×	8	823
Daniel Mobley United States	6	425 1.0×	115 0.6×	292 2.6×	411 4.1×	154 1.8×	8	811
Arnab Bhattacharjee Bangladesh	11	167 0.4×	106 0.6×	65 0.6×	88 0.9×	81 1.0×	21	359
Farideh Ebrahimi Iran	10	442 1.0×	104 0.6×	77 0.7×	48 0.5×	144 1.7×	18	588

Countries citing papers authored by Sajad Mousavi

Since Specialization

Citations

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

Fields of papers citing papers by Sajad Mousavi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sajad Mousavi

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

All Works

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17 of 17 papers shown

Babu, Ashwin Ramesh, et al.. (2025). Reinforcement Learning Platform for Adversarial Black-box Attacks with Custom Distortion Filters. Proceedings of the AAAI Conference on Artificial Intelligence. 39(26). 27628–27635.

Mousavi, Sajad, et al.. (2024). Joint path planning and power allocation of a cellular-connected UAV using apprenticeship learning via deep inverse reinforcement learning. Computer Networks. 254. 110789–110789. 7 indexed citations

Guillén, Antonio, et al.. (2024). Sustainability of Data Center Digital Twins with Reinforcement Learning. Proceedings of the AAAI Conference on Artificial Intelligence. 38(21). 23832–23834. 3 indexed citations

Gutiérrez‐Sacristán, Alba, Audrey Dionne, Faridis Serrano, et al.. (2024). Development and validation of an open-source pipeline for automatic population of case report forms from electronic health records: a pediatric multi-center prospective study. EBioMedicine. 108. 105337–105337.

Guillén, Antonio, et al.. (2024). Carbon Footprint Reduction for Sustainable Data Centers in Real-Time. Proceedings of the AAAI Conference on Artificial Intelligence. 38(20). 22322–22330. 5 indexed citations

Babu, Ashwin Ramesh, et al.. (2024). Robustness and Visual Explanation for Black Box Image, Video, and ECG Signal Classification with Reinforcement Learning. Proceedings of the AAAI Conference on Artificial Intelligence. 38(21). 23829–23831. 1 indexed citations

Bash, Cullen, et al.. (2024). SustainDC: Benchmarking for Sustainable Data Center Control. 100630–100669.

Guillén, Antonio, et al.. (2023). Concurrent Carbon Footprint Reduction (C2FR) Reinforcement Learning Approach for Sustainable Data Center Digital Twin. 1–8. 1 indexed citations

Babu, Ashwin Ramesh, et al.. (2023). Reinforcement Learning Based Black-Box Adversarial Attack for Robustness Improvement. 1–8. 1 indexed citations

10.

Babu, Ashwin Ramesh, et al.. (2023). Robustness with Query-efficient Adversarial Attack using Reinforcement Learning. 2330–2337. 5 indexed citations

11.

Babu, Ashwin Ramesh, et al.. (2023). RL-CAM: Visual Explanations for Convolutional Networks using Reinforcement Learning. 3861–3869. 6 indexed citations

12.

Feroe, Aliya G., Nishant Uppal, Alba Gutiérrez‐Sacristán, et al.. (2021). Medication Use in the Management of Comorbidities Among Individuals With Autism Spectrum Disorder From a Large Nationwide Insurance Database. JAMA Pediatrics. 175(9). 957–957. 31 indexed citations

13.

Mousavi, Sajad, et al.. (2020). Single-modal and multi-modal false arrhythmia alarm reduction using attention-based convolutional and recurrent neural networks. PLoS ONE. 15(1). e0226990–e0226990. 26 indexed citations

14.

Mousavi, Sajad, et al.. (2020). An Uncertainty Estimation Framework for Risk Assessment in Deep Learning-based AFib Classification. 960–964. 4 indexed citations

15.

Mousavi, Sajad, Fatemeh Afghah, & U. Rajendra Acharya. (2019). SleepEEGNet: Automated sleep stage scoring with sequence to sequence deep learning approach. PLoS ONE. 14(5). e0216456–e0216456. 334 indexed citations breakdown →

16.

Mousavi, Sajad & Fatemeh Afghah. (2019). Inter- and Intra- Patient ECG Heartbeat Classification for Arrhythmia Detection: A Sequence to Sequence Deep Learning Approach. PubMed. 2019. 1308–1312. 116 indexed citations

17.

Mousavi, Sajad, et al.. (2018). Use of a quantum genetic algorithm for coalition formation in large-scale UAV networks. Ad Hoc Networks. 87. 26–36. 47 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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