Mohammed Alawad

880 total citations
49 papers, 564 citations indexed

About

Mohammed Alawad is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering and Molecular Biology. According to data from OpenAlex, Mohammed Alawad has authored 49 papers receiving a total of 564 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Artificial Intelligence, 14 papers in Electrical and Electronic Engineering and 9 papers in Molecular Biology. Recurrent topics in Mohammed Alawad's work include Topic Modeling (14 papers), Biomedical Text Mining and Ontologies (8 papers) and Advanced Memory and Neural Computing (7 papers). Mohammed Alawad is often cited by papers focused on Topic Modeling (14 papers), Biomedical Text Mining and Ontologies (8 papers) and Advanced Memory and Neural Computing (7 papers). Mohammed Alawad collaborates with scholars based in United States, Iraq and Saudi Arabia. Mohammed Alawad's co-authors include Mingjie Lin, Georgia D. Tourassi, Hong‐Jun Yoon, Shang Gao, Xiao‐Cheng Wu, Linda Coyle, Eric B. Durbin, Lynne Penberthy, Jennifer A. Doherty and Antoinette M. Stroup and has published in prestigious journals such as PLoS ONE, BMC Bioinformatics and Journal of the American Medical Informatics Association.

In The Last Decade

Mohammed Alawad

42 papers receiving 546 citations

Peers

Mohammed Alawad

RNMI

EEE

CVPR

Mariam Zomorodi‐Moghadam Iran

Ali Haider Khan Pakistan

Liming Wang China

Bilal Mirza Singapore

Xiaofeng Qi China

C. Paul Bonnington New Zealand

Naveed Abbas Pakistan

Chao Che China

Shiva Toumaj Iran

Eswaran Perumal India

Mariam Zomorodi‐Moghadam Iran

Mohammed Alawad

512 ×1.5

90 ×0.8

128 ×1.4

RNMI

58 ×0.6

EEE

55 ×1.1

CVPR

Citations per year, relative to Mohammed Alawad Mohammed Alawad (= 1×) peers Mariam Zomorodi‐Moghadam

Countries citing papers authored by Mohammed Alawad

Since Specialization

Citations

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

Fields of papers citing papers by Mohammed Alawad

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mohammed Alawad

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

Alawad, Mohammed, et al.. (2025). Energy-Efficient Probabilistic Bayesian Neural Networks for Resource-Constrained Environments. ACM Journal on Emerging Technologies in Computing Systems. 22(1). 1–21.

Ahmed, Waleed, et al.. (2024). Re-Evaluating Deep Learning Attacks and Defenses in Cybersecurity Systems. Big Data and Cognitive Computing. 8(12). 191–191. 2 indexed citations

Alawad, Mohammed, et al.. (2024). Optimizing Federated Learning with Heterogeneous Edge Devices. 1–5. 1 indexed citations

Yuan, J.S., et al.. (2024). Impacting Robustness in Deep Learning-Based NIDS through Poisoning Attacks. Algorithms. 17(4). 155–155. 3 indexed citations

Alawad, Mohammed, et al.. (2024). Probabilistic Bayesian Neural Networks for Efficient Inference. 724–729. 1 indexed citations

Alawad, Mohammed, et al.. (2023). Node Selection in Federated Learning Using Sparsity Regularization and Compressive Sensing. 1319–1323. 2 indexed citations

Alawad, Mohammed, et al.. (2023). Stochastically Pruning Large Language Models Using Sparsity Regularization and Compressive Sensing. 63–68. 3 indexed citations

Alawad, Mohammed, et al.. (2022). Machine Learning and Deep Learning Techniques for Optic Disc and Cup Segmentation &ndash; A Review. Dove Medical Press (Taylor and Francis Group). 21 indexed citations

Alawad, Mohammed, et al.. (2022). Peripapillary atrophy classification using CNN deep learning for glaucoma screening. PLoS ONE. 17(10). e0275446–e0275446. 6 indexed citations

10.

Alawad, Mohammed, et al.. (2022). Towards Adversarial Attacks for Clinical Document Classification. Electronics. 12(1). 129–129. 6 indexed citations

11.

Bokhari, Yahya, Mohammed Alawad, Ebrahim Mahmoud, et al.. (2021). Early Prediction of COVID-19 Ventilation Requirement and Mortality from Routinely Collected Baseline Chest Radiographs, Laboratory, and Clinical Data with Machine Learning. Journal of Multidisciplinary Healthcare. Volume 14. 2017–2033. 23 indexed citations

12.

Gao, Shang, Mohammed Alawad, Hong‐Jun Yoon, et al.. (2021). Deep active learning for classifying cancer pathology reports. BMC Bioinformatics. 22(1). 113–113. 25 indexed citations

13.

Gao, Shang, Mohammed Alawad, M. Todd Young, et al.. (2021). Limitations of Transformers on Clinical Text Classification. IEEE Journal of Biomedical and Health Informatics. 25(9). 3596–3607. 104 indexed citations

14.

Klasky, Hilda, John Gounley, Mohammed Alawad, et al.. (2020). Accelerated training of bootstrap aggregation-based deep information extraction systems from cancer pathology reports. Journal of Biomedical Informatics. 110. 103564–103564. 10 indexed citations

15.

Alawad, Mohammed, Hong‐Jun Yoon, Shang Gao, et al.. (2020). Privacy-Preserving Deep Learning NLP Models for Cancer Registries. IEEE Transactions on Emerging Topics in Computing. 9(3). 1219–1230. 31 indexed citations

16.

Gao, Shang, Mohammed Alawad, Lynne Penberthy, et al.. (2020). Using case-level context to classify cancer pathology reports. PLoS ONE. 15(5). e0232840–e0232840. 15 indexed citations

17.

Shash, Ali A. & Mohammed Alawad. (2020). Modern Construction Methods (MMC) in Saudi Arabia: Evaluation Aspects and Barriers. 8(2). 4 indexed citations

18.

Alawad, Mohammed, Shang Gao, John X. Qiu, et al.. (2019). Deep Transfer Learning Across Cancer Registries for Information Extraction from Pathology Reports. PubMed. 2019. 1–4. 15 indexed citations

19.

Gao, Shang, John X. Qiu, Mohammed Alawad, et al.. (2019). Classifying cancer pathology reports with hierarchical self-attention networks. Artificial Intelligence in Medicine. 101. 101726–101726. 40 indexed citations

20.

Alawad, Mohammed, Ronald F. DeMara, & Mingjie Lin. (2015). Stochastically Estimating Modular Criticality in Large-Scale Logic Circuits Using Sparsity Regularization and Compressive Sensing. Journal of Low Power Electronics and Applications. 5(1). 3–37. 3 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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