Ali Daud

138 papers receiving 3.2k citations

Ali Daud's Hit Papers

BERT applications in natural language processing: a review 2025 · 34 citations
340+1+3Years since publication200400600

Peers

Ali Daud
Comparison fields: 5 of 165
  • Computer Science Applications 329
  • Modeling and Simulation 182
  • Artificial Intelligence 1.1k
  • Information Systems 794
  • Statistical and Nonlinear Physics 396
Replace Daniel Zeng with:
Daniel Zeng China
Wagner Meira Brazil
Sune Lehmann Denmark
Hsinchun Chen United States
Peter Haddawy Thailand
Stefan Feuerriegel Germany
Aytuğ Onan Türkiye
Manuel Cebrián United States
Naif Radi Aljohani Saudi Arabia
Cécile Paris Australia
Ali Daud relative to Daniel Zeng China Daniel Zeng's profile →
Citations per field
00.5×3.1×
Daniel Zeng · 1×
Citations per year

Countries citing papers authored by Ali Daud

Since Specialization
Citations

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

Fields of papers citing papers by Ali Daud

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ali Daud, 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 Ali Daud Line = papers co-authored together Ali Daud links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 153 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Coronavirus Pandemic (COVID-19)
Hit paper breakdown →
2021652
2 2017157
3 2016127
4
Exploring the frontiers of deep learning and natural language processing: A comprehensive overview of key challenges and emerging trends
Hit paper breakdown →
2023106
5 2010102
6 201792
7 201767
8 201963
9 201463
10 201162
11 201862
12
Deep learning for lungs cancer detection: a review
Hit paper breakdown →
202460
13 201660
14 201758
15 201957
16
A survey on the state-of-the-art machine learning models in the context of NLP
201654
17 201847
18 202344
19 201542
20 201040

About Ali Daud

Ali Daud is a scholar working on Information Systems, Artificial Intelligence, Statistical and Nonlinear Physics, Computer Networks and Communications and Computer Science Applications, having authored 153 papers that have together received 3.4k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (30 papers), Topic Modeling (28 papers), Expert finding and Q&A systems (22 papers), IoT and Edge/Fog Computing (13 papers), Recommender Systems and Techniques (11 papers), Natural Language Processing Techniques (11 papers), scientometrics and bibliometrics research (11 papers) and Sentiment Analysis and Opinion Mining (10 papers). The work is most often cited by research in Computer Science Applications (329 citations), Modeling and Simulation (182 citations), Artificial Intelligence (1.1k citations), Information Systems (794 citations) and Statistical and Nonlinear Physics (396 citations). Ali Daud has collaborated with scholars based in Pakistan, Saudi Arabia and United Arab Emirates. Frequent co-authors include Jalal S. Alowibdi, Abdulrahman A. Alshdadi, Tehmina Amjad, Naif Radi Aljohani, Essa Alhazmi, Mohamed M. Dessouky, Rabeeh Ayaz Abbasi, Wahab Khan, Dunren Che and Hussain Dawood. Their work appears in journals such as IEEE Access, Scientometrics, Scientific Reports, Artificial Intelligence Review and International Journal on Semantic Web and Information Systems.

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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