Muhammad Ehatisham-ul-Haq

1.7k total citations
46 papers, 1.2k citations indexed

About

Muhammad Ehatisham-ul-Haq is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Muhammad Ehatisham-ul-Haq has authored 46 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Computer Vision and Pattern Recognition, 10 papers in Artificial Intelligence and 9 papers in Computer Networks and Communications. Recurrent topics in Muhammad Ehatisham-ul-Haq's work include Context-Aware Activity Recognition Systems (21 papers), IoT and Edge/Fog Computing (9 papers) and Chaos-based Image/Signal Encryption (7 papers). Muhammad Ehatisham-ul-Haq is often cited by papers focused on Context-Aware Activity Recognition Systems (21 papers), IoT and Edge/Fog Computing (9 papers) and Chaos-based Image/Signal Encryption (7 papers). Muhammad Ehatisham-ul-Haq collaborates with scholars based in Pakistan, United Kingdom and Saudi Arabia. Muhammad Ehatisham-ul-Haq's co-authors include Muhammad Awais Azam, Usman Naeem, Yasar Amin, Faisal Hussain, Fawad Hussain, Nasir Siddiqui, Jonathan Loo, Asra Khalid, Fawad Fawad and Ik Hyun Lee and has published in prestigious journals such as PLoS ONE, Scientific Reports and Expert Systems with Applications.

In The Last Decade

Muhammad Ehatisham-ul-Haq

45 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Muhammad Ehatisham-ul-Haq Pakistan 19 767 359 271 206 172 46 1.2k
Bogdan Ionescu Romania 21 1.1k 1.4× 403 1.1× 157 0.6× 149 0.7× 222 1.3× 180 1.7k
Mohammad I. Daoud Jordan 20 257 0.3× 261 0.7× 265 1.0× 230 1.1× 101 0.6× 82 1.3k
P. Karthigaikumar India 16 381 0.5× 286 0.8× 138 0.5× 81 0.4× 104 0.6× 60 948
Aston Zhang United States 16 547 0.7× 550 1.5× 105 0.4× 182 0.9× 184 1.1× 33 1.2k
Le T. Nguyen United States 12 641 0.8× 368 1.0× 254 0.9× 91 0.4× 166 1.0× 22 1.1k
Dat Tran Australia 17 288 0.4× 474 1.3× 78 0.3× 276 1.3× 341 2.0× 153 1.2k
Amr Elchouemi United States 13 248 0.3× 234 0.7× 125 0.5× 133 0.6× 69 0.4× 80 935
Sung Bum Pan South Korea 15 304 0.4× 131 0.4× 222 0.8× 95 0.5× 267 1.6× 94 875
Yunhao Liu China 16 369 0.5× 288 0.8× 121 0.4× 74 0.4× 121 0.7× 45 1.2k
Uma Shanker Tiwary India 17 348 0.5× 197 0.5× 140 0.5× 53 0.3× 83 0.5× 73 1.1k

Countries citing papers authored by Muhammad Ehatisham-ul-Haq

Since Specialization
Citations

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

Fields of papers citing papers by Muhammad Ehatisham-ul-Haq

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Muhammad Ehatisham-ul-Haq. 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 Muhammad Ehatisham-ul-Haq. The network helps show where Muhammad Ehatisham-ul-Haq may publish in the future.

Co-authorship network of co-authors of Muhammad Ehatisham-ul-Haq

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

All Works

20 of 20 papers shown
1.
Hassan, Ch Anwar Ul, et al.. (2025). EmoTrans attention based emotion recognition using EEG signals and facial analysis with expert validation. Scientific Reports. 15(1). 22004–22004.
2.
Arsalan, Aamir, et al.. (2024). A Novel Framework for Daily Life Activity and Context Recognition In-The-Wild Using Smartphone Inertial Sensors. IEEE Access. 12. 175176–175195. 2 indexed citations
3.
4.
Arsalan, Aamir, et al.. (2023). Motorbike Driving Activity Recognition Using Smartphone Motion Sensors. 1–6. 1 indexed citations
5.
6.
Ehatisham-ul-Haq, Muhammad, Fiza Murtaza, Muhammad Awais Azam, & Yasar Amin. (2022). Daily Living Activity Recognition In-The-Wild: Modeling and Inferring Activity-Aware Human Contexts. Electronics. 11(2). 226–226. 14 indexed citations
7.
Hannan, Abdul, Faisal Hussain, Muhammad Ehatisham-ul-Haq, et al.. (2021). A decentralized hybrid computing consumer authentication framework for a reliable drone delivery as a service. PLoS ONE. 16(4). e0250737–e0250737. 9 indexed citations
8.
Fatima, Bushra, et al.. (2021). Gender Recognition using EEG during Mobile Game Play. 634–639. 3 indexed citations
9.
Ehatisham-ul-Haq, Muhammad, Muhammad Awais Azam, Fiza Murtaza, Yasar Amin, & Qiang Fu. (2021). S-THAD: a framework for sensor-based temporal human activity detection from continuous data streams. Journal of Ambient Intelligence and Humanized Computing. 13(2). 1037–1051. 1 indexed citations
10.
Ehatisham-ul-Haq, Muhammad, et al.. (2020). Recognizing Human-Object Interaction (HOI) Using Wrist-Mounted Inertial Sensors. IEEE Sensors Journal. 21(6). 7899–7907. 4 indexed citations
11.
Ehatisham-ul-Haq, Muhammad, Muhammad Awais Azam, Yasar Amin, & Usman Naeem. (2020). C2FHAR: Coarse-to-Fine Human Activity Recognition With Behavioral Context Modeling Using Smart Inertial Sensors. IEEE Access. 8. 7731–7747. 23 indexed citations
12.
Siddiqui, Nasir, Fiza Murtaza, Muhammad Ehatisham-ul-Haq, et al.. (2020). A highly nonlinear substitution-box (S-box) design using action of modular group on a projective line over a finite field. PLoS ONE. 15(11). e0241890–e0241890. 58 indexed citations
13.
Ehatisham-ul-Haq, Muhammad, et al.. (2020). REALME: An Approach for Handwritten Signature Verification based on Smart Wrist Sensor. 1–6. 2 indexed citations
14.
Ehatisham-ul-Haq, Muhammad, et al.. (2020). Object based Human-Object Interaction (HOI) Recognition using Wrist-mounted Sensors. 1–6. 6 indexed citations
15.
Ehatisham-ul-Haq, Muhammad, Abdul Hannan, Muhammad Asif Khan, et al.. (2020). Inferring Emotion Tags from Object Images Using Convolutional Neural Network. Applied Sciences. 10(15). 5333–5333. 5 indexed citations
16.
Siddiqui, Nasir, et al.. (2020). An Approach towards Position-Independent Human Activity Recognition Model based on Wearable Accelerometer Sensor. Procedia Computer Science. 177. 196–203. 12 indexed citations
17.
Hussain, Faisal, Fawad Hussain, Muhammad Ehatisham-ul-Haq, & Muhammad Awais Azam. (2019). Activity-Aware Fall Detection and Recognition Based on Wearable Sensors. IEEE Sensors Journal. 19(12). 4528–4536. 137 indexed citations
18.
Ehatisham-ul-Haq, Muhammad, Ali Javed, Muhammad Awais Azam, et al.. (2019). Robust Human Activity Recognition Using Multimodal Feature-Level Fusion. IEEE Access. 7. 60736–60751. 123 indexed citations
19.
Hussain, Faisal, Muhammad Ehatisham-ul-Haq, Muhammad Awais Azam, & Asra Khalid. (2018). Elderly Assistance Using Wearable Sensors by Detecting Fall and Recognizing Fall Patterns. 770–777. 16 indexed citations
20.
Ehatisham-ul-Haq, Muhammad, Muhammad Awais Azam, Jonathan Loo, et al.. (2017). Authentication of Smartphone Users Based on Activity Recognition and Mobile Sensing. Sensors. 17(9). 2043–2043. 88 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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