Laha Ale
Impact in
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- IoT and Edge/Fog Computing
- Caching and Content Delivery
- Opportunistic and Delay-Tolerant Networks
- Age of Information Optimization
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- Advanced Neural Network Applications
Papers in
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- IoT and Edge/Fog Computing 10
- Age of Information Optimization 3
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- Advanced Neural Network Applications 4
- Context-Aware Activity Recognition Systems 1
- Co-authors
- Ning Zhang (10 shared papers)Longzhuang Li (3 shared papers)Dajiang Chen (3 shared papers)Tao Han (1 shared paper)Huici Wu (1 shared paper)Scott A. King (5 shared papers)Alaa Sheta (1 shared paper)Ye Wang (1 shared paper)
- Journals
- IEEE Internet of Things Journal (6 papers)ACM Transactions on Internet Technology (1 paper)Vehicle System Dynamics (1 paper)IEEE Transactions on Vehicular Technology (1 paper)Database (1 paper)
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Laha Ale
16 papers receiving 463 citations
Peers
Comparison fields: 5 of 81
- Computer Networks and Communications 193
- Computer Vision and Pattern Recognition 96
- Information Systems 59
- Civil and Structural Engineering 54
- Artificial Intelligence 75
Countries citing papers authored by Laha Ale
This map shows the geographic impact of Laha Ale'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 Laha Ale with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Laha Ale more than expected).
Fields of papers citing papers by Laha Ale
This network shows the impact of papers produced by Laha Ale. 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 Laha Ale. The network helps show where Laha Ale may publish in the future.
Co-authors
The 25 scholars most cited alongside Laha Ale, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 158 | |
| 2 | 2018 | 81 | |
| 3 | 2019 | 66 | |
| 4 | 2022 | 56 | |
| 5 | 2024 | 25 | |
| 6 | 2024 | 18 | |
| 7 | 2024 | 17 | |
| 8 | 2021 | 16 | |
| 9 | 2019 | 11 | |
| 10 | 2024 | 7 | |
| 11 | 2025 | 5 | |
| 12 | 2020 | 4 | |
| 13 | 2025 | 3 | |
| 14 | 2025 | 2 | |
| 15 | 2025 | 2 | |
| 16 | 2021 | 2 | |
| 17 | 2025 | 0 | |
| 18 | 2026 | 0 |
About Laha Ale
Laha Ale is a scholar working on Computer Networks and Communications, Computer Vision and Pattern Recognition, Aerospace Engineering, Information Systems and Artificial Intelligence, having authored 18 papers that have together received 473 indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (10 papers), Advanced Neural Network Applications (4 papers), Age of Information Optimization (3 papers), UAV Applications and Optimization (3 papers), Transportation and Mobility Innovations (1 paper), Cognitive Computing and Networks (1 paper), Infrastructure Maintenance and Monitoring (1 paper) and Context-Aware Activity Recognition Systems (1 paper). The work is most often cited by research in Computer Networks and Communications (193 citations), Computer Vision and Pattern Recognition (96 citations), Information Systems (59 citations), Civil and Structural Engineering (54 citations) and Artificial Intelligence (75 citations). Laha Ale has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Ning Zhang, Longzhuang Li, Dajiang Chen, Tao Han, Huici Wu, Scott A. King, Alaa Sheta, Ye Wang, Robert Gentleman and Deepayan Sarkar. Their work appears in journals such as IEEE Internet of Things Journal, ACM Transactions on Internet Technology, Vehicle System Dynamics, IEEE Transactions on Vehicular Technology and Database.
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.