Yunseong Lee
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- IoT and Edge/Fog Computing 8
- Mobile Ad Hoc Networks 4
- Opportunistic and Delay-Tolerant Networks 3
- Energy Efficient Wireless Sensor Networks 3
- Information Systems top 5%
- Cloud Computing and Resource Management 6
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- Advanced Wireless Communication Technologies 4
- Advanced Memory and Neural Computing 3
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- Parallel Computing and Optimization Techniques 3
- Co-authors
- Sungrae ChoNhu‐Ngoc DaoByung-Gon ChunWoongsoo NaChul LeeBrian ChoZhengping QianHyunbum Kim
- Cited by
- Computer Networks and CommunicationsInformation SystemsIndustrial and Manufacturing Engineering
- Journals
- IEEE Access (1 paper)IEEE Internet of Things Journal (2 papers)Future Generation Computer Systems (1 paper)
- Partner nations
- South KoreaUnited StatesItaly
In The Last Decade
Yunseong Lee
30 papers receiving 305 citations
Peers
Comparison fields: 5 of 43
- Computer Networks and Communications 190
- Information Systems 128
- Industrial and Manufacturing Engineering 24
- Electrical and Electronic Engineering 127
- Artificial Intelligence 48
Countries citing papers authored by Yunseong Lee
This map shows the geographic impact of Yunseong Lee'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 Yunseong Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yunseong Lee more than expected).
Fields of papers citing papers by Yunseong Lee
This network shows the impact of papers produced by Yunseong Lee. 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 Yunseong Lee. The network helps show where Yunseong Lee may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Yunseong Lee, 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 | 2025 | 1 | |
| 2 | 2025 | 2 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 2 | |
| 5 | 2024 | 10 | |
| 6 | 2023 | 5 | |
| 7 | 2022 | 11 | |
| 8 | 2021 | 3 | |
| 9 | 2021 | 10 | |
| 10 | 2020 | 18 | |
| 11 | 2020 | 16 | |
| 12 | 2019 | 6 | |
| 13 | 2018 | 26 | |
| 14 | 2018 | 21 | |
| 15 | 2018 | 32 | |
| 16 | Towards High-Performance Prediction Serving Systems | 2017 | 2 |
| 17 | Elastic memory: bring elasticity back to in-memory big data analytics | 2015 | 4 |
| 18 | 2015 | 8 | |
| 19 | 2015 | 11 | |
| 20 | 2014 | 4 |
About Yunseong Lee
Yunseong Lee is a scholar working on Computer Networks and Communications, Information Systems and Hardware and Architecture, having authored 31 papers that have together received 318 indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (8 papers), Cloud Computing and Resource Management (6 papers), Mobile Ad Hoc Networks (4 papers), Advanced Wireless Communication Technologies (4 papers), Advanced Memory and Neural Computing (3 papers), Parallel Computing and Optimization Techniques (3 papers), Opportunistic and Delay-Tolerant Networks (3 papers) and Energy Efficient Wireless Sensor Networks (3 papers). The work is most often cited by research in Computer Networks and Communications (190 citations), Information Systems (128 citations) and Industrial and Manufacturing Engineering (24 citations). Yunseong Lee has collaborated with scholars based in South Korea, United States and Italy. Frequent co-authors include Sungrae Cho, Nhu‐Ngoc Dao, Byung-Gon Chun, Woongsoo Na, Chul Lee, Brian Cho, Zhengping Qian, Hyunbum Kim, Wonjong Noh and Chihyun Cho. Their work appears in journals such as IEEE Access, IEEE Internet of Things Journal and Future Generation Computer 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.