Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Countries citing papers authored by Sumudu Samarakoon
Since
Specialization
Citations
This map shows the geographic impact of Sumudu Samarakoon'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 Sumudu Samarakoon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sumudu Samarakoon more than expected).
Fields of papers citing papers by Sumudu Samarakoon
This network shows the impact of papers produced by Sumudu Samarakoon. 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 Sumudu Samarakoon. The network helps show where Sumudu Samarakoon may publish in the future.
Co-authorship network of co-authors of Sumudu Samarakoon
This figure shows the co-authorship network connecting the top 25 collaborators of Sumudu Samarakoon.
A scholar is included among the top collaborators of Sumudu Samarakoon 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 Sumudu Samarakoon. Sumudu Samarakoon is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Samarakoon, Sumudu, et al.. (2021). Joint client scheduling and resource allocation under channel uncertainty in federated learning. University of Oulu Repository (University of Oulu).46 indexed citations
3.
Samarakoon, Sumudu, et al.. (2021). Network slicing for vehicular communication. University of Oulu Repository (University of Oulu).29 indexed citations
4.
Issaid, Chaouki Ben, Sumudu Samarakoon, Mehdi Bennis, & H. Vincent Poor. (2021). Federated distributionally robust optimization for phase configuration of RISs. University of Oulu Repository (University of Oulu).3 indexed citations
5.
Samarakoon, Sumudu, Jihong Park, & Mehdi Bennis. (2021). Robust reconfigurable intelligent surfaces via invariant risk and causal representations. University of Oulu Repository (University of Oulu).4 indexed citations
6.
Park, Jihong, Sumudu Samarakoon, Anis Elgabli, et al.. (2021). Communication-efficient and distributed learning over wireless networks:principles and applications. University of Oulu Repository (University of Oulu).156 indexed citations
7.
Samarakoon, Sumudu, et al.. (2021). BayGo:joint Bayesian learning and information-aware graph optimization. University of Oulu Repository (University of Oulu).4 indexed citations
8.
Hsu, Yung-Lin, Chen–Feng Liu, Sumudu Samarakoon, Hung‐Yu Wei, & Mehdi Bennis. (2021). Age-optimal power allocation in industrial IoT:a risk-sensitive federated learning approach. University of Oulu Repository (University of Oulu).6 indexed citations
Alexandropoulos, George C., Sumudu Samarakoon, Mehdi Bennis, & Mérouane Debbah. (2020). Phase configuration learning in wireless networks with multiple reconfigurable intelligent surfaces. University of Oulu Repository (University of Oulu).41 indexed citations
11.
Samarakoon, Sumudu, et al.. (2020). Federated learning under channel uncertainty:joint client scheduling and resource allocation. University of Oulu Repository (University of Oulu).51 indexed citations
12.
Samarakoon, Sumudu, et al.. (2020). Enhancing video streaming in vehicular networks via resource slicing. University of Oulu Repository (University of Oulu).38 indexed citations
13.
Butt, M. Majid, et al.. (2020). Deep learning assisted CSI estimation for joint URLLC and eMBB resource allocation. University of Oulu Repository (University of Oulu).17 indexed citations
14.
Abdel-Aziz, Mohamed K., Chen–Feng Liu, Sumudu Samarakoon, Mehdi Bennis, & Walid Saad. (2019). Ultra-reliable low-latency vehicular networks:taming the age of information tail. University of Oulu Repository (University of Oulu).43 indexed citations
15.
Elgabli, Anis, et al.. (2019). Reinforcement learning based vehicle-cell association algorithm for highly mobile millimeter wave communication. University of Oulu Repository (University of Oulu).11 indexed citations
Elbamby, Mohammed S., Cristina Perfecto, Chen–Feng Liu, et al.. (2019). Wireless edge computing with latency and reliability guarantees. University of Oulu Repository (University of Oulu).115 indexed citations
18.
Liu, Chen–Feng, Sumudu Samarakoon, Mehdi Bennis, & H. Vincent Poor. (2018). Fronthaul-aware software-defined wireless networks:resource allocation and user scheduling. University of Oulu Repository (University of Oulu).15 indexed citations
19.
Bennis, Mehdi, et al.. (2017). Joint load balancing and interference mitigation in 5G heterogeneous networks. University of Oulu Repository (University of Oulu).55 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.