Akshay Narayan

749 total citations
15 papers, 508 citations indexed

About

Akshay Narayan is a scholar working on Information Systems, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, Akshay Narayan has authored 15 papers receiving a total of 508 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Information Systems, 7 papers in Computer Networks and Communications and 4 papers in Artificial Intelligence. Recurrent topics in Akshay Narayan's work include Cloud Computing and Resource Management (5 papers), Reinforcement Learning in Robotics (4 papers) and Software-Defined Networks and 5G (3 papers). Akshay Narayan is often cited by papers focused on Cloud Computing and Resource Management (5 papers), Reinforcement Learning in Robotics (4 papers) and Software-Defined Networks and 5G (3 papers). Akshay Narayan collaborates with scholars based in Singapore, United States and India. Akshay Narayan's co-authors include Rachit Agarwal, Sylvia Ratnasamy, Scott Shenker, Peter Gao, Gautam Kumar, João Carreira, Sagar Karandikar, Sangjin Han, Shrisha Rao and Prateek Saxena and has published in prestigious journals such as IEEE Systems Journal, IEEE Transactions on Services Computing and DSpace@MIT (Massachusetts Institute of Technology).

In The Last Decade

Akshay Narayan

14 papers receiving 488 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Akshay Narayan Singapore 10 420 375 71 70 58 15 508
Miika Komu Finland 9 391 0.9× 255 0.7× 46 0.6× 115 1.6× 65 1.1× 39 459
Mark Huang United States 7 624 1.5× 202 0.5× 52 0.7× 113 1.6× 86 1.5× 7 650
Yury Audzevich United Kingdom 7 553 1.3× 287 0.8× 168 2.4× 145 2.1× 66 1.1× 12 616
Shun-Sheng Wang Taiwan 9 405 1.0× 281 0.7× 41 0.6× 41 0.6× 50 0.9× 27 442
Timothy Zhu United States 10 427 1.0× 374 1.0× 72 1.0× 28 0.4× 50 0.9× 20 472
Andrew D. Ferguson United States 7 586 1.4× 294 0.8× 73 1.0× 82 1.2× 99 1.7× 8 608
Steve Muir United States 8 534 1.3× 155 0.4× 97 1.4× 47 0.7× 84 1.4× 16 568
Omid Alipourfard United States 8 522 1.2× 222 0.6× 117 1.6× 87 1.2× 133 2.3× 8 570
Thanh Do Norway 10 462 1.1× 275 0.7× 62 0.9× 72 1.0× 73 1.3× 30 524
Nanxi Kang United States 7 601 1.4× 163 0.4× 137 1.9× 142 2.0× 107 1.8× 9 639

Countries citing papers authored by Akshay Narayan

Since Specialization
Citations

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

Fields of papers citing papers by Akshay Narayan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Akshay Narayan

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

All Works

15 of 15 papers shown
1.
Narayan, Akshay, Bimlesh Wadhwa, Nigel CK Tan, & Min Soo Choo. (2024). Integrating AI in Software Engineering Teaching and Learning. 1–7.
2.
Narayan, Akshay & Tze-Yun Leong. (2019). Effects of Task Similarity on Policy Transfer with Selective Exploration in Reinforcement Learning. Adaptive Agents and Multi-Agents Systems. 2132–2134. 1 indexed citations
3.
Mao, Hongzi, Parimarjan Negi, Akshay Narayan, et al.. (2019). Park: An Open Platform for Learning-Augmented Computer Systems. DSpace@MIT (Massachusetts Institute of Technology). 32. 2490–2502. 39 indexed citations
4.
Narayan, Akshay, et al.. (2018). Sincronia. 16–29. 68 indexed citations
5.
Li, Zhuoru, Akshay Narayan, & Tze-Yun Leong. (2017). An Efficient Approach to Model-Based Hierarchical Reinforcement Learning. Proceedings of the AAAI Conference on Artificial Intelligence. 31(1). 10 indexed citations
6.
Narayan, Akshay, Zhuoru Li, & Tze-Yun Leong. (2017). SEAPoT-RL: Selective Exploration Algorithm for Policy Transfer in RL. Proceedings of the AAAI Conference on Artificial Intelligence. 31(1). 1 indexed citations
7.
Gao, Peter, Akshay Narayan, Sagar Karandikar, et al.. (2016). Network requirements for resource disaggregation. 249–264. 154 indexed citations
8.
Gao, Peter, Akshay Narayan, Gautam Kumar, et al.. (2015). pHost. 1–12. 144 indexed citations
9.
Rao, Shrisha, et al.. (2014). System of Systems for Quality-of-Service Observation and Response in Cloud Computing Environments. IEEE Systems Journal. 9(1). 212–222. 15 indexed citations
10.
Narayan, Akshay & Shrisha Rao. (2013). Power-Aware Cloud Metering. IEEE Transactions on Services Computing. 7(3). 440–451. 18 indexed citations
11.
Narayan, Akshay & Prateek Saxena. (2013). The curse of 140 characters. 33–42. 26 indexed citations
12.
Sarkar, Santonu, et al.. (2012). Analysis of SaaS Business Platform Workloads for Sizing and Collocation. 868–875. 10 indexed citations
14.
Narayan, Akshay, et al.. (2012). Smart metering of cloud services. 1–7. 13 indexed citations
15.
Narayan, Akshay, et al.. (2012). ISOSURFACE EXTRACTION FROM HYBRID UNSTRUCTURED GRIDS CONTAINING PENTAHEDRAL ELEMENTS. 660–669. 2 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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