Abhishek Chandra
- Computer Networks and Communications top 0.5%
- Information Systems top 0.2%
- Artificial Intelligence top 5%
- Hardware and Architecture top 2%
- Electrical and Electronic Engineering
- Co-authors
- Prashant ShenoyJon WeissmanPawan GoyalBhuvan UrgaonkarWeibo GongTimothy WoodKwangsung OhRamesh K. Sitaraman
- Topics
- Cloud Computing and Resource Management (58 papers)Caching and Content Delivery (32 papers)IoT and Edge/Fog Computing (28 papers)
- Partner nations
- United StatesIndiaSouth Korea
In The Last Decade
Abhishek Chandra
105 papers receiving 2.4k citations
Hit Papers
Peers
Comparison fields: 5 of 78
- Computer Networks and Communications 2.2k
- Information Systems 1.8k
- Artificial Intelligence 338
- Hardware and Architecture 297
- Electrical and Electronic Engineering 196
Countries citing papers authored by Abhishek Chandra
This map shows the geographic impact of Abhishek Chandra'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 Abhishek Chandra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Abhishek Chandra more than expected).
Fields of papers citing papers by Abhishek Chandra
This network shows the impact of papers produced by Abhishek Chandra. 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 Abhishek Chandra. The network helps show where Abhishek Chandra may publish in the future.
Co-authorship network of co-authors of Abhishek Chandra
This figure shows the co-authorship network connecting the top 25 collaborators of Abhishek Chandra. A scholar is included among the top collaborators of Abhishek Chandra 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 Abhishek Chandra. Abhishek Chandra is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 7 | |
| 4 | 10 | |
| 5 | 6 | |
| 6 | 4 | |
| 7 | Dlion: Decentralized distributed deep learning in micro-clouds | 10 |
| 8 | 9 | |
| 9 | 33 | |
| 10 | 5 | |
| 11 | 36 | |
| 12 | 20 | |
| 13 | Enabling scalable social group analytics via hypergraph analysis systems | 2 |
| 14 | 5 | |
| 15 | 2 | |
| 16 | Virtual putty | 1 |
| 17 | Nebulas: using distributed voluntary resources to build clouds | 49 |
| 18 | PSS: Predictive Energy-Efficient Sensing Scheduling in Wireless Sensor Networks | 3 |
| 19 | 90 | |
| 20 | Scalability of Linux Event-Dispatch Mechanisms | 24 |
About Abhishek Chandra
Abhishek Chandra is a scholar working on Computer Networks and Communications, Information Systems and Hardware and Architecture, having authored 107 papers that have together received 2.6k indexed citations. Recurring topics across this work include Cloud Computing and Resource Management (58 papers), Caching and Content Delivery (32 papers) and IoT and Edge/Fog Computing (28 papers). The work is most often cited by research in Computer Networks and Communications (2.2k citations), Information Systems (1.8k citations) and Hardware and Architecture (297 citations). Abhishek Chandra has collaborated with scholars based in United States, India and South Korea. Frequent co-authors include Prashant Shenoy, Jon Weissman, Pawan Goyal, Bhuvan Urgaonkar, Weibo Gong, Timothy Wood, Kwangsung Oh, Ramesh K. Sitaraman, Michael Cardosa and Micah Adler. Their work appears in journals such as IEEE Transactions on Computers, Surgery and Surgical Endoscopy.
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.