Niloy Mukherjee
- Computer Networks and Communications top 10%
- Artificial Intelligence top 10%
- Industrial and Manufacturing Engineering top 5%
- Information Systems top 10%
- Signal Processing
- Co-authors
- Deb RoySubhash C. SarinMing ChengMohamed ZaïtDinesh DasJesse KampPeter GorniakTirthankar Lahiri
- Topics
- Scheduling and Optimization Algorithms (5 papers)Advanced Manufacturing and Logistics Optimization (5 papers)Cloud Computing and Resource Management (5 papers)
- Cited by
- Industrial and Manufacturing EngineeringComputer Networks and CommunicationsSignal Processing
- Journals
- Journal of the Operational Research SocietyInternational Journal of Production ResearchProceedings of the VLDB Endowment
- Partner nations
- United StatesIndiaSwitzerland
In The Last Decade
Niloy Mukherjee
20 papers receiving 293 citations
Peers
Comparison fields: 5 of 38
- Computer Networks and Communications 139
- Artificial Intelligence 102
- Industrial and Manufacturing Engineering 88
- Information Systems 61
- Signal Processing 41
Countries citing papers authored by Niloy Mukherjee
This map shows the geographic impact of Niloy Mukherjee'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 Niloy Mukherjee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Niloy Mukherjee more than expected).
Fields of papers citing papers by Niloy Mukherjee
This network shows the impact of papers produced by Niloy Mukherjee. 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 Niloy Mukherjee. The network helps show where Niloy Mukherjee may publish in the future.
Co-authorship network of co-authors of Niloy Mukherjee
This figure shows the co-authorship network connecting the top 25 collaborators of Niloy Mukherjee. A scholar is included among the top collaborators of Niloy Mukherjee 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 Niloy Mukherjee. Niloy Mukherjee is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 6 | |
| 3 | 7 | |
| 4 | 4 | |
| 5 | 11 | |
| 6 | 5 | |
| 7 | 13 | |
| 8 | 18 | |
| 9 | 70 | |
| 10 | 1 | |
| 11 | 20 | |
| 12 | 1 | |
| 13 | 4 | |
| 14 | 68 | |
| 15 | 9 | |
| 16 | 7 | |
| 17 | 49 | |
| 18 | 6 | |
| 19 | 25 | |
| 20 | 5 |
About Niloy Mukherjee
Niloy Mukherjee is a scholar working on Industrial and Manufacturing Engineering, Computer Networks and Communications and Signal Processing, having authored 21 papers that have together received 332 indexed citations. Recurring topics across this work include Scheduling and Optimization Algorithms (5 papers), Advanced Manufacturing and Logistics Optimization (5 papers) and Cloud Computing and Resource Management (5 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (88 citations), Computer Networks and Communications (139 citations) and Signal Processing (41 citations). Niloy Mukherjee has collaborated with scholars based in United States, India and Switzerland. Frequent co-authors include Deb Roy, Subhash C. Sarin, Ming Cheng, Mohamed Zaït, Dinesh Das, Jesse Kamp, Peter Gorniak, Tirthankar Lahiri, Sivaji Bandyopadhyay and Braja Gopal Patra. Their work appears in journals such as Journal of the Operational Research Society, International Journal of Production Research and Proceedings of the VLDB Endowment.
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.