Manish Purohit
- Computer Networks and Communications top 10%
- Artificial Intelligence
- Statistical and Nonlinear Physics
- Information Systems
- Computer Vision and Pattern Recognition
- Co-authors
- Samir KhullerV. S. SubrahmanianB. Aditya PrakashSungjin ImRavi KumarRami PuzisGaurav GuptaIndu Pal Kaur
- Topics
- Optimization and Search Problems (7 papers)Complexity and Algorithms in Graphs (5 papers)Advanced Bandit Algorithms Research (4 papers)
- Cited by
- Computational MathematicsComputer Networks and CommunicationsStatistical and Nonlinear Physics
- Partner nations
- United StatesIndiaAustralia
In The Last Decade
Manish Purohit
24 papers receiving 173 citations
Peers
Comparison fields: 5 of 77
- Computer Networks and Communications 68
- Artificial Intelligence 39
- Statistical and Nonlinear Physics 35
- Information Systems 24
- Computer Vision and Pattern Recognition 24
Countries citing papers authored by Manish Purohit
This map shows the geographic impact of Manish Purohit'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 Manish Purohit with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Manish Purohit more than expected).
Fields of papers citing papers by Manish Purohit
This network shows the impact of papers produced by Manish Purohit. 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 Manish Purohit. The network helps show where Manish Purohit may publish in the future.
Co-authorship network of co-authors of Manish Purohit
This figure shows the co-authorship network connecting the top 25 collaborators of Manish Purohit. A scholar is included among the top collaborators of Manish Purohit 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 Manish Purohit. Manish Purohit is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 38 | |
| 2 | 2 | |
| 3 | Online Knapsack with Frequency Predictions | 5 |
| 4 | Dynamic Balancing for Model Selection in Bandits and RL | 1 |
| 5 | 1 | |
| 6 | 12 | |
| 7 | Online Learning with Imperfect Hints | 4 |
| 8 | Matroid Coflow Scheduling. | 2 |
| 9 | Efficient Rematerialization for Deep Networks | 9 |
| 10 | 3 | |
| 11 | 7 | |
| 12 | Mobile Communication: A Survey from 4G to 5G | 0 |
| 13 | 0 | |
| 14 | 1 | |
| 15 | 15 | |
| 16 | 41 | |
| 17 | 8 | |
| 18 | 4 | |
| 19 | 1 | |
| 20 | 1 |
About Manish Purohit
Manish Purohit is a scholar working on Computer Networks and Communications, Management Science and Operations Research and Industrial and Manufacturing Engineering, having authored 27 papers that have together received 177 indexed citations. Recurring topics across this work include Optimization and Search Problems (7 papers), Complexity and Algorithms in Graphs (5 papers) and Advanced Bandit Algorithms Research (4 papers). The work is most often cited by research in Computational Mathematics (2 citations), Computer Networks and Communications (68 citations) and Statistical and Nonlinear Physics (35 citations). Manish Purohit has collaborated with scholars based in United States, India and Australia. Frequent co-authors include Samir Khuller, V. S. Subrahmanian, B. Aditya Prakash, Sungjin Im, Ravi Kumar, Rami Puzis, Gaurav Gupta, Indu Pal Kaur, Sachin Kumar Singh and Waleed Hassan Almalki. Their work appears in journals such as IEEE Communications Magazine, Chemico-Biological Interactions and Theoretical Computer Science.
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.