Prem Gopalan
Impact in
- Computational Mathematics top 5%
-
- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
Papers in
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- Complex Network Analysis Techniques 4
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- Bayesian Methods and Mixture Models 4
- Co-authors
- David M. BleiLaurent CharlinJake M. HofmanMichael J. FreedmanErik NordströmDavid ShueSteven Y. KoJennifer Rexford
- Journals
- Nature Genetics (1 paper)Proceedings of the National Academy of Sciences (1 paper)Computer Networks (1 paper)Networked Systems Design and Implementation (1 paper)Purdue e-Pubs (Purdue University System) (1 paper)
- Partner nations
- United StatesHong KongSpain
In The Last Decade
Prem Gopalan
12 papers receiving 593 citations
Peers
Comparison fields: 5 of 59
- Computational Mathematics 18
- Statistical and Nonlinear Physics 197
- Information Systems 189
- Artificial Intelligence 270
- Transportation 56
Countries citing papers authored by Prem Gopalan
This map shows the geographic impact of Prem Gopalan'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 Prem Gopalan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Prem Gopalan more than expected).
Fields of papers citing papers by Prem Gopalan
This network shows the impact of papers produced by Prem Gopalan. 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 Prem Gopalan. The network helps show where Prem Gopalan may publish in the future.
Co-authorship network
The 24 scholars most cited alongside Prem Gopalan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 30 | |
| 2 | Scalable recommendation with hierarchical Poisson factorization | 2015 | 107 |
| 3 | Bayesian Nonparametric Poisson Factorization for Recommendation Systems | 2014 | 42 |
| 4 | Content-based recommendations with Poisson factorization | 2014 | 107 |
| 5 | Modeling Overlapping Communities with Node Popularities | 2013 | 11 |
| 6 | Efficient Online Inference for Bayesian Nonparametric Relational Models | 2013 | 7 |
| 7 | 2013 | 174 | |
| 8 | Serval: an end-host stack for service-centric networking | 2012 | 107 |
| 9 | Scalable Inference of Overlapping Communities | 2012 | 50 |
| 10 | 2006 | 4 | |
| 11 | 2005 | 1 | |
| 12 | Application Performance on the CROSS/ Linux Software Programmable Router | 2001 | 3 |
About Prem Gopalan
Prem Gopalan is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence, Computer Networks and Communications, Statistics and Probability and Cognitive Neuroscience, having authored 12 papers that have together received 643 indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (4 papers), Complex Network Analysis Techniques (4 papers), Software-Defined Networks and 5G (3 papers), Network Traffic and Congestion Control (3 papers), Caching and Content Delivery (2 papers), Functional Brain Connectivity Studies (2 papers), Recommender Systems and Techniques (2 papers) and Advanced Malware Detection Techniques (1 paper). The work is most often cited by research in Computational Mathematics (18 citations), Statistical and Nonlinear Physics (197 citations), Information Systems (189 citations), Artificial Intelligence (270 citations) and Transportation (56 citations). Prem Gopalan has collaborated with scholars based in United States, Hong Kong and Spain. Frequent co-authors include David M. Blei, Laurent Charlin, Jake M. Hofman, Michael J. Freedman, Erik Nordström, David Shue, Steven Y. Ko, Jennifer Rexford, Matvey Arye and Francisco J. R. Ruiz. Their work appears in journals such as Nature Genetics, Proceedings of the National Academy of Sciences, Computer Networks, Networked Systems Design and Implementation and Purdue e-Pubs (Purdue University System).
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.