Paramveer S. Dhillon

1.5k total citations
45 papers, 814 citations indexed

About

Paramveer S. Dhillon is a scholar working on Artificial Intelligence, Sociology and Political Science and Computer Vision and Pattern Recognition. According to data from OpenAlex, Paramveer S. Dhillon has authored 45 papers receiving a total of 814 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Artificial Intelligence, 7 papers in Sociology and Political Science and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in Paramveer S. Dhillon's work include Topic Modeling (7 papers), Natural Language Processing Techniques (6 papers) and Text and Document Classification Technologies (6 papers). Paramveer S. Dhillon is often cited by papers focused on Topic Modeling (7 papers), Natural Language Processing Techniques (6 papers) and Text and Document Classification Technologies (6 papers). Paramveer S. Dhillon collaborates with scholars based in United States, Israel and Germany. Paramveer S. Dhillon's co-authors include Lyle Ungar, Dean P. Foster, Sinan Aral, Yichao Lu, Dean Eckles, Christos Nicolaides, Christoph H. Lampert, Sebastian Nowozin, Dipayan Ghosh and Seth Benzell and has published in prestigious journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and NeuroImage.

In The Last Decade

Paramveer S. Dhillon

43 papers receiving 777 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Paramveer S. Dhillon United States 15 364 163 123 96 76 45 814
Lilian Berton Brazil 13 379 1.0× 90 0.6× 139 1.1× 88 0.9× 15 0.2× 51 682
Yukio Ohsawa Japan 16 851 2.3× 293 1.8× 94 0.8× 183 1.9× 13 0.2× 179 1.2k
Mustafa Mamat Malaysia 18 124 0.3× 265 1.6× 23 0.2× 513 5.3× 63 0.8× 55 865
Katarzyna Musiał Australia 20 738 2.0× 159 1.0× 137 1.1× 483 5.0× 40 0.5× 81 1.5k
Isabel Valera Germany 14 613 1.7× 77 0.5× 66 0.5× 69 0.7× 3 0.0× 39 945
Allan J. Rossman United States 14 160 0.4× 45 0.3× 28 0.2× 23 0.2× 19 0.3× 52 930
Hasan Rashaideh Jordan 8 178 0.5× 34 0.2× 35 0.3× 30 0.3× 77 1.0× 15 738
Zhesi Shen China 15 151 0.4× 18 0.1× 107 0.9× 553 5.8× 30 0.4× 41 981
Yuying Shi China 13 19 0.1× 132 0.8× 45 0.4× 144 1.5× 21 0.3× 51 833
Alessandro Rozza Italy 10 412 1.1× 184 1.1× 441 3.6× 298 3.1× 3 0.0× 22 1.3k

Countries citing papers authored by Paramveer S. Dhillon

Since Specialization
Citations

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

Fields of papers citing papers by Paramveer S. Dhillon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Paramveer S. Dhillon. 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 Paramveer S. Dhillon. The network helps show where Paramveer S. Dhillon may publish in the future.

Co-authorship network of co-authors of Paramveer S. Dhillon

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

All Works

20 of 20 papers shown
1.
Jiang, Julie, et al.. (2024). Characterizing the Structure of Online Conversations Across Reddit. Proceedings of the ACM on Human-Computer Interaction. 8(CSCW2). 1–23.
2.
Ma, Jiaqi, et al.. (2023). PM2.5 forecasting under distribution shift: A graph learning approach. SHILAP Revista de lepidopterología. 5. 23–29. 2 indexed citations
3.
Eckles, Dean, et al.. (2023). Targeting for Long-Term Outcomes. Management Science. 70(6). 3841–3855. 11 indexed citations
4.
Aral, Sinan & Paramveer S. Dhillon. (2022). What (Exactly) Is Novelty in Networks? Unpacking the Vision Advantages of Brokers, Bridges, and Weak Ties. Management Science. 69(2). 1092–1115. 19 indexed citations
5.
Aral, Sinan & Paramveer S. Dhillon. (2020). Digital Paywall Design: Implications for Content Demand and Subscriptions. Management Science. 67(4). 2381–2402. 29 indexed citations
6.
Holtz, David, Seth Benzell, M. Amin Rahimian, et al.. (2020). Interdependence and the cost of uncoordinated responses to COVID-19. Proceedings of the National Academy of Sciences. 117(33). 19837–19843. 121 indexed citations
7.
Aral, Sinan & Paramveer S. Dhillon. (2020). Digital Paywall Design: Implications for Content Demand & Subscriptions. SSRN Electronic Journal. 2 indexed citations
8.
Urban, Glen L., Artem Timoshenko, Paramveer S. Dhillon, & John R. Hauser. (2019). Is deep learning a game changer for marketing analytics. DSpace@MIT (Massachusetts Institute of Technology). 61(2). 70–76. 14 indexed citations
9.
Aral, Sinan & Paramveer S. Dhillon. (2018). Social influence maximization under empirical influence models. Nature Human Behaviour. 2(6). 375–382. 69 indexed citations
10.
Dhillon, Paramveer S., Dean P. Foster, & Lyle Ungar. (2015). Eigenwords: spectral word embeddings. Journal of Machine Learning Research. 16(1). 3035–3078. 43 indexed citations
11.
Dhillon, Paramveer S., Dean P. Foster, Sham M. Kakade, & Lyle Ungar. (2013). A risk comparison of ordinary least squares vs ridge regression. Journal of Machine Learning Research. 14(1). 1505–1511. 21 indexed citations
12.
Stoyanovich, Julia, Paramveer S. Dhillon, Susan B. Davidson, & Brian Lyons. (2013). Learning to explore scientific workflow repositories. 1–4. 1 indexed citations
13.
Dhillon, Paramveer S., S. Sathiya Keerthi, Kedar Bellare, Olivier Chapelle, & Sundararajan Sellamanickam. (2012). Deterministic Annealing for Semi-Supervised Structured Output Learning. International Conference on Artificial Intelligence and Statistics. 22. 299–307. 5 indexed citations
14.
Dhillon, Paramveer S., Partha Talukdar, & Koby Crammer. (2012). Metric Learning for Graph-Based Domain Adaptation. ScholarlyCommons (University of Pennsylvania). 255–264. 4 indexed citations
15.
Dhillon, Paramveer S., et al.. (2012). Using CCA to improve CCA: A new spectral method for estimating vector models of words.. International Conference on Machine Learning. 2 indexed citations
16.
Dhillon, Paramveer S., Dean P. Foster, & Lyle Ungar. (2011). Minimum Description Length Penalization for Group and Multi-Task Sparse Learning. Journal of Machine Learning Research. 12(16). 525–564. 13 indexed citations
17.
Dhillon, Paramveer S., Partha Talukdar, & Koby Crammer. (2010). Learning Better Data Representation Using Inference-Driven Metric Learning. Meeting of the Association for Computational Linguistics. 377–381. 7 indexed citations
18.
Dhillon, Paramveer S., Dean P. Foster, & Lyle Ungar. (2010). Feature Selection using Multiple Streams. International Conference on Artificial Intelligence and Statistics. 153–160. 6 indexed citations
19.
Dhillon, Paramveer S., et al.. (2008). Real- Time Monocular Face Tracking Using an Active Camera. 1 indexed citations
20.
Dhillon, Paramveer S., Dean P. Foster, & Lyle Ungar. (2008). Efficient Feature Selection in the Presence of Multiple Feature Classes. 779–784. 6 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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