Abir De

952 total citations
38 papers, 437 citations indexed

About

Abir De is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence and Transportation. According to data from OpenAlex, Abir De has authored 38 papers receiving a total of 437 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Statistical and Nonlinear Physics, 16 papers in Artificial Intelligence and 8 papers in Transportation. Recurrent topics in Abir De's work include Complex Network Analysis Techniques (17 papers), Opinion Dynamics and Social Influence (13 papers) and Advanced Graph Neural Networks (9 papers). Abir De is often cited by papers focused on Complex Network Analysis Techniques (17 papers), Opinion Dynamics and Social Influence (13 papers) and Advanced Graph Neural Networks (9 papers). Abir De collaborates with scholars based in India, Germany and United States. Abir De's co-authors include Niloy Ganguly, Manuel Gomez-Rodriguez, Sourangshu Bhattacharya, Soumen Chakrabarti, Utkarsh Upadhyay, Ali Zarezade, Bernhard Schölkopf, Behzad Tabibian, Parantapa Bhattacharya and Isabel Valera and has published in prestigious journals such as Proceedings of the National Academy of Sciences, PLoS Computational Biology and IEEE Transactions on Knowledge and Data Engineering.

In The Last Decade

Abir De

33 papers receiving 418 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Abir De India 12 175 170 51 46 35 38 437
P. K. Srijith India 9 128 0.7× 83 0.5× 57 1.1× 29 0.6× 13 0.4× 28 286
Luca Rossi United Kingdom 13 284 1.6× 83 0.5× 49 1.0× 130 2.8× 79 2.3× 38 502
Alexander Semenov United States 13 84 0.5× 93 0.5× 90 1.8× 22 0.5× 8 0.2× 73 434
Hao Yin United States 6 233 1.3× 350 2.1× 49 1.0× 74 1.6× 18 0.5× 12 516
Zhitao Wang China 14 230 1.3× 209 1.2× 137 2.7× 46 1.0× 61 1.7× 35 456
Gadi Aleksandrowicz Israel 5 211 1.2× 41 0.2× 63 1.2× 89 1.9× 9 0.3× 10 366

Countries citing papers authored by Abir De

Since Specialization
Citations

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

Fields of papers citing papers by Abir De

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Abir De. 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 Abir De. The network helps show where Abir De may publish in the future.

Co-authorship network of co-authors of Abir De

This figure shows the co-authorship network connecting the top 25 collaborators of Abir De. A scholar is included among the top collaborators of Abir De 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 Abir De. Abir De 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.
Chakrabarti, Soumen, et al.. (2025). Retrieval of Graph Structured Objects: Theory and Applications. 6841–6844.
2.
De, Abir, et al.. (2024). Generator Assisted Mixture of Experts for Feature Acquisition in Batch. Proceedings of the AAAI Conference on Artificial Intelligence. 38(10). 10927–10934.
3.
Bedathur, Srikanta, et al.. (2024). Retrieving Continuous-Time Event Sequences Using Neural Temporal Point Processes with Learnable Hashing. ACM Transactions on Intelligent Systems and Technology. 16(2). 1–23.
4.
Ranu, Sayan, et al.. (2023). Learning and Maximizing Influence in Social Networks Under Capacity Constraints. 733–741. 2 indexed citations
5.
De, Abir, et al.. (2022). Pooled testing of traced contacts under superspreading dynamics. PLoS Computational Biology. 18(3). e1010008–e1010008. 1 indexed citations
6.
Zhang, Ping, Rishabh Iyer, Ashish V. Tendulkar, Gaurav Aggarwal, & Abir De. (2021). Learning to Select Exogenous Events for Marked Temporal Point Process. Neural Information Processing Systems. 34. 1 indexed citations
7.
8.
De, Abir & Soumen Chakrabarti. (2021). Differentially Private Link Prediction with Protected Connections. Proceedings of the AAAI Conference on Artificial Intelligence. 35(1). 63–71. 7 indexed citations
9.
De, Abir, Paramita Koley, Niloy Ganguly, & Manuel Gomez-Rodriguez. (2020). Regression under Human Assistance. Proceedings of the AAAI Conference on Artificial Intelligence. 34(3). 2611–2620. 16 indexed citations
10.
Gupta, Utkarsh, et al.. (2020). Deep Neural Matching Models for Graph Retrieval. 1701–1704. 3 indexed citations
11.
Ganguly, Niloy, et al.. (2019). Learning Network Traffic Dynamics Using Temporal Point Process. 1927–1935. 15 indexed citations
12.
Zarezade, Ali, Abir De, Utkarsh Upadhyay, Hamid R. Rabiee, & Manuel Gomez-Rodriguez. (2018). Steering Social Activity: A Stochastic Optimal Control Point Of View. Journal of Machine Learning Research. 18(205). 1–35. 11 indexed citations
13.
Upadhyay, Utkarsh, Abir De, & Manuel Gomez-Rodriguez. (2018). Deep Reinforcement Learning of Marked Temporal Point Processes. MPG.PuRe (Max Planck Society). 31. 3168–3178. 35 indexed citations
14.
De, Abir, Sourangshu Bhattacharya, & Niloy Ganguly. (2018). Shaping Opinion Dynamics in Social Networks. Adaptive Agents and Multi-Agents Systems. 1336–1344. 1 indexed citations
15.
Ganguly, Niloy, et al.. (2018). CRPP. 537–546. 7 indexed citations
16.
De, Abir, et al.. (2017). SLANT+: A Nonlinear Model for Opinion Dynamics in Social Networks. 931–936. 10 indexed citations
17.
De, Abir, et al.. (2017). STRM: A sister tweet reinforcement process for modeling hashtag popularity. ii. 1–9. 8 indexed citations
18.
De, Abir, Isabel Valera, Niloy Ganguly, Sourangshu Bhattacharya, & Manuel Gomez-Rodriguez. (2016). Learning and Forecasting Opinion Dynamics in Social Networks. MPG.PuRe (Max Planck Society). 29. 397–405. 35 indexed citations
19.
De, Abir, Isabel Valera, Niloy Ganguly, Sourangshu Bhattacharya, & Manuel Gomez-Rodriguez. (2015). Learning Opinion Dynamics in Social Networks. 1 indexed citations
20.
De, Abir, Maunendra Sankar Desarkar, Niloy Ganguly, & Pabitra Mitra. (2012). Local learning of item dissimilarity using content and link structure. 221–224. 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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Breakdown of academic impact, for papers by P. K. Srijith Breakdown of academic impact, for papers by Luca Rossi Breakdown of academic impact, for papers by Alexander Semenov Breakdown of academic impact, for papers by Hao Yin Breakdown of academic impact, for papers by Zhitao Wang Breakdown of academic impact, for papers by Gadi Aleksandrowicz
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