Kushal Chakrabarti

2.3k total citations
15 papers, 40 citations indexed

About

Kushal Chakrabarti is a scholar working on Artificial Intelligence, Computational Mechanics and Computer Networks and Communications. According to data from OpenAlex, Kushal Chakrabarti has authored 15 papers receiving a total of 40 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 6 papers in Computational Mechanics and 4 papers in Computer Networks and Communications. Recurrent topics in Kushal Chakrabarti's work include Stochastic Gradient Optimization Techniques (8 papers), Sparse and Compressive Sensing Techniques (6 papers) and Machine Learning and ELM (3 papers). Kushal Chakrabarti is often cited by papers focused on Stochastic Gradient Optimization Techniques (8 papers), Sparse and Compressive Sensing Techniques (6 papers) and Machine Learning and ELM (3 papers). Kushal Chakrabarti collaborates with scholars based in United States, India and Switzerland. Kushal Chakrabarti's co-authors include Nikhil Chopra, Lior Pachter, Nirupam Gupta, Amrit Singh Bedi, Fikadu T. Dagefu and Jeffrey N. Twigg and has published in prestigious journals such as Automatica, Genome Research and IEEE Transactions on Control of Network Systems.

In The Last Decade

Kushal Chakrabarti

14 papers receiving 39 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kushal Chakrabarti United States 4 13 10 7 7 5 15 40
Simon Bartels Denmark 2 6 0.5× 24 2.4× 3 0.4× 2 0.3× 6 1.2× 4 48
Junyuan Lin United States 4 7 0.5× 4 0.4× 4 0.6× 7 1.0× 2 0.4× 10 32
S. P. Wen China 4 9 0.7× 10 1.0× 1 0.1× 5 0.7× 5 1.0× 13 42
X. H. Sun China 4 7 0.5× 4 0.4× 2 0.3× 5 1.0× 12 66
M. Lucio Martínez United States 1 10 0.8× 8 0.8× 3 0.4× 2 0.3× 2 28
Afroz Mohiuddin United States 3 6 0.5× 26 2.6× 3 0.4× 3 0.6× 3 35
Sahand Sharifzadeh Germany 6 5 0.4× 39 3.9× 2 0.3× 6 0.9× 1 0.2× 11 83
Z. Gao China 3 3 0.2× 15 1.5× 3 0.4× 11 2.2× 8 44

Countries citing papers authored by Kushal Chakrabarti

Since Specialization
Citations

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

Fields of papers citing papers by Kushal Chakrabarti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kushal Chakrabarti

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

All Works

15 of 15 papers shown
1.
Chakrabarti, Kushal & Nikhil Chopra. (2024). On Convergence of the Iteratively Preconditioned Gradient-Descent (IPG) Observer. IEEE Control Systems Letters. 8. 1715–1720. 2 indexed citations
2.
Chakrabarti, Kushal & Nikhil Chopra. (2023). A control theoretic framework for adaptive gradient optimizers. Automatica. 160. 111466–111466. 2 indexed citations
3.
4.
Chakrabarti, Kushal, et al.. (2023). Iteratively Preconditioned Gradient-Descent Approach for Moving Horizon Estimation Problems. 8457–8462. 1 indexed citations
5.
Chakrabarti, Kushal & Nikhil Chopra. (2023). IPG Observer: A Newton-Type Observer Robust to Measurement Noise. 3069–3074. 4 indexed citations
6.
Chakrabarti, Kushal & Nikhil Chopra. (2022). A State-Space Perspective on the Expedited Gradient Methods: Nadam, RAdam, and Rescaled Gradient Flow. 4. 31–36. 1 indexed citations
7.
Chakrabarti, Kushal, Nirupam Gupta, & Nikhil Chopra. (2022). On Preconditioning of Decentralized Gradient-Descent When Solving a System of Linear Equations. IEEE Transactions on Control of Network Systems. 9(2). 811–822. 1 indexed citations
8.
Chakrabarti, Kushal & Nikhil Chopra. (2022). Analysis and Synthesis of Adaptive Gradient Algorithms in Machine Learning: The Case of AdaBound and MAdamSSM. 2022 IEEE 61st Conference on Decision and Control (CDC). 795–800. 1 indexed citations
9.
Chakrabarti, Kushal, Amrit Singh Bedi, Fikadu T. Dagefu, Jeffrey N. Twigg, & Nikhil Chopra. (2022). Fast Distributed Beamforming without Receiver Feedback. 1408–1412. 1 indexed citations
10.
Chakrabarti, Kushal & Nikhil Chopra. (2021). Generalized AdaGrad (G-AdaGrad) and Adam: A State-Space Perspective. 2021 60th IEEE Conference on Decision and Control (CDC). 1496–1501. 4 indexed citations
11.
Chakrabarti, Kushal, Nirupam Gupta, & Nikhil Chopra. (2021). Iterative pre-conditioning for expediting the distributed gradient-descent method: The case of linear least-squares problem. Automatica. 137. 110095–110095. 5 indexed citations
12.
Chakrabarti, Kushal, Nirupam Gupta, & Nikhil Chopra. (2021). Robustness of Iteratively Pre-Conditioned Gradient-Descent Method: The Case of Distributed Linear Regression Problem. 2248–2253. 3 indexed citations
13.
Chakrabarti, Kushal, Nirupam Gupta, & Nikhil Chopra. (2020). Robustness of Iteratively Pre-Conditioned Gradient-Descent Method: The Case of Distributed Linear Regression Problem. IEEE Control Systems Letters. 5(6). 2180–2185. 2 indexed citations
14.
Chakrabarti, Kushal, et al.. (2019). A Kalman Filter Approach for Biomolecular Systems with Noise Covariance Updating. 262–267. 1 indexed citations
15.
Chakrabarti, Kushal & Lior Pachter. (2004). Visualization of Multiple Genome Annotations and Alignments With the K-BROWSER. Genome Research. 14(4). 716–720. 12 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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2026