Debasish Chatterjee

2.1k total citations
98 papers, 1.4k citations indexed

About

Debasish Chatterjee is a scholar working on Control and Systems Engineering, Computational Theory and Mathematics and Numerical Analysis. According to data from OpenAlex, Debasish Chatterjee has authored 98 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 73 papers in Control and Systems Engineering, 17 papers in Computational Theory and Mathematics and 13 papers in Numerical Analysis. Recurrent topics in Debasish Chatterjee's work include Stability and Control of Uncertain Systems (44 papers), Advanced Control Systems Optimization (34 papers) and Control Systems and Identification (22 papers). Debasish Chatterjee is often cited by papers focused on Stability and Control of Uncertain Systems (44 papers), Advanced Control Systems Optimization (34 papers) and Control Systems and Identification (22 papers). Debasish Chatterjee collaborates with scholars based in India, Switzerland and United States. Debasish Chatterjee's co-authors include Daniel Liberzon, Linh Vu, John Lygeros, Atreyee Kundu, Eugenio Cinquemani, Peter Hokayem, Federico Ramponi, Amit Patra, Mayank Agarwal and Daniel E. Quevedo and has published in prestigious journals such as IEEE Transactions on Automatic Control, Automatica and Journal of Materials Processing Technology.

In The Last Decade

Debasish Chatterjee

87 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Debasish Chatterjee India 18 1.1k 257 150 83 70 98 1.4k
Mario Sassano Italy 18 928 0.8× 247 1.0× 165 1.1× 90 1.1× 63 0.9× 140 1.3k
Hans Schumacher Netherlands 7 614 0.5× 143 0.6× 241 1.6× 99 1.2× 33 0.5× 18 1.0k
Samuel Coogan United States 17 513 0.4× 172 0.7× 264 1.8× 90 1.1× 55 0.8× 107 960
Stephan Trenn Germany 20 1.1k 0.9× 254 1.0× 200 1.3× 164 2.0× 24 0.3× 108 1.4k
Liguo Zhang China 14 528 0.5× 159 0.6× 52 0.3× 90 1.1× 16 0.2× 118 788
Leonardo Amaral Mozelli Brazil 15 751 0.7× 326 1.3× 142 0.9× 63 0.8× 43 0.6× 42 956
James A. Primbs United States 20 942 0.8× 72 0.3× 196 1.3× 85 1.0× 215 3.1× 70 1.4k
Stefan Pettersson Sweden 21 2.1k 1.8× 378 1.5× 274 1.8× 236 2.8× 14 0.2× 62 2.5k
Naceur Benhadj Braïek Tunisia 21 1.5k 1.3× 214 0.8× 71 0.5× 284 3.4× 18 0.3× 167 1.8k
Bo‐Chao Zheng China 19 684 0.6× 376 1.5× 75 0.5× 70 0.8× 10 0.1× 49 886

Countries citing papers authored by Debasish Chatterjee

Since Specialization
Citations

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

Fields of papers citing papers by Debasish Chatterjee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Debasish Chatterjee

This figure shows the co-authorship network connecting the top 25 collaborators of Debasish Chatterjee. A scholar is included among the top collaborators of Debasish Chatterjee 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 Debasish Chatterjee. Debasish Chatterjee 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.
Chatterjee, Debasish, et al.. (2025). Explicit Feedback Synthesis Driven by Quasi-Interpolation for Nonlinear Model Predictive Control. IEEE Transactions on Automatic Control. 70(7). 4751–4758. 1 indexed citations
2.
Grüne, Lars, et al.. (2025). Representation of practical nonsmooth control Lyapunov functions by piecewise affine functions and neural networks. Systems & Control Letters. 202. 106103–106103. 1 indexed citations
3.
Chatterjee, Debasish, et al.. (2024). Exact Solutions to Minmax Optimal Control Problems for Constrained Noisy Linear Systems. IEEE Control Systems Letters. 8. 2063–2068. 2 indexed citations
4.
Chatterjee, Debasish, et al.. (2024). Discrete‐time Pontryagin maximum principle under rate constraints: Necessary conditions for optimality. Asian Journal of Control. 27(2). 852–862. 1 indexed citations
5.
Chatterjee, Debasish, et al.. (2024). Almost sure detection of the presence of malicious components in cyber–physical systems. Automatica. 167. 111789–111789.
6.
Banavar, Ravi N., et al.. (2023). Quantitative Estimates on the Domain of Feedback Linearization. IFAC-PapersOnLine. 56(1). 144–149. 1 indexed citations
7.
Chatterjee, Debasish, et al.. (2023). Control-Theoretic Splines under Uncountably Many Constraints: Fast and Exact Solutions. IFAC-PapersOnLine. 56(2). 1241–1246. 1 indexed citations
8.
Chatterjee, Debasish, et al.. (2023). Attaining the Chebyshev bound for optimal learning: A numerical algorithm. Systems & Control Letters. 181. 105648–105648. 2 indexed citations
9.
Chatterjee, Debasish, et al.. (2023). An illustration of a quasi-interpolation driven technique for feedback synthesis. IFAC-PapersOnLine. 56(2). 7498–7502.
10.
Ikeda, Takuya, Masaaki Nagahara, Debasish Chatterjee, & Srikant Sukumar. (2021). Constrained Smoothing Splines by Optimal Control. IEEE Control Systems Letters. 6. 1298–1303. 3 indexed citations
11.
Sukumar, Srikant, et al.. (2020). Optimal Multiplexing of Discrete-Time Constrained Control Systems on Matrix Lie Groups. IEEE Transactions on Automatic Control. 66(4). 1895–1901.
12.
Chatterjee, Debasish, et al.. (2017). Resource efficient stochastic predictive control under packet dropouts. IET Control Theory and Applications. 11(11). 1666–1673. 4 indexed citations
13.
Chatterjee, Debasish, et al.. (2017). Output Feedback Stable Stochastic Predictive Control With Hard Control Constraints. IEEE Control Systems Letters. 1(2). 382–387. 1 indexed citations
14.
Kundu, Atreyee & Debasish Chatterjee. (2017). Stabilizing switching signals: A transition from point-wise to asymptotic conditions. Systems & Control Letters. 106. 16–23. 10 indexed citations
15.
Chatterjee, Debasish, et al.. (2017). Stabilizing Stochastic Predictive Control Under Bernoulli Dropouts. IEEE Transactions on Automatic Control. 63(6). 1579–1590. 19 indexed citations
16.
Chatterjee, Debasish, et al.. (2017). Optimal Dictionary for Least Squares Representation. DSpace (IIT Bombay). 18(107). 1–28. 1 indexed citations
17.
Chatterjee, Debasish, et al.. (2016). Characterization of maximum hands-off control. Systems & Control Letters. 94. 31–36. 33 indexed citations
18.
Chatterjee, Debasish, et al.. (2016). Discrete-time Maximum Principle on matrix Lie groups. arXiv (Cornell University). 1 indexed citations
19.
Chatterjee, Debasish, et al.. (2013). On mean-square boundedness of stochastic linear systems with quantized observations. Institutional Research Information System (Università degli Studi di Brescia).
20.
Hokayem, Peter, Eugenio Cinquemani, Debasish Chatterjee, & John Lygeros. (2010). Stochastic MPC with output feedback and bounded control inputs. arXiv (Cornell University). 2 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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