Jaideep Pathak

3.3k total citations · 3 hit papers
11 papers, 1.7k citations indexed

About

Jaideep Pathak is a scholar working on Artificial Intelligence, Atmospheric Science and Statistical and Nonlinear Physics. According to data from OpenAlex, Jaideep Pathak has authored 11 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 6 papers in Atmospheric Science and 4 papers in Statistical and Nonlinear Physics. Recurrent topics in Jaideep Pathak's work include Meteorological Phenomena and Simulations (6 papers), Neural Networks and Reservoir Computing (6 papers) and Neural Networks and Applications (4 papers). Jaideep Pathak is often cited by papers focused on Meteorological Phenomena and Simulations (6 papers), Neural Networks and Reservoir Computing (6 papers) and Neural Networks and Applications (4 papers). Jaideep Pathak collaborates with scholars based in United States, Switzerland and United Kingdom. Jaideep Pathak's co-authors include Edward Ott, Brian R. Hunt, Michelle Girvan, Zhixin Lu, Roger W. Brockett, Istvan Szunyogh, Karthik Kashinath, Peter Harrington, Thorsten Kurth and Anima Anandkumar and has published in prestigious journals such as Physical Review Letters, SHILAP Revista de lepidopterología and Geophysical Research Letters.

In The Last Decade

Jaideep Pathak

11 papers receiving 1.6k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Model-Free Prediction of Large Spatiotemporally Chaotic Systems from Data: A Reservoir Computing Approach

2018 770 citations Jaideep Pathak, Brian R. Hunt et al. Physical Review Letters profile →
Using machine learning to replicate chaotic attractors and calculate Lyapunov exponents from data

2017 399 citations Jaideep Pathak, Zhixin Lu et al. Chaos An Interdisciplinary Journal of Nonlinear Science profile →
FourCastNet: Accelerating Global High-Resolution Weather Forecasting Using Adaptive Fourier Neural Operators

2023 98 citations Thorsten Kurth, Shashank Subramanian et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jaideep Pathak United States	9	1.1k	622	391	310	288	11	1.7k
Dirk Witthaut Germany	35	480 0.4×	997 1.6×	1.1k 2.8×	186 0.6×	106 0.4×	117	3.6k
R. Eykholt United States	15	209 0.2×	433 0.7×	176 0.5×	107 0.3×	92 0.3×	25	1.2k
Elbert E. N. Macau Brazil	23	118 0.1×	729 1.2×	99 0.3×	265 0.9×	46 0.2×	168	1.7k
Jan Sieber United Kingdom	25	87 0.1×	543 0.9×	303 0.8×	99 0.3×	49 0.2×	73	1.7k
Jürgen Kurths Germany	13	122 0.1×	567 0.9×	102 0.3×	147 0.5×	79 0.3×	24	1.6k
Hans Jacob S. Feder United States	9	183 0.2×	224 0.4×	128 0.3×	65 0.2×	49 0.2×	12	1.5k
James F. Heagy United States	18	116 0.1×	2.4k 3.8×	100 0.3×	274 0.9×	89 0.3×	37	3.0k
Nicholas Tufillaro United States	21	81 0.1×	794 1.3×	90 0.2×	47 0.2×	108 0.4×	61	1.5k
Pierre‐Olivier Amblard France	19	158 0.1×	352 0.6×	99 0.3×	118 0.4×	74 0.3×	84	1.0k

Countries citing papers authored by Jaideep Pathak

Since Specialization

Citations

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

Fields of papers citing papers by Jaideep Pathak

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jaideep Pathak

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

All Works

Sort: Min cites: Since: Top N: Style:

11 of 11 papers shown

Brenowitz, Noah, Yair Cohen, Jaideep Pathak, et al.. (2025). Residual corrective diffusion modeling for km-scale atmospheric downscaling. Communications Earth & Environment. 6(1). 14 indexed citations

Brenowitz, Noah, Yair Cohen, Jaideep Pathak, et al.. (2025). A Practical Probabilistic Benchmark for AI Weather Models. Geophysical Research Letters. 52(7). 8 indexed citations

Kurth, Thorsten, Shashank Subramanian, Peter Harrington, et al.. (2023). FourCastNet: Accelerating Global High-Resolution Weather Forecasting Using Adaptive Fourier Neural Operators. 1–11. 98 indexed citations breakdown →

Chattopadhyay, Ashesh, Jaideep Pathak, Ebrahim Nabizadeh, Wahid Bhimji, & Pedram Hassanzadeh. (2023). Long-term stability and generalization of observationally-constrained stochastic data-driven models for geophysical turbulence. SHILAP Revista de lepidopterología. 2. 3 indexed citations

Szunyogh, Istvan, et al.. (2022). A Hybrid Approach to Atmospheric Modeling That Combines Machine Learning With a Physics‐Based Numerical Model. Journal of Advances in Modeling Earth Systems. 14(3). 42 indexed citations

Pathak, Jaideep, Mustafa Mustafa, Karthik Kashinath, et al.. (2021). ML-PDE: A Framework for a Machine Learning Enhanced PDE Solver. Bulletin of the American Physical Society. 1 indexed citations

Szunyogh, Istvan, et al.. (2020). A Machine Learning‐Based Global Atmospheric Forecast Model. Geophysical Research Letters. 47(9). 94 indexed citations

Vlachas, Pantelis R., Jaideep Pathak, Brian R. Hunt, et al.. (2019). Forecasting of Spatio-temporal Chaotic Dynamics with Recurrent Neural Networks: a comparative study of Reservoir Computing and Backpropagation Algorithms. 12 indexed citations

Pathak, Jaideep, Brian R. Hunt, Michelle Girvan, Zhixin Lu, & Edward Ott. (2018). Model-Free Prediction of Large Spatiotemporally Chaotic Systems from Data: A Reservoir Computing Approach. Physical Review Letters. 120(2). 24102–24102. 770 indexed citations breakdown →

10.

Lu, Zhixin, Jaideep Pathak, Brian R. Hunt, et al.. (2017). Reservoir observers: Model-free inference of unmeasured variables in chaotic systems. Chaos An Interdisciplinary Journal of Nonlinear Science. 27(4). 41102–41102. 225 indexed citations

11.

Pathak, Jaideep, Zhixin Lu, Brian R. Hunt, Michelle Girvan, & Edward Ott. (2017). Using machine learning to replicate chaotic attractors and calculate Lyapunov exponents from data. Chaos An Interdisciplinary Journal of Nonlinear Science. 27(12). 121102–121102. 399 indexed citations breakdown →

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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