Rohit Tripathy

847 total citations · 1 hit paper
7 papers, 584 citations indexed

About

Rohit Tripathy is a scholar working on Molecular Biology, Artificial Intelligence and Statistics, Probability and Uncertainty. According to data from OpenAlex, Rohit Tripathy has authored 7 papers receiving a total of 584 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Molecular Biology, 3 papers in Artificial Intelligence and 3 papers in Statistics, Probability and Uncertainty. Recurrent topics in Rohit Tripathy's work include Probabilistic and Robust Engineering Design (3 papers), Advanced Multi-Objective Optimization Algorithms (2 papers) and Model Reduction and Neural Networks (2 papers). Rohit Tripathy is often cited by papers focused on Probabilistic and Robust Engineering Design (3 papers), Advanced Multi-Objective Optimization Algorithms (2 papers) and Model Reduction and Neural Networks (2 papers). Rohit Tripathy collaborates with scholars based in United States, India and Canada. Rohit Tripathy's co-authors include Ilias Bilionis, Marcial Gonzalez, Jitesh H. Panchal, Gregory W. Carter, Peter K. Koo, Antonio Majdandzic, Gregory A. Cary, Amber Tang, Hong Wang and R. Thundil Karuppa Raj and has published in prestigious journals such as Journal of Computational Physics, Briefings in Bioinformatics and npj Systems Biology and Applications.

In The Last Decade

Rohit Tripathy

6 papers receiving 563 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.

Deep UQ: Learning deep neural network surrogate models for high dimensional uncertainty quantification

2018 312 citations Rohit Tripathy, Ilias Bilionis Journal of Computational Physics profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Rohit Tripathy United States	5	251	243	124	111	89	7	584
Laura Mainini Italy	12	168 0.7×	204 0.8×	63 0.5×	57 0.5×	117 1.3×	36	560
Apostolos F. Psaros United States	13	315 1.3×	255 1.0×	90 0.7×	30 0.3×	77 0.9×	17	675
Mengwu Guo Netherlands	11	279 1.1×	477 2.0×	66 0.5×	73 0.7×	213 2.4×	22	746
E. Andrés Spain	11	135 0.5×	115 0.5×	40 0.3×	132 1.2×	146 1.6×	28	604
Zongren Zou United States	10	102 0.4×	297 1.2×	160 1.3×	27 0.2×	73 0.8×	15	588
Timothy Wildey United States	16	233 0.9×	112 0.5×	69 0.6×	240 2.2×	281 3.2×	52	644
Loïc Le Gratiet France	10	278 1.1×	85 0.3×	117 0.9×	284 2.6×	22 0.2×	13	649
David A. Barajas‐Solano United States	12	145 0.6×	461 1.9×	143 1.2×	44 0.4×	177 2.0×	31	887
Xiaoqun Wang China	16	332 1.3×	59 0.2×	34 0.3×	120 1.1×	149 1.7×	62	943

Countries citing papers authored by Rohit Tripathy

Since Specialization

Citations

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

Fields of papers citing papers by Rohit Tripathy

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rohit Tripathy

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

All Works

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7 of 7 papers shown

1.

Tripathy, Rohit, et al.. (2025). Effective integration of multi-omics with prior knowledge to identify biomarkers via explainable graph neural networks. npj Systems Biology and Applications. 11(1). 43–43. 5 indexed citations

2.

Kawaguchi, Risa Karakida, et al.. (2022). Learning single-cell chromatin accessibility profiles using meta-analytic marker genes. Briefings in Bioinformatics. 24(1). 2 indexed citations

3.

Majdandzic, Antonio, et al.. (2022). Selecting deep neural networks that yield consistent attribution-based interpretations for genomics.. PubMed. 200. 131–149. 5 indexed citations

4.

Tripathy, Rohit, et al.. (2019). Simulator-free solution of high-dimensional stochastic elliptic partial differential equations using deep neural networks. Journal of Computational Physics. 404. 109120–109120. 117 indexed citations

5.

Tripathy, Rohit & Ilias Bilionis. (2018). Deep UQ: Learning deep neural network surrogate models for high dimensional uncertainty quantification. Journal of Computational Physics. 375. 565–588. 312 indexed citations breakdown →

6.

Tripathy, Rohit, Ilias Bilionis, & Marcial Gonzalez. (2016). Gaussian processes with built-in dimensionality reduction: Applications to high-dimensional uncertainty propagation. Journal of Computational Physics. 321. 191–223. 142 indexed citations

7.

Tripathy, Rohit, et al.. (2014). A Numerical Investigation on the Performance of an Earth Air Heat Exchanger System for the Indian District of Nagpur. Applied Mechanics and Materials. 592-594. 1398–1402. 1 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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