Harsh Bhatia

1.6k total citations
38 papers, 830 citations indexed

About

Harsh Bhatia is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Computer Networks and Communications. According to data from OpenAlex, Harsh Bhatia has authored 38 papers receiving a total of 830 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Computer Vision and Pattern Recognition, 11 papers in Computer Graphics and Computer-Aided Design and 10 papers in Computer Networks and Communications. Recurrent topics in Harsh Bhatia's work include Computer Graphics and Visualization Techniques (11 papers), Advanced Data Storage Technologies (6 papers) and Data Visualization and Analytics (6 papers). Harsh Bhatia is often cited by papers focused on Computer Graphics and Visualization Techniques (11 papers), Advanced Data Storage Technologies (6 papers) and Data Visualization and Analytics (6 papers). Harsh Bhatia collaborates with scholars based in United States, Slovenia and Brazil. Harsh Bhatia's co-authors include Peer‐Timo Bremer, Valerio Pascucci, Helgi I. Ingólfsson, Timothy S. Carpenter, Felice C. Lightstone, ‪Siewert J. Marrink, Attila Gyulassy, Peter Lindström, Guoning Chen and Joshua A. Levine and has published in prestigious journals such as Nature, The Journal of Physical Chemistry B and The Journal of Physical Chemistry C.

In The Last Decade

Harsh Bhatia

35 papers receiving 818 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Harsh Bhatia United States 16 299 148 121 104 97 38 830
Martin Falk Sweden 14 118 0.4× 249 1.7× 47 0.4× 167 1.6× 36 0.4× 38 615
Paweł Dłotko Poland 15 88 0.3× 88 0.6× 90 0.7× 48 0.5× 459 4.7× 53 967
Scott B. Baden United States 18 184 0.6× 115 0.8× 134 1.1× 65 0.6× 59 0.6× 79 1.3k
László Tóth Hungary 17 85 0.3× 59 0.4× 70 0.6× 122 1.2× 77 0.8× 103 1.4k
Al Globus United States 13 55 0.2× 108 0.7× 69 0.6× 96 0.9× 78 0.8× 48 743
Yuanan Diao United States 18 221 0.7× 146 1.0× 70 0.6× 111 1.1× 196 2.0× 97 962
Ingrid Hotz Germany 21 56 0.2× 438 3.0× 174 1.4× 279 2.7× 223 2.3× 98 1.1k
Michael Mascagni United States 21 141 0.5× 212 1.4× 73 0.6× 16 0.2× 235 2.4× 79 1.2k
David M. Beazley United States 14 42 0.1× 62 0.4× 121 1.0× 39 0.4× 54 0.6× 36 1.1k
Guang Song United States 23 1.2k 3.9× 314 2.1× 21 0.2× 30 0.3× 183 1.9× 71 1.7k

Countries citing papers authored by Harsh Bhatia

Since Specialization
Citations

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

Fields of papers citing papers by Harsh Bhatia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Harsh Bhatia

This figure shows the co-authorship network connecting the top 25 collaborators of Harsh Bhatia. A scholar is included among the top collaborators of Harsh Bhatia 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 Harsh Bhatia. Harsh Bhatia 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.
Bhatia, Harsh, et al.. (2024). Innovative way to break chemical bonds broadens horizons for making molecules. Nature. 632(8025). 508–509. 1 indexed citations
2.
Bhatia, Harsh, Fikret Aydin, Timothy S. Carpenter, et al.. (2023). The confluence of machine learning and multiscale simulations. Current Opinion in Structural Biology. 80. 102569–102569. 16 indexed citations
3.
Bhatia, Harsh, et al.. (2023). Progressive Tree-Based Compression of Large-Scale Particle Data. IEEE Transactions on Visualization and Computer Graphics. 30(7). 4321–4338. 2 indexed citations
4.
Zhu, Ben, Menglong Zhao, Harsh Bhatia, et al.. (2022). Data-driven model for divertor plasma detachment prediction. Journal of Plasma Physics. 88(5). 13 indexed citations
5.
Bhatia, Harsh, et al.. (2022). AMM: Adaptive Multilinear Meshes. IEEE Transactions on Visualization and Computer Graphics. 28(6). 2350–2363. 9 indexed citations
6.
Bhatia, Harsh, Timothy S. Carpenter, Helgi I. Ingólfsson, et al.. (2021). Machine-learning-based dynamic-importance sampling for adaptive multiscale simulations. Nature Machine Intelligence. 3(5). 401–409. 24 indexed citations
7.
Natale, Francesco Di, et al.. (2021). Multiscale Machine-Learned Modeling Infrastructure RAS. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information).
8.
Bhatia, Harsh, et al.. (2021). High-Quality and Low-Memory-Footprint Progressive Decoding of Large-Scale Particle Data. 32–42. 6 indexed citations
9.
Ingólfsson, Helgi I., Harsh Bhatia, William F. Bennett, et al.. (2020). Capturing Biologically Complex Tissue-Specific Membranes at Different Levels of Compositional Complexity. The Journal of Physical Chemistry B. 124(36). 7819–7829. 45 indexed citations
10.
Bhatia, Harsh, et al.. (2018). Problems and Suggestions of Small Scale Industries in Rajnandgaon District. 6(4). 455–458.
11.
Bhatia, Harsh, Nikhil Jain, Abhinav Bhatelé, et al.. (2018). Interactive Investigation of Traffic Congestion on Fat‐Tree Networks Using TreeScope. Computer Graphics Forum. 37(3). 561–572. 8 indexed citations
12.
Bhatia, Harsh, et al.. (2018). A Study of the Trade-off Between Reducing Precision and Reducing Resolution for Data Analysis and Visualization. IEEE Transactions on Visualization and Computer Graphics. 25(1). 1193–1203. 16 indexed citations
13.
Ingólfsson, Helgi I., Timothy S. Carpenter, Harsh Bhatia, et al.. (2017). Computational Lipidomics of the Neuronal Plasma Membrane. Biophysical Journal. 113(10). 2271–2280. 206 indexed citations
14.
Bhatia, Harsh, et al.. (2014). Local, smooth, and consistent Jacobi set simplification. Computational Geometry. 48(4). 311–332. 10 indexed citations
15.
Bhatia, Harsh, Attila Gyulassy, Hao Wang, Peer‐Timo Bremer, & Valerio Pascucci. (2013). Robust Detection of Singularities in Vector Fields. University of North Texas Digital Library (University of North Texas). 2 indexed citations
16.
Rosen, Paul, et al.. (2013). Visualizing Robustness of Critical Points for 2D Time‐Varying Vector Fields. Computer Graphics Forum. 32(3pt2). 221–230. 17 indexed citations
17.
Bhatia, Harsh, et al.. (2012). The Helmholtz-Hodge Decomposition—A Survey. IEEE Transactions on Visualization and Computer Graphics. 19(8). 1386–1404. 167 indexed citations
18.
Levine, Joshua A., et al.. (2012). A Quantized Boundary Representation of 2D Flows. Computer Graphics Forum. 31(3pt1). 945–954. 5 indexed citations
19.
Bhatia, Harsh, Peer‐Timo Bremer, Guoning Chen, et al.. (2011). Flow Visualization with Quantified Spatial and Temporal Errors Using Edge Maps. IEEE Transactions on Visualization and Computer Graphics. 18(9). 1383–1396. 28 indexed citations
20.
Bhatia, Harsh, Peer‐Timo Bremer, Guoning Chen, et al.. (2011). Edge maps: Representing flow with bounded error. King Abdullah University of Science and Technology Repository (King Abdullah University of Science and Technology). 10. 75–82. 18 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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