Prasanna Balaprakash

3.9k total citations · 1 hit paper
115 papers, 1.7k citations indexed

About

Prasanna Balaprakash is a scholar working on Artificial Intelligence, Computer Networks and Communications and Hardware and Architecture. According to data from OpenAlex, Prasanna Balaprakash has authored 115 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Artificial Intelligence, 33 papers in Computer Networks and Communications and 22 papers in Hardware and Architecture. Recurrent topics in Prasanna Balaprakash's work include Parallel Computing and Optimization Techniques (20 papers), Advanced Data Storage Technologies (17 papers) and Model Reduction and Neural Networks (14 papers). Prasanna Balaprakash is often cited by papers focused on Parallel Computing and Optimization Techniques (20 papers), Advanced Data Storage Technologies (17 papers) and Model Reduction and Neural Networks (14 papers). Prasanna Balaprakash collaborates with scholars based in United States, France and Belgium. Prasanna Balaprakash's co-authors include Romit Maulik, Bethany Lusch, Mauro Birattari, Thomas Stützle, Stefan M. Wild, Marco Dorigo, Sandeep Madireddy, Paul Hovland, Boyana Norris and Yanjing Li and has published in prestigious journals such as Proceedings of the IEEE, Journal of Computational Physics and European Journal of Operational Research.

In The Last Decade

Prasanna Balaprakash

106 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.

Reduced-order modeling of advection-dominated systems with recurrent neural networks and convolutional autoencoders

2021 185 citations Romit Maulik, Bethany Lusch et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Prasanna Balaprakash United States	22	483	342	318	257	227	115	1.7k
Vicente Hernández Spain	18	193 0.4×	440 1.3×	181 0.6×	107 0.4×	312 1.4×	107	1.7k
Sivasankaran Rajamanickam United States	21	306 0.6×	548 1.6×	134 0.4×	547 2.1×	286 1.3×	90	2.0k
Jochen Garcke Germany	17	573 1.2×	95 0.3×	190 0.6×	36 0.1×	140 0.6×	54	1.9k
James McKee United Kingdom	11	233 0.5×	200 0.6×	63 0.2×	175 0.7×	254 1.1×	32	1.2k
Zheng Zhang United States	22	173 0.4×	184 0.5×	232 0.7×	97 0.4×	707 3.1×	168	1.8k
Erik G. Boman United States	21	164 0.3×	582 1.7×	75 0.2×	435 1.7×	307 1.4×	73	1.5k
R. Baker Kearfott United States	22	558 1.2×	156 0.5×	366 1.2×	109 0.4×	211 0.9×	75	3.5k
Anshul Gupta United States	19	317 0.7×	844 2.5×	51 0.2×	697 2.7×	347 1.5×	82	1.9k
Hongbo Liu China	20	544 1.1×	486 1.4×	68 0.2×	87 0.3×	178 0.8×	146	2.0k
Feng Chen China	21	648 1.3×	1.3k 3.8×	138 0.4×	432 1.7×	177 0.8×	151	2.4k

Countries citing papers authored by Prasanna Balaprakash

Since Specialization

Citations

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

Fields of papers citing papers by Prasanna Balaprakash

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Prasanna Balaprakash

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

All Works

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20 of 20 papers shown

Choi, Jong Youl, Kshitij Mehta, Pei Zhang, et al.. (2025). Scalable training of trustworthy and energy-efficient predictive graph foundation models for atomistic materials modeling: a case study with HydraGNN. The Journal of Supercomputing. 81(4). 5 indexed citations

Tsaris, Aristeidis, Mohamed Wahib, Larry M. York, et al.. (2025). Distributed Cross-Channel Hierarchical Aggregation for Foundation Models. 935–948.

Wang, Xiao, Jong Youl Choi, Hong‐Jun Yoon, et al.. (2025). ORBIT-2: Scaling Exascale Vision Foundation Models for Weather and Climate Downscaling. 86–98. 1 indexed citations

Balaprakash, Prasanna, Franck Cappello, Ewa Deelman, et al.. (2025). SWARM: Reimagining scientific workflow management systems in a distributed world. The International Journal of High Performance Computing Applications. 39(5). 692–712. 2 indexed citations

Suter, Frédéric, et al.. (2025). The (R)evolution of Scientific Workflows in the Agentic AI Era: Towards Autonomous Science. 2305–2316.

Balaprakash, Prasanna, et al.. (2024). Multi-fidelity reinforcement learning with control variates. Neurocomputing. 597. 127963–127963.

Krishnan, R., George Papadimitriou, Anirban Mandal, et al.. (2024). Advancing anomaly detection in computational workflows with active learning. Future Generation Computer Systems. 166. 107608–107608. 1 indexed citations

Balaprakash, Prasanna, et al.. (2024). Physics-informed heterogeneous graph neural networks for DC blocker placement. Electric Power Systems Research. 235. 110795–110795. 1 indexed citations

Maulik, Romit, et al.. (2023). Quantifying uncertainty for deep learning based forecasting and flow-reconstruction using neural architecture search ensembles. Physica D Nonlinear Phenomena. 454. 133852–133852. 5 indexed citations

10.

Leyffer, Sven, et al.. (2023). Learning Symbolic Expressions: Mixed-Integer Formulations, Cuts, and Heuristics. INFORMS journal on computing. 1 indexed citations

11.

Samanta, Amit, et al.. (2023). Machine-learning-aided density functional theory calculations of stacking fault energies in steel. Scripta Materialia. 241. 115862–115862. 4 indexed citations

12.

Krishnan, R., George Papadimitriou, Cong Wang, et al.. (2023). Graph neural networks for detecting anomalies in scientific workflows. The International Journal of High Performance Computing Applications. 37(3-4). 394–411. 5 indexed citations

13.

Maulik, Romit, Jiali Wang, Gianmarco Mengaldo, et al.. (2022). Efficient high-dimensional variational data assimilation with machine-learned reduced-order models. Geoscientific model development. 15(8). 3433–3445. 21 indexed citations

14.

Balaprakash, Prasanna, et al.. (2021). Data-Driven Random Access Optimization in Multi-Cell IoT Networks Using NOMA. IEEE Transactions on Wireless Communications. 21(7). 4938–4953. 5 indexed citations

15.

Balaprakash, Prasanna, et al.. (2020). FIdelity: Efficient Resilience Analysis Framework for Deep Learning Accelerators. 270–281. 48 indexed citations

16.

Madireddy, Sandeep, et al.. (2020). Toward Generalizable Models of I/O Throughput. 41–49. 4 indexed citations

17.

Wang, Jiali, Prasanna Balaprakash, & V. R. Kotamarthi. (2019). Fast domain-aware neural network emulation of a planetary boundary layer parameterization in a numerical weather forecast model. Geoscientific model development. 12(10). 4261–4274. 32 indexed citations

18.

Mametjanov, Azamat, et al.. (2015). Autotuning FPGA Design Parameters for Performance and Power. 84–91. 18 indexed citations

19.

Balaprakash, Prasanna, Darius Buntinas, Anthony Chan, et al.. (2013). Exascale workload characterization and architecture implications. 5. 10 indexed citations

20.

Balaprakash, Prasanna, Mauro Birattari, & Thomas Stützle. (2007). Improvement strategies for the F-Race algorithm: sampling design and iterative refinement. Lecture notes in computer science. 108–122. 100 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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