Adeesh Kolluru

516 total citations · 1 hit paper
6 papers, 252 citations indexed

About

Adeesh Kolluru is a scholar working on Materials Chemistry, Artificial Intelligence and Electrical and Electronic Engineering. According to data from OpenAlex, Adeesh Kolluru has authored 6 papers receiving a total of 252 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Materials Chemistry, 2 papers in Artificial Intelligence and 2 papers in Electrical and Electronic Engineering. Recurrent topics in Adeesh Kolluru's work include Machine Learning in Materials Science (5 papers), Catalytic Processes in Materials Science (2 papers) and Topic Modeling (2 papers). Adeesh Kolluru is often cited by papers focused on Machine Learning in Materials Science (5 papers), Catalytic Processes in Materials Science (2 papers) and Topic Modeling (2 papers). Adeesh Kolluru collaborates with scholars based in United States, Denmark and Canada. Adeesh Kolluru's co-authors include Muhammed Shuaibi, C. Lawrence Zitnick, Zachary W. Ulissi, Abhishek Das, Brandon M. Wood, Siddharth Goyal, Javier Heras‐Domingo, Anuroop Sriram, Oleksandr Voznyy and Janice Lan and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Journal of Chemical Physics and SHILAP Revista de lepidopterología.

In The Last Decade

Adeesh Kolluru

6 papers receiving 241 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.

The Open Catalyst 2022 (OC22) Dataset and Challenges for Oxide Electrocatalysts

2023 174 citations Richard Tran, Janice Lan et al. ACS Catalysis profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Adeesh Kolluru United States	4	209	67	59	44	34	6	252
Janice Lan United States	4	190 0.9×	62 0.9×	49 0.8×	40 0.9×	33 1.0×	4	236
Felix Brockherde Germany	2	322 1.5×	32 0.5×	111 1.9×	25 0.6×	64 1.9×	2	350
Hyunwook Jung South Korea	9	213 1.0×	48 0.7×	37 0.6×	54 1.2×	57 1.7×	18	307
Esben L. Kolsbjerg Denmark	8	241 1.2×	42 0.6×	63 1.1×	44 1.0×	63 1.9×	10	310
Sina Stocker Germany	5	222 1.1×	27 0.4×	103 1.7×	37 0.8×	30 0.9×	5	266
Edward J. Beard United Kingdom	7	184 0.9×	35 0.5×	74 1.3×	11 0.3×	43 1.3×	8	295
Tairan Wang China	7	172 0.8×	86 1.3×	25 0.4×	70 1.6×	95 2.8×	20	353
Jessica Freeze United States	5	139 0.7×	40 0.6×	50 0.8×	27 0.6×	34 1.0×	7	302
Callum J. Court United Kingdom	5	305 1.5×	14 0.2×	107 1.8×	18 0.4×	43 1.3×	5	387
Aditi S. Krishnapriyan United States	8	174 0.8×	15 0.2×	27 0.5×	12 0.3×	59 1.7×	15	248

Countries citing papers authored by Adeesh Kolluru

Since Specialization

Citations

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

Fields of papers citing papers by Adeesh Kolluru

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Adeesh Kolluru

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

All Works

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6 of 6 papers shown

1.

Riebesell, Janosh, et al.. (2025). TorchSim: an efficient atomistic simulation engine in PyTorch. SHILAP Revista de lepidopterología. 1(2). 25003–25003. 2 indexed citations

2.

Xu, Wenbin, Adeesh Kolluru, Bowen Deng, et al.. (2025). Spin-informed universal graph neural networks for simulating magnetic ordering. Proceedings of the National Academy of Sciences. 122(27). e2422973122–e2422973122. 1 indexed citations

3.

Shuaibi, Muhammed, et al.. (2024). Investigating the error imbalance of large-scale machine learning potentials in catalysis. Catalysis Science & Technology. 14(20). 5899–5908. 5 indexed citations

4.

Tran, Richard, Janice Lan, Muhammed Shuaibi, et al.. (2023). The Open Catalyst 2022 (OC22) Dataset and Challenges for Oxide Electrocatalysts. ACS Catalysis. 13(5). 3066–3084. 174 indexed citations breakdown →

5.

Kolluru, Adeesh, Muhammed Shuaibi, Aini Palizhati, et al.. (2022). Open Challenges in Developing Generalizable Large-Scale Machine-Learning Models for Catalyst Discovery. ACS Catalysis. 12(14). 8572–8581. 48 indexed citations

6.

Kolluru, Adeesh, Muhammed Shuaibi, Siddharth Goyal, et al.. (2022). Transfer learning using attentions across atomic systems with graph neural networks (TAAG). The Journal of Chemical Physics. 156(18). 184702–184702. 22 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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