Caleb Geniesse

4.4k total citations · 1 hit paper
9 papers, 1.8k citations indexed

About

Caleb Geniesse is a scholar working on Cognitive Neuroscience, Computational Theory and Mathematics and Molecular Biology. According to data from OpenAlex, Caleb Geniesse has authored 9 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Cognitive Neuroscience, 4 papers in Computational Theory and Mathematics and 3 papers in Molecular Biology. Recurrent topics in Caleb Geniesse's work include Functional Brain Connectivity Studies (3 papers), Advanced Neuroimaging Techniques and Applications (3 papers) and Topological and Geometric Data Analysis (3 papers). Caleb Geniesse is often cited by papers focused on Functional Brain Connectivity Studies (3 papers), Advanced Neuroimaging Techniques and Applications (3 papers) and Topological and Geometric Data Analysis (3 papers). Caleb Geniesse collaborates with scholars based in United States, United Kingdom and Italy. Caleb Geniesse's co-authors include Vijay S. Pande, Bharath Ramsundar, Zhenqin Wu, Joseph Gomes, Karl Leswing, Evan N. Feinberg, Manish Saggar, Giovanni Petri, Olaf Sporns and Rhiju Das and has published in prestigious journals such as Nature Communications, The Journal of Cell Biology and NeuroImage.

In The Last Decade

Caleb Geniesse

9 papers receiving 1.8k 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.

MoleculeNet: a benchmark for molecular machine learning

2017 1.7k citations Zhenqin Wu, Bharath Ramsundar et al. Chemical Science profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Caleb Geniesse United States	6	1.2k	1.1k	864	289	94	9	1.8k
Karl Leswing United States	11	1.5k 1.2×	1.3k 1.2×	1.1k 1.3×	304 1.1×	115 1.2×	14	2.3k
Steven Kearnes United States	8	1.1k 0.9×	1.2k 1.1×	723 0.8×	224 0.8×	93 1.0×	17	1.8k
Zhenqin Wu United States	9	1.6k 1.3×	1.3k 1.2×	1.3k 1.5×	339 1.2×	121 1.3×	16	2.4k
Evan N. Feinberg United States	9	1.7k 1.4×	1.3k 1.3×	2.0k 2.3×	306 1.1×	161 1.7×	17	3.2k
Marcus Olivecrona Sweden	3	1.5k 1.2×	980 0.9×	1.1k 1.3×	203 0.7×	77 0.8×	3	2.1k
Kevin McCloskey United States	7	758 0.6×	658 0.6×	558 0.6×	189 0.7×	57 0.6×	13	1.2k
Joseph Gomes United States	10	1.5k 1.2×	1.6k 1.5×	1.2k 1.3×	376 1.3×	144 1.5×	26	2.6k
Zhaoping Xiong China	13	1.1k 0.9×	647 0.6×	828 1.0×	164 0.6×	55 0.6×	22	1.6k
Dingyan Wang China	22	1.2k 0.9×	761 0.7×	1.2k 1.4×	141 0.5×	65 0.7×	47	2.1k
Timothy Hirzel United States	4	795 0.6×	797 0.8×	550 0.6×	122 0.4×	57 0.6×	6	1.3k

Countries citing papers authored by Caleb Geniesse

Since Specialization

Citations

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

Fields of papers citing papers by Caleb Geniesse

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Caleb Geniesse

This figure shows the co-authorship network connecting the top 25 collaborators of Caleb Geniesse. A scholar is included among the top collaborators of Caleb Geniesse 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 Caleb Geniesse. Caleb Geniesse 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:

9 of 9 papers shown

1.

Geniesse, Caleb, George A. Constantinides, Nhan Viet Tran, et al.. (2025). Greater than the Sum of its LUTs: Scaling Up LUT-based Neural Networks with AmigoLUT. 25–35. 2 indexed citations

2.

Jo, Booil, Caleb Geniesse, Lucina Q. Uddin, et al.. (2025). A data-driven latent variable approach to validating the research domain criteria framework. Nature Communications. 16(1). 830–830. 3 indexed citations

3.

Geniesse, Caleb, et al.. (2024). Deconstructing the Mapper algorithm to extract richer topological and temporal features from functional neuroimaging data. Network Neuroscience. 8(4). 1355–1382. 3 indexed citations

4.

Morris, Timothy W., et al.. (2022). Synaptopodin stress fiber and contractomere at the epithelial junction. The Journal of Cell Biology. 221(5). 7 indexed citations

5.

Geniesse, Caleb, et al.. (2022). NeuMapper: A scalable computational framework for multiscale exploration of the brain’s dynamical organization. Network Neuroscience. 6(2). 1–32. 9 indexed citations

6.

Xie, Hua, et al.. (2021). Spontaneous and deliberate modes of creativity: Multitask eigen-connectivity analysis captures latent cognitive modes during creative thinking. NeuroImage. 243. 118531–118531. 18 indexed citations

7.

Geniesse, Caleb, Olaf Sporns, Giovanni Petri, & Manish Saggar. (2019). Generating dynamical neuroimaging spatiotemporal representations (DyNeuSR) using topological data analysis. Network Neuroscience. 3(3). 763–778. 33 indexed citations

8.

Watkins, Andrew M., Caleb Geniesse, Wipapat Kladwang, et al.. (2018). Blind prediction of noncanonical RNA structure at atomic accuracy. Science Advances. 4(5). eaar5316–eaar5316. 33 indexed citations

9.

Wu, Zhenqin, Bharath Ramsundar, Evan N. Feinberg, et al.. (2017). MoleculeNet: a benchmark for molecular machine learning. Chemical Science. 9(2). 513–530. 1696 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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