Aaron Sarna

1.2k total citations · 1 hit paper
9 papers, 517 citations indexed

About

Aaron Sarna is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics and Global and Planetary Change. According to data from OpenAlex, Aaron Sarna has authored 9 papers receiving a total of 517 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Computer Vision and Pattern Recognition, 3 papers in Computational Mechanics and 2 papers in Global and Planetary Change. Recurrent topics in Aaron Sarna's work include 3D Shape Modeling and Analysis (3 papers), Advanced Aircraft Design and Technologies (2 papers) and Advanced Vision and Imaging (2 papers). Aaron Sarna is often cited by papers focused on 3D Shape Modeling and Analysis (3 papers), Advanced Aircraft Design and Technologies (2 papers) and Advanced Vision and Imaging (2 papers). Aaron Sarna collaborates with scholars based in United States and Netherlands. Aaron Sarna's co-authors include Forrester Cole, Kyle Genova, Avneesh Sud, Thomas Funkhouser, William T. Freeman, Daniel Vlasic, Dilip Krishnan, David Belanger, Ce Liu and Florencia Garcia-Vicente and has published in prestigious journals such as Radiology, IEEE Transactions on Geoscience and Remote Sensing and Atmospheric measurement techniques.

In The Last Decade

Aaron Sarna

9 papers receiving 507 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.

Local Deep Implicit Functions for 3D Shape

2020 229 citations Kyle Genova, Forrester Cole et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Aaron Sarna United States	7	398	247	193	30	28	9	517
Anpei Chen China	8	612 1.5×	285 1.2×	366 1.9×	42 1.4×	60 2.1×	14	694
Matthew A. Chan United States	2	544 1.4×	298 1.2×	327 1.7×	35 1.2×	36 1.3×	4	666
Pascal Gautron France	12	388 1.0×	179 0.7×	401 2.1×	30 1.0×	10 0.4×	40	493
Boxiao Pan United States	4	724 1.8×	283 1.1×	294 1.5×	29 1.0×	38 1.4×	9	845
Keunhong Park United States	6	410 1.0×	217 0.9×	253 1.3×	33 1.1×	44 1.6×	7	495
Matheus Gadelha United States	7	314 0.8×	233 0.9×	160 0.8×	62 2.1×	27 1.0×	21	434
Noha Radwan United States	3	323 0.8×	124 0.5×	194 1.0×	34 1.1×	63 2.3×	10	382
Kangle Deng United States	4	425 1.1×	152 0.6×	243 1.3×	45 1.5×	90 3.2×	5	509
Pierre-Yves Laffont France	9	356 0.9×	36 0.1×	118 0.6×	21 0.7×	19 0.7×	21	433

Countries citing papers authored by Aaron Sarna

Since Specialization

Citations

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

Fields of papers citing papers by Aaron Sarna

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aaron Sarna

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

All Works

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9 of 9 papers shown

1.

Sarna, Aaron, et al.. (2025). Benchmarking and improving algorithms for attributing satellite-observed contrails to flights. Atmospheric measurement techniques. 18(14). 3495–3532. 1 indexed citations

2.

Geraedts, Scott, Thomas Dean, Sebastian D. Eastham, et al.. (2023). A scalable system to measure contrail formation on a per-flight basis. Environmental Research Communications. 6(1). 15008–15008. 13 indexed citations

3.

Ng, Joe Yue-Hei, et al.. (2023). Contrail Detection on GOES-16 ABI With the OpenContrails Dataset. IEEE Transactions on Geoscience and Remote Sensing. 62. 1–14. 6 indexed citations

4.

Chen, Christina, Aaron Sarna, Charles T. Lau, et al.. (2022). Simplified Transfer Learning for Chest Radiography Models Using Less Data. Radiology. 305(2). 454–465. 30 indexed citations

5.

Genova, Kyle, Forrester Cole, Avneesh Sud, Aaron Sarna, & Thomas Funkhouser. (2020). Local Deep Implicit Functions for 3D Shape. 4856–4865. 229 indexed citations breakdown →

6.

Genova, Kyle, Forrester Cole, Avneesh Sud, Aaron Sarna, & Thomas Funkhouser. (2019). Deep Structured Implicit Functions. arXiv (Cornell University). 10 indexed citations

7.

Krishnan, Dilip, et al.. (2019). Boundless: Generative Adversarial Networks for Image Extension. 10520–10529. 47 indexed citations

8.

Genova, Kyle, et al.. (2018). Unsupervised Training for 3D Morphable Model Regression. 8377–8386. 174 indexed citations

9.

Cole, Forrester, David Belanger, Dilip Krishnan, et al.. (2017). Face Synthesis from Facial Identity Features.. arXiv (Cornell University). 7 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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