Hossen Teimoorinia

1.5k total citations
32 papers, 965 citations indexed

About

Hossen Teimoorinia is a scholar working on Astronomy and Astrophysics, Instrumentation and Electrical and Electronic Engineering. According to data from OpenAlex, Hossen Teimoorinia has authored 32 papers receiving a total of 965 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Astronomy and Astrophysics, 16 papers in Instrumentation and 6 papers in Electrical and Electronic Engineering. Recurrent topics in Hossen Teimoorinia's work include Galaxies: Formation, Evolution, Phenomena (20 papers), Astronomy and Astrophysical Research (16 papers) and Stellar, planetary, and galactic studies (9 papers). Hossen Teimoorinia is often cited by papers focused on Galaxies: Formation, Evolution, Phenomena (20 papers), Astronomy and Astrophysical Research (16 papers) and Stellar, planetary, and galactic studies (9 papers). Hossen Teimoorinia collaborates with scholars based in Canada, United States and United Kingdom. Hossen Teimoorinia's co-authors include Sara L. Ellison, Asa F. L. Bluck, Mallory Thorp, Jorge Moreno, J. Trevor Mendel, Connor Bottrell, S. F. Sánchez, David R. Patton, Luc Simard and R. Maiolino and has published in prestigious journals such as The Astrophysical Journal, Scientific Reports and Monthly Notices of the Royal Astronomical Society.

In The Last Decade

Hossen Teimoorinia

30 papers receiving 907 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hossen Teimoorinia Canada 16 859 505 94 57 56 32 965
H. Domínguez Sánchez Spain 18 897 1.0× 595 1.2× 129 1.4× 57 1.0× 75 1.3× 39 1.0k
Sandor Kruk United Kingdom 19 739 0.9× 390 0.8× 119 1.3× 52 0.9× 98 1.8× 39 899
Rebecca Smethurst United Kingdom 24 969 1.1× 539 1.1× 136 1.4× 76 1.3× 105 1.9× 35 1.1k
Connor Bottrell Canada 17 860 1.0× 513 1.0× 169 1.8× 49 0.9× 60 1.1× 45 974
Joanna Woo Canada 18 1.2k 1.4× 754 1.5× 58 0.6× 83 1.5× 59 1.1× 27 1.2k
Preethi Nair United States 13 730 0.8× 433 0.9× 88 0.9× 52 0.9× 68 1.2× 20 792
M. Treyer France 16 746 0.9× 342 0.7× 43 0.5× 83 1.5× 62 1.1× 27 800
Jean Coupon Switzerland 17 789 0.9× 413 0.8× 46 0.5× 101 1.8× 68 1.2× 26 830
Shiyin Shen China 16 1.3k 1.5× 758 1.5× 54 0.6× 133 2.3× 76 1.4× 71 1.3k
Jillian M. Scudder United States 14 1.1k 1.2× 597 1.2× 96 1.0× 68 1.2× 37 0.7× 24 1.1k

Countries citing papers authored by Hossen Teimoorinia

Since Specialization
Citations

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

Fields of papers citing papers by Hossen Teimoorinia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hossen Teimoorinia

This figure shows the co-authorship network connecting the top 25 collaborators of Hossen Teimoorinia. A scholar is included among the top collaborators of Hossen Teimoorinia 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 Hossen Teimoorinia. Hossen Teimoorinia 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.
Gulliver, T. Aaron, et al.. (2025). Adaptive Machine Learning for Automatic Load Optimization in Connected Smart Green Townhouses. Algorithms. 18(3). 132–132. 1 indexed citations
2.
Woo, Joanna, et al.. (2024). Stellar populations with optical spectra: deep learning versus popular spectrum fitting codes. Monthly Notices of the Royal Astronomical Society. 530(4). 4260–4276. 12 indexed citations
3.
Gulliver, T. Aaron, et al.. (2024). Load Optimization for Connected Modern Buildings Using Deep Hybrid Machine Learning in Island Mode. Energies. 17(24). 6475–6475. 2 indexed citations
4.
Gulliver, T. Aaron, et al.. (2024). Resource Optimization for Grid-Connected Smart Green Townhouses Using Deep Hybrid Machine Learning. Energies. 17(23). 6201–6201. 5 indexed citations
5.
Teimoorinia, Hossen, et al.. (2024). Revisiting Active Galactic Nucleus Placement on the Baldwin, Phillips, and Terlevich Diagram: A Spectral Decomposition Approach. The Astrophysical Journal. 973(2). 95–95. 1 indexed citations
6.
Fabbro, S., et al.. (2023). Mitigating the nonlinearities in a pyramid wavefront sensor. Journal of Astronomical Telescopes Instruments and Systems. 9(4). 4 indexed citations
7.
Teimoorinia, Hossen, et al.. (2022). Mapping the Diversity of Galaxy Spectra with Deep Unsupervised Machine Learning. The Astronomical Journal. 163(2). 71–71. 16 indexed citations
8.
Bottrell, Connor, Maan H Hani, Sara L. Ellison, et al.. (2021). Convolutional neural network identification of galaxy post-mergers in UNIONS using IllustrisTNG. Monthly Notices of the Royal Astronomical Society. 504(1). 372–392. 54 indexed citations
9.
Bottrell, Connor, Maan H Hani, Hossen Teimoorinia, David R. Patton, & Sara L. Ellison. (2021). The combined and respective roles of imaging and stellar kinematics in identifying galaxy merger remnants. Monthly Notices of the Royal Astronomical Society. 511(1). 100–119. 27 indexed citations
10.
Čuperlović‐Culf, Miroslava, Emma Cunningham, Hossen Teimoorinia, et al.. (2021). Metabolomics and computational analysis of the role of monoamine oxidase activity in delirium and SARS-COV-2 infection. Scientific Reports. 11(1). 10629–10629. 18 indexed citations
11.
Francesco, James Di, et al.. (2019). CLOVER: Convnet Line-fitting Of Velocities in Emission-line Regions. The Astrophysical Journal. 885(1). 32–32. 3 indexed citations
12.
Francesco, James Di, et al.. (2019). CLOVER: Convolutional neural network spectra identifier and kinematics predictor. Astrophysics Source Code Library. 1 indexed citations
13.
Bluck, Asa F. L., Connor Bottrell, Hossen Teimoorinia, et al.. (2019). What shapes a galaxy? – unraveling the role of mass, environment, and star formation in forming galactic structure. Monthly Notices of the Royal Astronomical Society. 485(1). 666–696. 50 indexed citations
14.
Bottrell, Connor, Maan H Hani, Hossen Teimoorinia, et al.. (2019). Deep learning predictions of galaxy merger stage and the importance of observational realism. Monthly Notices of the Royal Astronomical Society. 490(4). 5390–5413. 84 indexed citations
15.
Ellison, Sara L., Mallory Thorp, Lihwai Lin, et al.. (2019). The ALMaQUEST survey – III. Scatter in the resolved star-forming main sequence is primarily due to variations in star formation efficiency. Monthly Notices of the Royal Astronomical Society Letters. 493(1). L39–L43. 53 indexed citations
16.
Teimoorinia, Hossen, et al.. (2018). Classifying galaxy spectra at 0.5 < z < 1 with self-organizing maps. Monthly Notices of the Royal Astronomical Society. 14 indexed citations
17.
Teimoorinia, Hossen, Asa F. L. Bluck, & Sara L. Ellison. (2016). An artificial neural network approach for ranking quenching parameters in central galaxies. Monthly Notices of the Royal Astronomical Society. 457(2). 2086–2106. 50 indexed citations
18.
Teimoorinia, Hossen. (2012). SPECTRAL CLASSIFICATION OF GALAXIES AT 0.5 ⩽z⩽ 1 IN THE CDFS: THE ARTIFICIAL NEURAL NETWORK APPROACH. The Astronomical Journal. 144(6). 172–172. 11 indexed citations
19.
Balestra, I., V. Mainieri, P. Popesso, et al.. (2010). The Great Observatories Origins Deep Survey. Astronomy and Astrophysics. 512. A12–A12. 127 indexed citations
20.
Fosbury, R. A. E., et al.. (2009). Ly$\mathsf{\alpha}$ emitters in the GOODS-S field. Astronomy and Astrophysics. 510. A109–A109. 26 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by H. Domínguez Sánchez Breakdown of academic impact, for papers by Sandor Kruk Breakdown of academic impact, for papers by Rebecca Smethurst Breakdown of academic impact, for papers by Connor Bottrell Breakdown of academic impact, for papers by Joanna Woo Breakdown of academic impact, for papers by Preethi Nair Breakdown of academic impact, for papers by M. Treyer Breakdown of academic impact, for papers by Jean Coupon Breakdown of academic impact, for papers by Shiyin Shen Breakdown of academic impact, for papers by Jillian M. Scudder
Rankless by CCL
2026