D. Poznanski

14.0k total citations · 2 hit papers
55 papers, 2.4k citations indexed

About

D. Poznanski is a scholar working on Astronomy and Astrophysics, Nuclear and High Energy Physics and Instrumentation. According to data from OpenAlex, D. Poznanski has authored 55 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 49 papers in Astronomy and Astrophysics, 16 papers in Nuclear and High Energy Physics and 5 papers in Instrumentation. Recurrent topics in D. Poznanski's work include Gamma-ray bursts and supernovae (39 papers), Stellar, planetary, and galactic studies (20 papers) and Galaxies: Formation, Evolution, Phenomena (15 papers). D. Poznanski is often cited by papers focused on Gamma-ray bursts and supernovae (39 papers), Stellar, planetary, and galactic studies (20 papers) and Galaxies: Formation, Evolution, Phenomena (15 papers). D. Poznanski collaborates with scholars based in United States, Israel and United Kingdom. D. Poznanski's co-authors include J. S. Bloom, A. V. Filippenko, M. Ganeshalingam, J. X. Prochaska, Weidong Li, R. Chornock, Dalya Baron, J. M. Silverman, M. Modjaz and R. J. Foley and has published in prestigious journals such as Nature, Science and The Astrophysical Journal.

In The Last Decade

D. Poznanski

50 papers receiving 2.3k citations

Hit Papers

Nearby supernova rates from the Lick Observatory Supernov... 2011 2026 2016 2021 2011 2017 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
D. Poznanski United States 27 2.3k 811 269 51 46 55 2.4k
N. Butler United States 23 1.7k 0.7× 403 0.5× 229 0.9× 35 0.7× 75 1.6× 84 1.8k
Yin-Zhe Ma South Africa 25 1.8k 0.8× 928 1.1× 235 0.9× 25 0.5× 23 0.5× 98 1.9k
N. Aghanim France 27 2.3k 1.0× 1.2k 1.4× 244 0.9× 30 0.6× 23 0.5× 80 2.4k
M. Liguori Italy 24 1.8k 0.8× 857 1.1× 133 0.5× 31 0.6× 15 0.3× 57 1.9k
Brice Ménard United States 22 1.3k 0.6× 312 0.4× 382 1.4× 43 0.8× 23 0.5× 44 1.5k
Subo Dong United States 27 2.3k 1.0× 312 0.4× 537 2.0× 39 0.8× 133 2.9× 105 2.4k
L. Denneau United States 20 2.0k 0.8× 223 0.3× 322 1.2× 31 0.6× 110 2.4× 78 2.1k
E. Pierpaoli United States 26 1.7k 0.7× 1.0k 1.3× 267 1.0× 27 0.5× 16 0.3× 74 2.0k
Donald P. Schneider United States 26 1.9k 0.8× 368 0.5× 649 2.4× 22 0.4× 46 1.0× 38 2.0k
Lado Samushia United States 21 2.4k 1.0× 1.2k 1.5× 457 1.7× 58 1.1× 35 0.8× 37 2.5k

Countries citing papers authored by D. Poznanski

Since Specialization
Citations

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

Fields of papers citing papers by D. Poznanski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of D. Poznanski

This figure shows the co-authorship network connecting the top 25 collaborators of D. Poznanski. A scholar is included among the top collaborators of D. Poznanski 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 D. Poznanski. D. Poznanski 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.
Pardo, S., D. Poznanski, S. Croft, Andrew Siemion, & Matt Lebofsky. (2025). Using Anomaly Detection to Search for Technosignatures in Breakthrough Listen Observations. The Astronomical Journal. 170(1). 12–12.
2.
Sneppen, Albert, D. Watson, Andreas Bauswein, et al.. (2023). Spherical symmetry in the kilonova AT2017gfo/GW170817. Nature. 614(7948). 436–439. 32 indexed citations
3.
Arcavi, I., D. A. Howell, C. McCully, et al.. (2017). LIGO/Virgo G298048: Rapid Evolution of Possible Counterpart. GRB Coordinates Network. 21581. 1. 1 indexed citations
4.
Arcavi, I., D. A. Howell, C. McCully, et al.. (2017). LIGO/Virgo G298048: Las Cumbres Observatory Detection of The Possible Optical Counterpart in NGC 4993. GRB Coordinates Network. 21538. 1. 1 indexed citations
5.
Poznanski, D., et al.. (2017). The effect of interstellar absorption on measurements of the baryon acoustic peak in the Lyman α forest. Monthly Notices of the Royal Astronomical Society. 472(1). 799–807.
6.
Baron, Dalya & D. Poznanski. (2016). The weirdest SDSS galaxies: results from an outlier detection algorithm. Monthly Notices of the Royal Astronomical Society. 465(4). 4530–4555. 80 indexed citations
7.
Poznanski, D., Z. Kostrzewa-Rutkowska, Ł. Wyrzykowski, & N. Blagorodnova. (2015). Bright but slow – Type II supernovae from OGLE-IV – implications for magnitude-limited surveys. Monthly Notices of the Royal Astronomical Society. 449(2). 1753–1759. 1 indexed citations
8.
Graur, Or, et al.. (2014). Spectroscopic identification of a redshift 1.55 supernova host galaxy from the Subaru Deep Field Supernova Survey. Springer Link (Chiba Institute of Technology). 3 indexed citations
9.
Ben-Ami, Sagi, A. Gal‐Yam, P. A. Mazzali, et al.. (2014). SN 2010MB: DIRECT EVIDENCE FOR A SUPERNOVA INTERACTING WITH A LARGE AMOUNT OF HYDROGEN-FREE CIRCUMSTELLAR MATERIAL. The Astrophysical Journal. 785(1). 37–37. 18 indexed citations
10.
Polishook, David, E. O. Ofek, S. R. Kulkarni, et al.. (2012). Asteroid rotation periods from the Palomar Transient Factory survey. Monthly Notices of the Royal Astronomical Society. 421(3). 2094–2108. 16 indexed citations
11.
Poznanski, D., J. X. Prochaska, & J. S. Bloom. (2012). An empirical relation between sodium absorption and dust extinction. Monthly Notices of the Royal Astronomical Society. 426(2). 1465–1474. 187 indexed citations
12.
Lidman, C., J. Stuart B. Wyithe, J. R. Mould, et al.. (2012). Near-infrared observations of type Ia supernovae: The best known \n standard candle for cosmology. CaltechAUTHORS (California Institute of Technology). 20 indexed citations
13.
Cao, Y., M. M. Kasliwal, James D. Neill, et al.. (2012). CLASSICAL NOVAE IN ANDROMEDA: LIGHT CURVES FROM THE PALOMAR TRANSIENT FACTORY ANDGALEX. The Astrophysical Journal. 752(2). 133–133. 32 indexed citations
14.
Arcavi, I., A. Gal‐Yam, David Polishook, et al.. (2011). PTF11eon/SN2011dh is Possibly a Type IIb Event. The astronomer's telegram. 3413. 1. 1 indexed citations
15.
Quimby, R., M. M. Kasliwal, S. B. Cenko, et al.. (2009). Supernovae 2009cb, 2009cg-2009cx; Psn K0903-1, K0903-2, K0903-1; Variable Stars. 1754. 1.
16.
Chornock, R., R. J. Foley, A. V. Filippenko, et al.. (2008). XRB 080109/SN 2008D: early decline in brightness and change in.. GRB Coordinates Network. 7176. 1.
17.
Perley, D. A., J. S. Bloom, M. Modjaz, D. Poznanski, & C. C. Thoene. (2007). GRB 070429B: probable host galaxy and redshift.. GCN. 7140. 1. 3 indexed citations
18.
Prochaska, J. X., et al.. (2007). GRB 071010B: Keck/LRIS spectroscopy.. GRB Coordinates Network. 6864. 1. 3 indexed citations
19.
Apellániz, J. Maíz, Howard E. Bond, M. H. Siegel, et al.. (2004). The Progenitor of the Type II-P SN 2004dj in NGC 2403. The Astrophysical Journal. 615(2). L113–L116. 41 indexed citations
20.
Poznanski, D., A. Gal‐Yam, Keren Sharon, et al.. (2003). Supernovae 2003B, 2003Q, 2003R, 2003S, and 2003T. IAUC. 8058. 1. 1 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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