Philipp Seidl

434 total citations
8 papers, 157 citations indexed

About

Philipp Seidl is a scholar working on Artificial Intelligence, Materials Chemistry and Molecular Biology. According to data from OpenAlex, Philipp Seidl has authored 8 papers receiving a total of 157 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 3 papers in Materials Chemistry and 2 papers in Molecular Biology. Recurrent topics in Philipp Seidl's work include Machine Learning in Materials Science (3 papers), Machine Learning in Healthcare (2 papers) and Computational Drug Discovery Methods (2 papers). Philipp Seidl is often cited by papers focused on Machine Learning in Materials Science (3 papers), Machine Learning in Healthcare (2 papers) and Computational Drug Discovery Methods (2 papers). Philipp Seidl collaborates with scholars based in Austria, United States and United Kingdom. Philipp Seidl's co-authors include Sepp Hochreiter, Günter Klambauer, Marwin Segler, Hubert Ramsauer, Michael Widrich, Thomas Adler, Michael Kopp, David P. Kreil, Johannes M. Lehner and Lukas Gruber and has published in prestigious journals such as Anesthesia & Analgesia, Journal of Chemical Information and Modeling and Faraday Discussions.

In The Last Decade

Philipp Seidl

8 papers receiving 153 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Philipp Seidl Austria	4	79	44	38	33	26	8	157
Krzysztof Maziarz United Kingdom	4	85 1.1×	24 0.5×	22 0.6×	49 1.5×	11 0.4×	7	153
Niv Giladi Israel	2	76 1.0×	20 0.5×	17 0.4×	73 2.2×	8 0.3×	3	162
Xiaoyang Qu China	10	119 1.5×	31 0.7×	21 0.6×	29 0.9×	22 0.8×	53	260
Shiyang Chen China	8	48 0.6×	11 0.3×	9 0.2×	45 1.4×	6 0.2×	27	146
Jiangtong Li China	10	165 2.1×	14 0.3×	14 0.4×	160 4.8×	8 0.3×	16	266
Zheng Fang China	5	45 0.6×	9 0.2×	7 0.2×	20 0.6×	10 0.4×	14	93
Moritoshi Yasunaga Japan	6	49 0.6×	4 0.1×	15 0.4×	13 0.4×	17 0.7×	46	118
Meiqin Wang China	11	302 3.8×	63 1.4×	13 0.3×	234 7.1×	20 0.8×	77	416
Meicheng Liu China	7	101 1.3×	11 0.3×	15 0.4×	41 1.2×	3 0.1×	20	138
Xinwei Zhao China	9	35 0.4×	9 0.2×	30 0.8×	286 8.7×	25 1.0×	18	353

Countries citing papers authored by Philipp Seidl

Since Specialization

Citations

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

Fields of papers citing papers by Philipp Seidl

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Philipp Seidl

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

8 of 8 papers shown

1.

Tschoellitsch, Thomas, Philipp Moser, Philipp Seidl, et al.. (2024). Machine learning prediction of unexpected readmission or death after discharge from intensive care: A retrospective cohort study. Journal of Clinical Anesthesia. 99. 111654–111654. 2 indexed citations

2.

Maziarz, Krzysztof, et al.. (2024). Re-evaluating retrosynthesis algorithms with Syntheseus. Faraday Discussions. 256(0). 568–586. 18 indexed citations

3.

Tschoellitsch, Thomas, Philipp Moser, Philipp Seidl, et al.. (2024). Potential Predictors for Deterioration of Renal Function After Transfusion. Anesthesia & Analgesia. 138(3). 645–654. 1 indexed citations

4.

Tschoellitsch, Thomas, Philipp Seidl, Carl Böck, et al.. (2023). Using emergency department triage for machine learning-based admission and mortality prediction. European Journal of Emergency Medicine. 30(6). 408–416. 10 indexed citations

5.

Seidl, Philipp, et al.. (2022). Supervised Machine Learning Classification for Short Straddles on the S&P500. Risks. 10(12). 235–235. 2 indexed citations

6.

Seidl, Philipp, Philipp Renz, Natalia Dyubankova, et al.. (2022). Improving Few- and Zero-Shot Reaction Template Prediction Using Modern Hopfield Networks. Journal of Chemical Information and Modeling. 62(9). 2111–2120. 46 indexed citations

7.

Seidl, Philipp, Philipp Renz, Natalia Dyubankova, et al.. (2021). Modern Hopfield Networks for Few- and Zero-Shot Reaction Prediction.. arXiv (Cornell University). 1 indexed citations

8.

Ramsauer, Hubert, Johannes M. Lehner, Philipp Seidl, et al.. (2021). Hopfield Networks is All You Need. 77 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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