Károly Héberger
Impact in
- Analytical Chemistry top 0.1%
- Spectroscopy and Chemometric Analyses
- Computational Theory and Mathematics top 0.1%
- Computational Drug Discovery Methods
Papers in
-
- Spectroscopy and Chemometric Analyses 33
- Spectroscopy 58
- Analytical Chemistry and Chromatography 52
- Co-authors
- Anita RáczDávid BajuszRosa M. Alonso‐SalcesLuis Á. BerruetaK. Kollár‐HunekMiklós GörgényiFabiano RenieroClaude Guillou
In The Last Decade
Károly Héberger
167 papers receiving 7.3k citations
Hit Papers
Peers
Comparison fields: 5 of 199
- Analytical Chemistry 1.8k
- Computational Theory and Mathematics 1.9k
- Spectroscopy 1.8k
- Biochemistry 326
- Organic Chemistry 1.4k
Countries citing papers authored by Károly Héberger
This map shows the geographic impact of Károly Héberger'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 Károly Héberger with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Károly Héberger more than expected).
Fields of papers citing papers by Károly Héberger
This network shows the impact of papers produced by Károly Héberger. 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 Károly Héberger. The network helps show where Károly Héberger may publish in the future.
Co-authors
The 25 scholars most cited alongside Károly Héberger, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2024 | 1 | |
| 3 | 2023 | 5 | |
| 4 | 2022 | 11 | |
| 5 | 2022 | 30 | |
| 6 | 2021 | 14 | |
| 7 | Effect of Dataset Size and Train/Test Split Ratios in QSAR/QSPR Multiclass Classification Hit paper breakdown → | 2021 | 199 |
| 8 | 2021 | 2 | |
| 9 | 2020 | 11 | |
| 10 | 2019 | 2 | |
| 11 | 2019 | 21 | |
| 12 | 2018 | 16 | |
| 13 | 2018 | 13 | |
| 14 | 2017 | 35 | |
| 15 | 2016 | 10 | |
| 16 | 2015 | 23 | |
| 17 | 2015 | 32 | |
| 18 | 2015 | 11 | |
| 19 | 2012 | 8 | |
| 20 | Determination of the Gibbs free energy of one methylene unit from Kováts retention index-boiling point correlations on DB-210 stationary phase | 1999 | 3 |
About Károly Héberger
Károly Héberger is a scholar working on Analytical Chemistry, Spectroscopy, Computational Theory and Mathematics, Organic Chemistry and Statistics and Probability, having authored 168 papers that have together received 7.5k indexed citations. Recurring topics across this work include Analytical Chemistry and Chromatography (52 papers), Computational Drug Discovery Methods (48 papers), Spectroscopy and Chemometric Analyses (33 papers), Chemical Thermodynamics and Molecular Structure (29 papers), Advanced Chemical Sensor Technologies (23 papers), Free Radicals and Antioxidants (19 papers), Advanced Statistical Methods and Models (10 papers) and Multi-Criteria Decision Making (9 papers). The work is most often cited by research in Analytical Chemistry (1.8k citations), Computational Theory and Mathematics (1.9k citations), Spectroscopy (1.8k citations), Biochemistry (326 citations) and Organic Chemistry (1.4k citations). Károly Héberger has collaborated with scholars based in Hungary, Poland and Italy. Frequent co-authors include Anita Rácz, Dávid Bajusz, Rosa M. Alonso‐Salces, Luis Á. Berrueta, K. Kollár‐Hunek, Miklós Görgényi, Fabiano Reniero, Claude Guillou, Orsolya Farkas and Hanns Fischer. Their work appears in journals such as Journal of Chromatography A, Analytica Chimica Acta, Chemometrics and Intelligent Laboratory Systems, Berichte der Bunsengesellschaft für physikalische Chemie and Chromatographia.
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.