Jakob Richter
- Environmental Engineering top 5%
- Artificial Intelligence top 5%
- Machine Learning and Data Classification 6
- Metaheuristic Optimization Algorithms Research 2
- Data Analysis with R 2
- Ecological Modeling top 10%
-
- Advanced Multi-Objective Optimization Algorithms 4
-
- Reproductive Biology and Fertility 2
-
- Cardiovascular Function and Risk Factors 2
-
- Sperm and Testicular Function 2
-
- Advanced MRI Techniques and Applications 2
- Co-authors
- Patrick SchratzMichel LangBernd BischlJannes MuenchowEugenia IturritxaAlexander BrenningStefan CoorsMartin Binder
- Partner nations
- GermanyUnited StatesSpain
In The Last Decade
Jakob Richter
18 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 176
- Environmental Engineering 168
- Artificial Intelligence 306
- Ecological Modeling 37
- Health Informatics 10
- Health Information Management 32
Countries citing papers authored by Jakob Richter
This map shows the geographic impact of Jakob Richter'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 Jakob Richter with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jakob Richter more than expected).
Fields of papers citing papers by Jakob Richter
This network shows the impact of papers produced by Jakob Richter. 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 Jakob Richter. The network helps show where Jakob Richter may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jakob Richter, 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 | 0 | |
| 2 | 2025 | 4 | |
| 3 | 2024 | 6 | |
| 4 | 2024 | 5 | |
| 5 | 2023 | 36 | |
| 6 | Hyperparameter optimization: Foundations, algorithms, best practices, and open challengesbreakdown → | 2023 | 398 |
| 7 | 2022 | 5 | |
| 8 | 2021 | 5 | |
| 9 | 2020 | 3 | |
| 10 | Define and Work with Parameter Spaces for Complex Algorithms [R package paradox version 0.6.0] | 2020 | 1 |
| 11 | 2019 | 235 | |
| 12 | Hyperparameter tuning and performance assessment of statistical and machine-learning algorithms using spatial databreakdown → | 2019 | 367 |
| 13 | 2019 | 3 | |
| 14 | 2016 | 4 | |
| 15 | 2016 | 1 | |
| 16 | Machine Learning in R | 2015 | 7 |
| 17 | 2014 | 37 | |
| 18 | 2013 | 200 | |
| 19 | 1988 | 7 |
About Jakob Richter
Jakob Richter is a scholar working on Computational Theory and Mathematics, Statistics and Probability and Reproductive Medicine, having authored 19 papers that have together received 1.3k indexed citations. Recurring topics across this work include Machine Learning and Data Classification (6 papers), Advanced Multi-Objective Optimization Algorithms (4 papers), Reproductive Biology and Fertility (2 papers), Cardiovascular Function and Risk Factors (2 papers), Sperm and Testicular Function (2 papers), Advanced MRI Techniques and Applications (2 papers), Metaheuristic Optimization Algorithms Research (2 papers) and Data Analysis with R (2 papers). The work is most often cited by research in Environmental Engineering (168 citations), Artificial Intelligence (306 citations) and Ecological Modeling (37 citations). Jakob Richter has collaborated with scholars based in Germany, United States and Spain. Frequent co-authors include Patrick Schratz, Michel Lang, Bernd Bischl, Jannes Muenchow, Eugenia Iturritxa, Alexander Brenning, Stefan Coors, Martin Binder, Lars Kotthoff and Giuseppe Casalicchio. Their work appears in journals such as Bioinformatics, Machine Learning and Ecological Modelling.
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.