Dustin Lange
- Artificial Intelligence top 5%
- Management Science and Operations Research top 5%
- Information Systems top 10%
- Signal Processing top 10%
- Management Information Systems top 10%
- Co-authors
- Sebastian SchelterFelix BießmannPhilipp SchmidtDavid SalinasFelix NaumannChristoph BöhmPhillipp SchmidtValentín Flunkert
- Topics
- Data Quality and Management (10 papers)Data Management and Algorithms (6 papers)Advanced Database Systems and Queries (5 papers)
- Journals
- Journal of Machine Learning ResearchProceedings of the VLDB EndowmentJournal of Head Trauma Rehabilitation
- Partner nations
- GermanyIsraelUnited States
In The Last Decade
Dustin Lange
16 papers receiving 410 citations
Peers
Comparison fields: 5 of 83
- Artificial Intelligence 269
- Management Science and Operations Research 188
- Information Systems 84
- Signal Processing 76
- Management Information Systems 51
Countries citing papers authored by Dustin Lange
This map shows the geographic impact of Dustin Lange'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 Dustin Lange with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dustin Lange more than expected).
Fields of papers citing papers by Dustin Lange
This network shows the impact of papers produced by Dustin Lange. 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 Dustin Lange. The network helps show where Dustin Lange may publish in the future.
Co-authorship network of co-authors of Dustin Lange
This figure shows the co-authorship network connecting the top 25 collaborators of Dustin Lange. A scholar is included among the top collaborators of Dustin Lange 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 Dustin Lange. Dustin Lange is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Automated data validation in machine learning systems | 15 |
| 2 | 7 | |
| 3 | Towards Automated ML Model Monitoring: Measure, Improve and Quantify Data Quality | 3 |
| 4 | DataWig: Missing Value Imputation for Tables | 67 |
| 5 | 11 | |
| 6 | 10 | |
| 7 | 46 | |
| 8 | 130 | |
| 9 | DEEQU - Data Quality Validation for Machine Learning Pipelines | 5 |
| 10 | 78 | |
| 11 | 10 | |
| 12 | 0 | |
| 13 | 0 | |
| 14 | 19 | |
| 15 | 7 | |
| 16 | 6 | |
| 17 | 1 | |
| 18 | 31 |
About Dustin Lange
Dustin Lange is a scholar working on Management Science and Operations Research, Signal Processing and Artificial Intelligence, having authored 18 papers that have together received 446 indexed citations. Recurring topics across this work include Data Quality and Management (10 papers), Data Management and Algorithms (6 papers) and Advanced Database Systems and Queries (5 papers). The work is most often cited by research in Management Science and Operations Research (188 citations), Artificial Intelligence (269 citations) and Signal Processing (76 citations). Dustin Lange has collaborated with scholars based in Germany, Israel and United States. Frequent co-authors include Sebastian Schelter, Felix Bießmann, Philipp Schmidt, David Salinas, Felix Naumann, Christoph Böhm, Phillipp Schmidt, Valentín Flunkert, Matthias Seeger and Tim Januschowski. Their work appears in journals such as Journal of Machine Learning Research, Proceedings of the VLDB Endowment and Journal of Head Trauma Rehabilitation.
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.