Justin Heinermann
- Electrical and Electronic Engineering
- Artificial Intelligence top 10%
- Aerospace Engineering
- Environmental Engineering
- Computer Vision and Pattern Recognition
- Topics
- Energy Load and Power Forecasting (3 papers)Computational Physics and Python Applications (2 papers)Advanced Image and Video Retrieval Techniques (1 paper)
- Journals
- Renewable EnergyResearch at the University of Copenhagen (University of Copenhagen)National Conference on Artificial Intelligence
In The Last Decade
Justin Heinermann
4 papers receiving 233 citations
Peers
Comparison fields: 5 of 65
- Electrical and Electronic Engineering 152
- Artificial Intelligence 98
- Aerospace Engineering 50
- Environmental Engineering 35
- Computer Vision and Pattern Recognition 26
Countries citing papers authored by Justin Heinermann
This map shows the geographic impact of Justin Heinermann'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 Justin Heinermann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Justin Heinermann more than expected).
Fields of papers citing papers by Justin Heinermann
This network shows the impact of papers produced by Justin Heinermann. 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 Justin Heinermann. The network helps show where Justin Heinermann may publish in the future.
Co-authorship network of co-authors of Justin Heinermann
This figure shows the co-authorship network connecting the top 25 collaborators of Justin Heinermann. A scholar is included among the top collaborators of Justin Heinermann 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 Justin Heinermann. Justin Heinermann is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | On Heterogeneous Machine Learning Ensembles for Wind Power Prediction. | 6 |
| 2 | Comparison of Numerical Models and Statistical Learning for Wind Speed Prediction. | 8 |
| 3 | 192 | |
| 4 | Buffer k-d Trees: Processing Massive Nearest Neighbor Queries on GPUs | 39 |
About Justin Heinermann
Justin Heinermann is a scholar working on Environmental Engineering, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 4 papers that have together received 245 indexed citations. Recurring topics across this work include Energy Load and Power Forecasting (3 papers), Computational Physics and Python Applications (2 papers) and Advanced Image and Video Retrieval Techniques (1 paper). The work is most often cited by research in Artificial Intelligence (98 citations), Electrical and Electronic Engineering (152 citations) and Environmental Engineering (35 citations). Justin Heinermann has collaborated with scholars based in Germany and Denmark. Frequent co-authors include Oliver Krämer, Cosmin E. Oancea, Fabian Gieseke, Christian Igel and Lueder von Bremen. Their work appears in journals such as Renewable Energy, Research at the University of Copenhagen (University of Copenhagen) and National Conference on Artificial Intelligence.
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.