Will Gersch
Impact in
- Signal Processing top 2%
- Blind Source Separation Techniques
Papers in
-
- Time Series Analysis and Forecasting 9
- Co-authors
- Genshiro Kitagawa (14 shared papers)Gyo Kitagawa (3 shared papers)Graham V. Goddard (1 shared paper)Daniel Sharpe (1 shared paper)Douglas A. Foutch (1 shared paper)Hirotugu Akaike (1 shared paper)N. Norby Nielsen (1 shared paper)Eugene Dong (3 shared papers)
- Journals
- IEEE Transactions on Automatic Control (7 papers)Journal of Sound and Vibration (6 papers)The Journal of the Acoustical Society of America (3 papers)Journal of Business and Economic Statistics (2 papers)Mathematical Biosciences (2 papers)
- Partner nations
- United StatesJapanCanada
In The Last Decade
Will Gersch
61 papers receiving 2.0k citations
Peers
Comparison fields: 5 of 131
- Signal Processing 437
- Statistics, Probability and Uncertainty 185
- Statistics and Probability 178
- Control and Systems Engineering 464
- Civil and Structural Engineering 420
Countries citing papers authored by Will Gersch
This map shows the geographic impact of Will Gersch'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 Will Gersch with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Will Gersch more than expected).
Fields of papers citing papers by Will Gersch
This network shows the impact of papers produced by Will Gersch. 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 Will Gersch. The network helps show where Will Gersch may publish in the future.
Co-authors
The 22 scholars most cited alongside Will Gersch, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 65 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1996 | 426 | |
| 2 | 1985 | 202 | |
| 3 | 1984 | 197 | |
| 4 | 1970 | 128 | |
| 5 | 1970 | 100 | |
| 6 | 1983 | 84 | |
| 7 | 1984 | 81 | |
| 8 | 1970 | 77 | |
| 9 | 1973 | 68 | |
| 10 | 1977 | 61 | |
| 11 | 1973 | 56 | |
| 12 | 1985 | 54 | |
| 13 | 1972 | 51 | |
| 14 | 1985 | 48 | |
| 15 | 1983 | 47 | |
| 16 | 1977 | 47 | |
| 17 | 1974 | 46 | |
| 18 | 1976 | 42 | |
| 19 | 1974 | 38 | |
| 20 | 1970 | 36 |
About Will Gersch
Will Gersch is a scholar working on Signal Processing, Statistics and Probability, Control and Systems Engineering, Applied Mathematics and Civil and Structural Engineering, having authored 65 papers that have together received 2.3k indexed citations. Recurring topics across this work include Structural Health Monitoring Techniques (12 papers), Fault Detection and Control Systems (10 papers), Time Series Analysis and Forecasting (9 papers), Control Systems and Identification (8 papers), EEG and Brain-Computer Interfaces (8 papers), Forecasting Techniques and Applications (8 papers), Statistical and numerical algorithms (7 papers) and Complex Systems and Time Series Analysis (6 papers). The work is most often cited by research in Signal Processing (437 citations), Statistics, Probability and Uncertainty (185 citations), Statistics and Probability (178 citations), Control and Systems Engineering (464 citations) and Civil and Structural Engineering (420 citations). Will Gersch has collaborated with scholars based in United States, Japan and Canada. Frequent co-authors include Genshiro Kitagawa, Gyo Kitagawa, Graham V. Goddard, Daniel Sharpe, Douglas A. Foutch, Hirotugu Akaike, N. Norby Nielsen, Eugene Dong, T. Brotherton and Paul Naitoh. Their work appears in journals such as IEEE Transactions on Automatic Control, Journal of Sound and Vibration, The Journal of the Acoustical Society of America, Journal of Business and Economic Statistics and Mathematical Biosciences.
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.