Lachlan Tychsen-Smith
- Computer Vision and Pattern Recognition top 10%
- Global and Planetary Change
- Artificial Intelligence
- Water Science and Technology
- Environmental Engineering
- Co-authors
- Lars PeterssonDavid Ahmedt‐AristizabalFazlul KarimLars AnderssonSimon DenmanClinton FookesNiklas PetterssonHarshala Gammulle
- Topics
- Hydrological Forecasting Using AI (2 papers)Flood Risk Assessment and Management (2 papers)Video Surveillance and Tracking Methods (2 papers)
- Cited by
- Computer Vision and Pattern RecognitionGlobal and Planetary ChangeWater Science and Technology
- Partner nations
- AustraliaUnited StatesUnited Kingdom
In The Last Decade
Lachlan Tychsen-Smith
8 papers receiving 208 citations
Peers
Comparison fields: 5 of 47
- Computer Vision and Pattern Recognition 117
- Global and Planetary Change 75
- Artificial Intelligence 43
- Water Science and Technology 42
- Environmental Engineering 40
Countries citing papers authored by Lachlan Tychsen-Smith
This map shows the geographic impact of Lachlan Tychsen-Smith'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 Lachlan Tychsen-Smith with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lachlan Tychsen-Smith more than expected).
Fields of papers citing papers by Lachlan Tychsen-Smith
This network shows the impact of papers produced by Lachlan Tychsen-Smith. 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 Lachlan Tychsen-Smith. The network helps show where Lachlan Tychsen-Smith may publish in the future.
Co-authorship network of co-authors of Lachlan Tychsen-Smith
This figure shows the co-authorship network connecting the top 25 collaborators of Lachlan Tychsen-Smith. A scholar is included among the top collaborators of Lachlan Tychsen-Smith 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 Lachlan Tychsen-Smith. Lachlan Tychsen-Smith is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 9 | |
| 3 | 75 | |
| 4 | 18 | |
| 5 | 2 | |
| 6 | 8 | |
| 7 | 87 | |
| 8 | 17 |
About Lachlan Tychsen-Smith
Lachlan Tychsen-Smith is a scholar working on Ecological Modeling, Environmental Engineering and Computer Vision and Pattern Recognition, having authored 8 papers that have together received 217 indexed citations. Recurring topics across this work include Hydrological Forecasting Using AI (2 papers), Flood Risk Assessment and Management (2 papers) and Video Surveillance and Tracking Methods (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (117 citations), Global and Planetary Change (75 citations) and Water Science and Technology (42 citations). Lachlan Tychsen-Smith has collaborated with scholars based in Australia, United States and United Kingdom. Frequent co-authors include Lars Petersson, David Ahmedt‐Aristizabal, Fazlul Karim, Lars Andersson, Simon Denman, Clinton Fookes, Niklas Pettersson, Harshala Gammulle, Shenghong Li and Dadong Wang. Their work appears in journals such as ACM Computing Surveys, Computer Methods and Programs in Biomedicine and Water.
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.