Chris Cundy
- Artificial Intelligence
- Geography, Planning and Development top 5%
- Signal Processing
- Computer Vision and Pattern Recognition
- Transportation
- Co-authors
- Yingjie HuNi LaoGengchen MaiKristy ChoiRyan Zhenqi ZhouWei LiuKenneth JosephStefano Ermon
- Topics
- Geographic Information Systems Studies (2 papers)Neural Networks and Applications (2 papers)Machine Learning and Data Classification (2 papers)
- Journals
- International Journal of Multiphase FlowACM Transactions on Spatial Algorithms and SystemsInternational Journal of Geographical Information Systems
- Partner nations
- United StatesUnited KingdomSingapore
In The Last Decade
Chris Cundy
7 papers receiving 176 citations
Hit Papers
Peers
Comparison fields: 5 of 54
- Artificial Intelligence 75
- Geography, Planning and Development 65
- Signal Processing 29
- Computer Vision and Pattern Recognition 27
- Transportation 23
Countries citing papers authored by Chris Cundy
This map shows the geographic impact of Chris Cundy'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 Chris Cundy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chris Cundy more than expected).
Fields of papers citing papers by Chris Cundy
This network shows the impact of papers produced by Chris Cundy. 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 Chris Cundy. The network helps show where Chris Cundy may publish in the future.
Co-authorship network of co-authors of Chris Cundy
This figure shows the co-authorship network connecting the top 25 collaborators of Chris Cundy. A scholar is included among the top collaborators of Chris Cundy 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 Chris Cundy. Chris Cundy 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 the Opportunities and Challenges of Foundation Models for GeoAI (Vision Paper)breakdown → | 45 |
| 2 | 5 | |
| 3 | Geo-knowledge-guided GPT models improve the extraction of location descriptions from disaster-related social media messagesbreakdown → | 85 |
| 4 | 38 | |
| 5 | 1 | |
| 6 | Flexible Approximate Inference via Stratified Normalizing Flows. | 1 |
| 7 | Parallelizing Linear Recurrent Neural Nets Over Sequence Length. | 8 |
About Chris Cundy
Chris Cundy is a scholar working on Geography, Planning and Development, Geochemistry and Petrology and Communication, having authored 7 papers that have together received 183 indexed citations. Recurring topics across this work include Geographic Information Systems Studies (2 papers), Neural Networks and Applications (2 papers) and Machine Learning and Data Classification (2 papers). The work is most often cited by research in Geography, Planning and Development (65 citations), Transportation (23 citations) and Health Informatics (4 citations). Chris Cundy has collaborated with scholars based in United States, United Kingdom and Singapore. Frequent co-authors include Yingjie Hu, Ni Lao, Gengchen Mai, Kristy Choi, Ryan Zhenqi Zhou, Wei Liu, Kenneth Joseph, Stefano Ermon, Éric Martin and Deepak R. Mishra. Their work appears in journals such as International Journal of Multiphase Flow, ACM Transactions on Spatial Algorithms and Systems and International Journal of Geographical Information Systems.
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.