Rishab Goel
Impact in
- Artificial Intelligence top 5%
- Advanced Graph Neural Networks
- Topic Modeling
- Semantic Web and Ontologies
Papers in
-
- Domain Adaptation and Few-Shot Learning 3
- Advanced Graph Neural Networks 3
- Topic Modeling 2
- Bayesian Modeling and Causal Inference 1
-
- Seismic Performance and Analysis 3
- Structural Engineering and Vibration Analysis 1
- Geotechnical Engineering and Underground Structures 1
- Co-authors
- Seyed Mehran Kazemi (3 shared papers)Pascal Poupart (2 shared papers)Marcus A. Brubaker (1 shared paper)Peter Forsyth (1 shared paper)Ivan Kobyzev (1 shared paper)Yuzhong Huang (1 shared paper)Huaijin Chen (1 shared paper)Ankit Patel (1 shared paper)
- Journals
- IEEE Transactions on Computational Imaging (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- United StatesIndiaAustria
In The Last Decade
Rishab Goel
7 papers receiving 233 citations
Peers
Comparison fields: 5 of 30
- Artificial Intelligence 218
- Computational Mathematics 3
- Management Science and Operations Research 61
- Computer Vision and Pattern Recognition 54
- Statistical and Nonlinear Physics 21
Countries citing papers authored by Rishab Goel
This map shows the geographic impact of Rishab Goel'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 Rishab Goel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rishab Goel more than expected).
Fields of papers citing papers by Rishab Goel
This network shows the impact of papers produced by Rishab Goel. 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 Rishab Goel. The network helps show where Rishab Goel may publish in the future.
Co-authors
The 12 scholars most cited alongside Rishab Goel, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 202 | |
| 2 | 2020 | 15 | |
| 3 | Relational Representation Learning for Dynamic (Knowledge) Graphs: A Survey. | 2019 | 11 |
| 4 | 2019 | 5 | |
| 5 | 2016 | 2 | |
| 6 | 2022 | 1 | |
| 7 | EARTHQUAKE BEHAVIOR OF BRIDGES WITH INTEGRAL ABUTMENTS | 1997 | 1 |
| 8 | Plastic Hinge Length and Depth for Piles in Marine Oil Terminals Including Nonlinear Soil Properties | 2010 | 0 |
About Rishab Goel
Rishab Goel is a scholar working on Artificial Intelligence, Civil and Structural Engineering, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Management Science and Operations Research, having authored 8 papers that have together received 237 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (3 papers), Advanced Graph Neural Networks (3 papers), Seismic Performance and Analysis (3 papers), Topic Modeling (2 papers), Retinal Imaging and Analysis (1 paper), Structural Engineering and Vibration Analysis (1 paper), Bayesian Modeling and Causal Inference (1 paper) and Geotechnical Engineering and Underground Structures (1 paper). The work is most often cited by research in Artificial Intelligence (218 citations), Computational Mathematics (3 citations), Management Science and Operations Research (61 citations), Computer Vision and Pattern Recognition (54 citations) and Statistical and Nonlinear Physics (21 citations). Rishab Goel has collaborated with scholars based in United States, India and Austria. Frequent co-authors include Seyed Mehran Kazemi, Pascal Poupart, Marcus A. Brubaker, Peter Forsyth, Ivan Kobyzev, Yuzhong Huang, Huaijin Chen, Ankit Patel, Rhonald C. Lua and Ashok Veeraraghavan. Their work appears in journals such as IEEE Transactions on Computational Imaging and arXiv (Cornell University).
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.