Rahul Iyer
Impact in
- Artificial Intelligence top 10%
- Explainable Artificial Intelligence (XAI)
- Adversarial Robustness in Machine Learning
- Reinforcement Learning in Robotics
- Topic Modeling
- Target Tracking and Data Fusion in Sensor Networks
- Anomaly Detection Techniques and Applications
Papers in
-
- Adversarial Robustness in Machine Learning 2
-
- Wireless Communication Networks Research 1
- Co-authors
- Katia Sycara (3 shared papers)Michael Lewis (1 shared paper)Ahmed H. Tewfik (1 shared paper)Ronghuo Zheng (1 shared paper)Tian Tian (1 shared paper)Zhiting Hu (1 shared paper)Mark Campbell (1 shared paper)Frédéric Bourgault (1 shared paper)
- Journals
- The Journal of Urology (1 paper)Diabetes (1 paper)IET Smart Grid (1 paper)EPiC series in computing (1 paper)International Conference on Computational Linguistics (1 paper)
- Partner nations
- United StatesIndia
In The Last Decade
Rahul Iyer
10 papers receiving 193 citations
Peers
Comparison fields: 5 of 58
- Health Informatics 6
- Artificial Intelligence 131
- General Decision Sciences 4
- Safety Research 13
- Computer Networks and Communications 34
Countries citing papers authored by Rahul Iyer
This map shows the geographic impact of Rahul Iyer'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 Rahul Iyer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rahul Iyer more than expected).
Fields of papers citing papers by Rahul Iyer
This network shows the impact of papers produced by Rahul Iyer. 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 Rahul Iyer. The network helps show where Rahul Iyer may publish in the future.
Co-authors
The 25 scholars most cited alongside Rahul Iyer, 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 | 2018 | 79 | |
| 2 | 2018 | 55 | |
| 3 | Joint Embedding of Hierarchical Categories and Entities for Concept Categorization and Dataless Classification | 2016 | 23 |
| 4 | 2008 | 22 | |
| 5 | 2012 | 7 | |
| 6 | 2006 | 5 | |
| 7 | 2011 | 2 | |
| 8 | 2025 | 1 | |
| 9 | 2023 | 1 | |
| 10 | 2006 | 1 | |
| 11 | 2004 | 1 | |
| 12 | 2021 | 0 | |
| 13 | 2020 | 0 | |
| 14 | 2017 | 0 |
About Rahul Iyer
Rahul Iyer is a scholar working on Artificial Intelligence, Computer Networks and Communications, Computer Vision and Pattern Recognition, Information Systems and Electrical and Electronic Engineering, having authored 14 papers that have together received 197 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (2 papers), Advanced Neural Network Applications (2 papers), Diabetes Management and Research (1 paper), Wireless Communication Networks Research (1 paper), Insect Pheromone Research and Control (1 paper), Statistical Distribution Estimation and Applications (1 paper), Cognitive Functions and Memory (1 paper) and Wind and Air Flow Studies (1 paper). The work is most often cited by research in Health Informatics (6 citations), Artificial Intelligence (131 citations), General Decision Sciences (4 citations), Safety Research (13 citations) and Computer Networks and Communications (34 citations). Rahul Iyer has collaborated with scholars based in United States and India. Frequent co-authors include Katia Sycara, Michael Lewis, Ahmed H. Tewfik, Ronghuo Zheng, Tian Tian, Zhiting Hu, Mark Campbell, Frédéric Bourgault, J. Wang and Beilei Zhang. Their work appears in journals such as The Journal of Urology, Diabetes, IET Smart Grid, EPiC series in computing and International Conference on Computational Linguistics.
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.