Rohitash Chandra
Impact in
- Artificial Intelligence top 1%
- Neural Networks and Applications
- Geochemistry and Geologic Mapping
- Metaheuristic Optimization Algorithms Research
- Evolutionary Algorithms and Applications
- Environmental Engineering top 5%
- Hydrological Forecasting Using AI
Papers in
-
- Neural Networks and Applications 30
- Evolutionary Algorithms and Applications 20
- Metaheuristic Optimization Algorithms Research 20
- Geochemistry and Geologic Mapping 12
- Neural Networks and Reservoir Computing 9
-
- Remote-Sensing Image Classification 8
Rohitash Chandra
107 papers receiving 2.2k citations
Hit Papers
Peers
Comparison fields: 5 of 169
- Artificial Intelligence 1.1k
- Environmental Engineering 271
- Media Technology 156
- Management Science and Operations Research 205
- Signal Processing 162
Countries citing papers authored by Rohitash Chandra
This map shows the geographic impact of Rohitash Chandra'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 Rohitash Chandra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rohitash Chandra more than expected).
Fields of papers citing papers by Rohitash Chandra
This network shows the impact of papers produced by Rohitash Chandra. 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 Rohitash Chandra. The network helps show where Rohitash Chandra may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Rohitash Chandra, 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 | 2025 | 7 | |
| 2 | 2025 | 1 | |
| 3 | 2025 | 0 | |
| 4 | 2025 | 0 | |
| 5 | 2024 | 6 | |
| 6 | 2024 | 9 | |
| 7 | 2024 | 3 | |
| 8 | 2024 | 10 | |
| 9 | 2024 | 3 | |
| 10 | 2023 | 3 | |
| 11 | 2023 | 10 | |
| 12 | 2023 | 12 | |
| 13 | 2023 | 42 | |
| 14 | 2022 | 7 | |
| 15 | 2022 | 4 | |
| 16 | 2021 | 16 | |
| 17 | 2018 | 45 | |
| 18 | Hybrid Evolutionary One-Step Gradient Descent for Training Recurrent Neural Networks. | 2008 | 1 |
| 19 | Knowledge Discovery using Artificial Neural Networks for a Conservation Biology Domain. | 2007 | 1 |
| 20 | The Comparison and Combination of Genetic and Gradient Descent Learning in Recurrent Neural Networks: An Application to Speech Phoneme Classification. | 2007 | 4 |
About Rohitash Chandra
Rohitash Chandra is a scholar working on Artificial Intelligence, Media Technology, Environmental Engineering, Signal Processing and Computational Theory and Mathematics, having authored 117 papers that have together received 2.3k indexed citations. Recurring topics across this work include Neural Networks and Applications (30 papers), Evolutionary Algorithms and Applications (20 papers), Metaheuristic Optimization Algorithms Research (20 papers), Geochemistry and Geologic Mapping (12 papers), Neural Networks and Reservoir Computing (9 papers), Meteorological Phenomena and Simulations (8 papers), Remote-Sensing Image Classification (8 papers) and Robotic Mechanisms and Dynamics (7 papers). The work is most often cited by research in Artificial Intelligence (1.1k citations), Environmental Engineering (271 citations), Media Technology (156 citations), Management Science and Operations Research (205 citations) and Signal Processing (162 citations). Rohitash Chandra has collaborated with scholars based in Australia, India and Fiji. Frequent co-authors include Jun Zhang, Azal Ahmad Khan, R. Dietmar Müller, Rishabh Gupta, Yew-Soon Ong, Chi-Keong Goh, Ehsan Farahbakhsh, Luc Rolland, Marcus Frean and Shelvin Chand. Their work appears in journals such as IEEE Access, Neurocomputing, Applied Soft Computing, PLoS ONE and Expert Systems with Applications.
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.