Rishabh Kumar Gupta

50 papers receiving 769 citations

Rishabh Kumar Gupta's Hit Papers

Evaluation of Deep Learning Models for Multi-Step Ahead Time Series Prediction 2021 · 184 citations
1840+1+3Years since publication50100150

Peers

Rishabh Kumar Gupta
Comparison fields: 5 of 118
  • Computational Mathematics 8
  • Cognitive Neuroscience 216
  • Experimental and Cognitive Psychology 124
  • Human-Computer Interaction 46
  • Signal Processing 70
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Citations per year

Countries citing papers authored by Rishabh Kumar Gupta

Since Specialization
Citations

This map shows the geographic impact of Rishabh Kumar Gupta'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 Rishabh Kumar Gupta with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rishabh Kumar Gupta more than expected).

Fields of papers citing papers by Rishabh Kumar Gupta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rishabh Kumar Gupta. 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 Rishabh Kumar Gupta. The network helps show where Rishabh Kumar Gupta may publish in the future.

Co-authors

The 25 scholars most cited alongside Rishabh Kumar Gupta, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Rishabh Kumar Gupta Line = papers co-authored together Rishabh Kumar Gupta links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 54 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Evaluation of Deep Learning Models for Multi-Step Ahead Time Series Prediction
Hit paper breakdown →
2021184
2 2022111
3 201587
4 201828
5 202125
6 201723
7 201622
8 201720
9 201620
10 201520
11
Neurophysiological experimental facility for Quality of Experience (QoE) assessment
201320
12 201613
13 201313
14 201613
15 201312
16 201812
17 201511
18 202210
19 20179
20 20219

About Rishabh Kumar Gupta

Rishabh Kumar Gupta is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology, Artificial Intelligence, Signal Processing and Atomic and Molecular Physics, and Optics, having authored 54 papers that have together received 793 indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (11 papers), Neural dynamics and brain function (9 papers), Emotion and Mood Recognition (7 papers), Quantum Computing Algorithms and Architecture (5 papers), Topic Modeling (4 papers), Quantum Information and Cryptography (4 papers), Expert finding and Q&A systems (3 papers) and Mobile Crowdsensing and Crowdsourcing (3 papers). The work is most often cited by research in Computational Mathematics (8 citations), Cognitive Neuroscience (216 citations), Experimental and Cognitive Psychology (124 citations), Human-Computer Interaction (46 citations) and Signal Processing (70 citations). Rishabh Kumar Gupta has collaborated with scholars based in Canada, India and United States. Frequent co-authors include Tiago Henrique Falk, Rohitash Chandra, Khalil ur Rehman Laghari, Sabre Kais, Hubert J. Banville, Manas Sajjan, Shree Hari Sureshbabu, R. D. Levine, Sebastian Möller and Robert Schleicher. Their work appears in journals such as The Journal of Physical Chemistry A, Physical Chemistry Chemical Physics, IEEE Software, Applied Sciences and The Journal of Chemical Physics.

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.

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