Prashant Singh
Prashant Singh publishes mostly in Artificial Intelligence, Electrical and Electronic Engineering and Molecular Biology, on topics such as Advanced Multi-Objective Optimization Algorithms, Probabilistic and Robust Engineering Design and Machine Learning and Algorithms.
- World rank
- #2,619,059 of 7,710,434 ranked researchers
- Rank in Sweden
- #33,601 of 71,437
- Works
- 62
- Citations
- 739
- Citations per work
- 11.9
What does Prashant Singh research?
Prashant Singh's work is mostly in Computer Science (22%), Engineering (10%), Agricultural and Biological Sciences (7%).
Their six largest subfields, inside their fields and domains; the grey slice is everything else they publish. The interactive view splits every one of their works down to single topics.
The fields and subfields, with their numbers
- Everything else3149.2%
- Physical Sciences2032.1%
- Computer Science1321.6%
- Engineering710.5%
- Life Sciences914.0%
- Social Sciences34.7%
- Decision Sciences34.7%
- 1Artificial Intelligence16% of their works
- 2Electrical and Electronic Engineering10% of their works
- 3Molecular Biology7% of their works
- 4Plant Science7% of their works
- 5Computational Theory and Mathematics6% of their works
- 6Statistics, Probability and Uncertainty5% of their works
Research topics
- Advanced Multi-Objective Optimization Algorithms
- Probabilistic and Robust Engineering Design
- Machine Learning and Algorithms
- Gaussian Processes and Bayesian Inference
- Markov Chains and Monte Carlo Methods
- Gene Regulatory Network Analysis
- Electromagnetic Compatibility and Measurements
- Optimal Experimental Design Methods
Which keywords describe Prashant Singh's research?
The keywords of their largest research topics: Gaussian Processes, Machine Learning, Evolutionary Algorithms, Multiobjective Optimization, Sensitivity Analysis, Uncertainty Quantification, Active Learning and Bayesian Monte Carlo.
- Stochastic Gene Expression
- Optimization
- Experimental Design
- Variational Inference
- Semi-Supervised Learning
- Bayesian Monte Carlo
- Uncertainty Quantification
- Multiobjective Optimization
- Machine Learning
- Gaussian Processes
- Evolutionary Algorithms
- Sensitivity Analysis
- Active Learning
- Markov Chain
- Sparse Regression
- Antenna Measurement
- Gene Regulatory Networks
- Reverberation Chambers
Size is their works in the topics tagged with each word, from their 8 largest topics. Each links to the topic it comes from most. The words come from the keyword list OpenAlex gives each topic, not from the text of the papers, so a word can appear that none of the papers uses.
All 18 words, with their numbers
- Gaussian Processes122 topics
- Machine Learning122 topics
- Evolutionary Algorithms101 topic
- Multiobjective Optimization101 topic
- Sensitivity Analysis81 topic
- Uncertainty Quantification81 topic
- Active Learning61 topic
- Bayesian Monte Carlo61 topic
- Markov Chain61 topic
- Semi-Supervised Learning61 topic
- Sparse Regression61 topic
- Variational Inference61 topic
- Antenna Measurement51 topic
- Experimental Design51 topic
- Gene Regulatory Networks51 topic
- Optimization51 topic
- Reverberation Chambers51 topic
- Stochastic Gene Expression51 topic
Where does Prashant Singh work?
Prashant Singh's main affiliation in the publication record is Uppsala University, Sweden.
How many publications and citations does Prashant Singh have?
OpenAlex counts 62 works and 739 citations for Prashant Singh, an h-index of 14, ranking #2,619,059 of 7,710,434 researchers worldwide on the quality score.
Ranked on field-normalised citation excellence (50%), output (30%) and citations (20%). Counts come from OpenAlex author records, which occasionally merge different people who share a name or split one person into several.
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