Best Researcher Award
Nusrat Rouf
SKUAST Kashmir, India
Nusrat Rouf is presented in this academic recognition profile as a researcher working in the area of artificial intelligence and financial applications. The supplied profile identifies SKUAST Kashmir, India, as the institutional affiliation and lists AI in Finance as the subject area. Publicly indexed scholarly records also associate a researcher named Nusrat Rouf with research on machine-learning-based stock-market prediction, financial-market volatility, sentiment analysis, and related computational approaches. [1] [2]
Abstract
This profile describes the academic and research record supplied for Nusrat Rouf in connection with the Best Researcher Award. The identified research area, AI in Finance, encompasses the application of machine learning, artificial intelligence, predictive analytics, and data-driven methods to financial-market problems. Published work attributed to Nusrat Rouf includes research examining machine-learning approaches for stock-market prediction and the relationship between external events and market volatility. [1] [2] The profile supplied for this article records 14 documents, 865 citations, and an h-index of 5; such metrics are time-dependent and should be interpreted according to the database and date on which they were retrieved.
Keywords
Artificial Intelligence in Finance; Machine Learning; Stock Market Prediction; Financial Analytics; Sentiment Analysis; Predictive Modeling; Financial Market Volatility; Computational Finance
Introduction
Artificial intelligence has become an important methodological component of contemporary financial research because financial datasets frequently contain high-dimensional, nonlinear, noisy, and time-dependent information. Machine-learning techniques can be used to identify patterns, construct predictive models, evaluate market signals, and support quantitative analysis. Research associated with Nusrat Rouf has addressed these themes through studies of stock-market prediction and machine-learning methodologies. [4] [2]
Research Profile
The supplied academic profile identifies Nusrat Rouf with SKUAST Kashmir in India and associates the researcher with AI in Finance. The broader publication record available through scholarly indexes connects the name with machine learning, stock-market forecasting, financial sentiment, predictive analytics, and computational approaches to financial-market analysis. [5] [2]
Research Contributions
One documented contribution is the systematic examination of machine-learning techniques used for stock-market prediction. The 2021 review surveyed methodologies and developments across the preceding decade and discussed approaches including machine learning, support-vector methods, neural networks, sentiment analysis, and related predictive techniques. [1] [3]
Publications
Selected publications relevant to the stated research area include the following works:
- Rouf, N.; Malik, M. B.; Arif, T. “Predicting the Stock Market Trend: An Ensemble Approach Using Impactful Exploratory Data Analysis.” Information, Communication and Computing Technology, 2021. DOI: 10.1007/978-3-030-88378-2_18. [3]
The publication record demonstrates a recurring research interest in computational methods for financial prediction. The 2021 review is particularly relevant to AI in Finance because it evaluates the development of machine-learning methodologies for stock-market prediction and identifies methodological directions for subsequent research. [1]
Research Impact
The supplied profile reports 865 citations across 14 documents and an h-index of 5. These values are presented as profile-level metrics supplied for this article rather than as permanently fixed bibliometric facts. Citation counts, document totals, and h-index values can vary between databases and can change as scholarly records are indexed or updated. The 2021 Electronics review has received substantial scholarly attention and is indexed by major scholarly platforms.
Award Suitability
Based on the supplied profile and publicly indexed publication evidence, Nusrat Rouf’s research portfolio has a clear thematic connection with AI in Finance, particularly through machine-learning-based financial prediction and stock-market analysis. [1] [2] For consideration under a Best Researcher Award, relevant assessment dimensions may include the originality of research questions, methodological rigor, quality and relevance of publications, citation performance, continuity of research activity, contribution to the field, and demonstrated academic or practical influence.
Conclusion
Nusrat Rouf’s documented research activities are associated with the application of artificial intelligence and machine-learning methods to financial-market problems, particularly stock-market prediction and volatility analysis. Published work in Electronics and Computational Intelligence and Neuroscience, together with a conference contribution on stock-market trend prediction, provides identifiable scholarly evidence of this research direction. [1] [2] [3]
External Links
References
- Rouf, N.; Malik, M. B.; Arif, T.; Sharma, S.; Singh, S.; Aich, S.; Kim, H.-C. (2021). Stock Market Prediction Using Machine Learning Techniques: A Decade Survey on Methodologies, Recent Developments, and Future Directions. Electronics, 10(21), 2717. DOI: 10.3390/electronics10212717.
https://doi.org/10.3390/electronics10212717
- Rouf, N.; Malik, M. B.; Sharma, S.; Ra, I.-H.; et al. (2022). Impact of Healthcare on Stock Market Volatility and Its Predictive Solution Using Improved Neural Network. Computational Intelligence and Neuroscience, 2022, Article 7097044. DOI: 10.1155/2022/7097044.
https://doi.org/10.1155/2022/7097044
- Rouf, N.; Malik, M. B.; Arif, T. (2021). Predicting the Stock Market Trend: An Ensemble Approach Using Impactful Exploratory Data Analysis. Information, Communication and Computing Technology. DOI: 10.1007/978-3-030-88378-2_18.
https://doi.org/10.1007/978-3-030-88378-2_18
- ORCID. (n.d.). ORCID record for Nusrat Rouf, ORCID 0000-0002-9989-2357. ORCID.
https://orcid.org/0000-0002-9989-2357
- Google Scholar. (n.d.). Google Scholar author profile: Nusrat Rouf, Scholar ID msx79scAAAAJ. Google Scholar.
https://scholar.google.com/citations?user=msx79scAAAAJ&hl=en&oi=sra