Innovative Research Award
Xiangning Meng
Northeastern University, China
| Xiangning Meng | |
|---|---|
| Affiliation | Northeastern University |
| Country | China |
| Scopus ID | 14033438400 |
| Documents | 85 |
| Citations | 995 Citations by 726 documents |
| h-index | 19 |
| Subject Area | Computational Modeling |
| Event | International Analytical Chemistry Awards |
Xiangning Meng is a researcher affiliated with Northeastern University, China, whose academic contributions are associated with computational modeling and analytical research methodologies. The Innovative Research Award profile recognizes scholarly activities, research productivity, and contributions within computational approaches supporting modern scientific investigations. [1]
Abstract
The Innovative Research Award article presents an academic overview of Xiangning Meng, a researcher from Northeastern University, China. The profile highlights research activities related to computational modeling, scientific analysis, and data-driven approaches that contribute to advancing analytical research fields. Bibliometric indicators including publication output, citation records, and h-index provide a structured representation of scholarly activity. [1]
Keywords
- Computational Modeling
- Analytical Chemistry
- Scientific Computing
- Research Innovation
Introduction
Computational modeling has become an important research discipline by enabling simulation, prediction, and interpretation of complex scientific systems. Researchers in this area integrate mathematical models, computational techniques, and experimental understanding to support discoveries across chemistry and related scientific fields. [2]
Research Profile
Xiangning Meng’s research profile reflects participation in computationally focused scientific investigations. The researcher has contributed to peer-reviewed academic literature with documented publications and citation impact recorded through international scholarly databases. [1]
Research Contributions
The research contributions associated with computational modeling involve developing analytical strategies, improving predictive understanding, and applying computational methods to scientific problems. Such approaches support efficient research workflows and complement experimental investigations. [2]
Publications
The publication record includes 85 indexed documents with a reported citation count of 995 citations from 726 documents and an h-index of 19 according to available Scopus profile information. These metrics represent measurable indicators of research dissemination and academic engagement. [1]
Research Impact
Research impact can be assessed through publication visibility, citation performance, and contribution to scientific knowledge. Xiangning Meng’s recorded academic metrics demonstrate continued participation in scholarly communication within computational modeling research areas. [1]
Award Suitability
The Innovative Research Award recognizes researchers demonstrating meaningful academic contributions, research productivity, and advancement of scientific knowledge. Xiangning Meng’s documented research activities in computational modeling align with the objectives of recognizing innovative scientific work. [3]
Conclusion
Xiangning Meng’s academic profile represents contributions to computational modeling and related analytical research fields. The combination of publication records, citation indicators, and research activities provides a foundation for evaluation within the Innovative Research Award framework.
External Links
- Scopus Author Profile:
Scopus Profile - DOI Reference:
https://doi.org/10.1016/j.aca.2023.341234 - Award Website:
International Analytical Chemistry Awards
References
- Elsevier. (n.d.). Scopus author details: Xiangning Meng, Author ID 14033438400. Scopus.
https://www.scopus.com/authid/detail.uri?authorId=14033438400
- Computational modeling approaches in scientific research. Analytical and computational methodology literature.
- International Analytical Chemistry Awards. Recognition framework for scientific achievement.