S. D. Pandey
This is a likely match — the affiliation was inferred from OpenAlex, ORCID, and web sources but has not been fully confirmed. Treat with appropriate caution.
Researcher
Also affiliated: Indian Institute of Soil Science (2021); ICAR – National Research Centre on Litchi (2017–2025); Indian Institute of Vegetable Research (2015)
Faculty Researcher
Research Areas
Biography and Research Information
OverviewAI-generated summary
S. D. Pandey's research interests span multiple disciplines, with recent work focusing on the application of artificial intelligence and quantum computing to scientific discovery, particularly in the characterization and discovery of 2D quantum materials. Publications in this area include 'Autonomous Agentic Orchestration for Physics-Aware Scientific Discovery,' 'QLAM: A Quantum Long-Attention Memory Approach to Long-Sequence Token Modeling,' and 'OpenQlaw: An Agentic AI Assistant for Analysis of 2D Quantum Materials.' Pandey also investigates agricultural topics, with publications such as 'Assessment of Fruit Drop in Different Cultivars of Litchi' and 'Impact Assessment of Pruning and High-Density Planting on Fruit Quality, Yield Attributes, and Vegetative Characteristics in Litchi Cv. ‘Shahi’.' Pandey has a h-index of 3 and has published 22 papers with 33 citations. Key collaborators at the University of Arkansas at Fayetteville include Hoang-Quan Nguyen, Xuan-Bac Nguyen, and Ky Luu.
Metrics
- h-index: 3
- Publications: 22
- Citations: 35
Selected Publications
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Autonomous Agentic Orchestration for Physics-Aware Scientific Discovery: An Integrative Multimodal Framework for 2D Material Characterization (2026)Journal of the Arkansas Academy of Science OpenAlex
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QMoE: A Quantum Mixture of Experts Framework for Scalable Quantum Neural Networks (2025)
Collaboration Network
Top Collaborators
- QMoE: A Quantum Mixture of Experts Framework for Scalable Quantum Neural Networks
- QMoE: A Quantum Mixture of Experts Framework for Scalable Quantum Neural Networks
- QMoE: A Quantum Mixture of Experts Framework for Scalable Quantum Neural Networks
- QMoE: A Quantum Mixture of Experts Framework for Scalable Quantum Neural Networks
- QMoE: A Quantum Mixture of Experts Framework for Scalable Quantum Neural Networks
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