Xinze Li Source Confirmed

Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.

Researcher

University of Arkansas at Fayetteville

faculty

XINZE001@e.ntu.edu.sg

19 h-index 182 pubs 1,423 cited

Research Areas

Advanced DC-DC Converters Multilevel Inverters and Converters Artificial Intelligence Applications Power Converter Design Advanced Neural Network Applications Battery Materials Natural Language Processing Techniques

Links

ORCID Research Group

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OverviewAI-generated summary

Xinze Li's research focuses on the application of artificial intelligence in power electronics and the design of power converters. Li has investigated AI-based methods for optimizing circuit parameters, triple phase shift modulation, and hybrid extended phase shift modulation in dual active bridge converters, aiming to minimize current stress and power loss while achieving full ZVS range and optimal efficiency. Publications also include work on layered cathode materials for batteries, design methodologies for symmetric CLLC resonant DC transformers, and data augmentation techniques using large language models. Li has also explored AI-based interpolation for seismic data. With 182 publications and an h-index of 19, Li's work contributes to advancements in power electronics, energy storage, and artificial intelligence applications.

Metrics

h-index: 19
Publications: 182
Citations: 1,423

Selected Publications

PE-GPT: A Physics-Informed Interactive Large Language Model for Power Converter Modulation Design (2024) DOI
A Cubic Wireless Charging Container System With Highly Uniform Magnetic Field Distribution (2024) DOI
PE-GPT: A New Paradigm for Power Electronics Design (2024) DOI