Xinze Li Data-verified
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Researcher
faculty
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Biography and Research Information
OverviewAI-generated summary
Xinze Li leads a research group at the University of Arkansas at Fayetteville. His scholarly work focuses on power electronics, particularly the design and optimization of converters using artificial intelligence and advanced modulation techniques. Li has published research on AI-based design for circuit parameters of power converters, triple phase-shift modulation for dual active bridge converters, and design methodologies for CLLC resonant DC transformers to improve efficiency and stability.
His recent publications also include work on data augmentation using large language models and seismic data interpolation. Li's research interests extend to materials science, with publications on layered cathode materials for battery applications. His h-index is 20, with 182 total publications and 1,479 total citations, indicating recent and ongoing activity in his fields of research.
Metrics
- h-index: 20
- Publications: 182
- Citations: 1,511
Selected Publications
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Physics-Informed Autonomous LLM Agents for Explainable Power Electronics Modulation Design (2026)
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Toward Ethical AI in Power Electronics: How Engineering Practice and Roles Must Adapt (2026)
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Virtualization as a New Scaling Law for Semiconductor Devices Beyond Geometric Scaling (2026)
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Generalized Waveform Modeling for Dual Active Bridge with Graph Neural Networks (2025)
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PE-GPT: A Physics-Informed Interactive Large Language Model for Power Converter Modulation Design (2024)
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A Cubic Wireless Charging Container System With Highly Uniform Magnetic Field Distribution (2024)
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PE-GPT: A New Paradigm for Power Electronics Design (2024)
Collaboration Network
Top Collaborators
- Artificial-Intelligence-Based Design for Circuit Parameters of Power Converters
- Artificial-Intelligence-Based Triple Phase Shift Modulation for Dual Active Bridge Converter With Minimized Current Stress
- Design Methodology for Symmetric CLLC Resonant DC Transformer Considering Voltage Conversion Ratio, System Stability, and Efficiency
- Automatic Triple Phase-Shift Modulation for DAB Converter With Minimized Power Loss
- Artificial-Intelligence-Based Hybrid Extended Phase Shift Modulation for the Dual Active Bridge Converter With Full ZVS Range and Optimal Efficiency
Showing 5 of 15 shared publications
- Artificial-Intelligence-Based Design for Circuit Parameters of Power Converters
- Artificial-Intelligence-Based Triple Phase Shift Modulation for Dual Active Bridge Converter With Minimized Current Stress
- Design Methodology for Symmetric CLLC Resonant DC Transformer Considering Voltage Conversion Ratio, System Stability, and Efficiency
- Automatic Triple Phase-Shift Modulation for DAB Converter With Minimized Power Loss
- Artificial-Intelligence-Based Hybrid Extended Phase Shift Modulation for the Dual Active Bridge Converter With Full ZVS Range and Optimal Efficiency
Showing 5 of 8 shared publications
- Design of Symmetrical CLLC-Resonant DC Transformer Considering Voltage Transfer Ratio and Cascaded System Stability
- Temporal Modeling for Power Converters With Physics-in-Architecture Recurrent Neural Network
- PE-GPT: A New Paradigm for Power Electronics Design
- Data-Light Physics-Informed Modeling for the Modulation Optimization of a Dual-Active-Bridge Converter
- STAR: One-Stop Optimization for Dual-Active-Bridge Converter With Robustness to Operational Diversity
Showing 5 of 6 shared publications
- Artificial-Intelligence-Based Triple Phase Shift Modulation for Dual Active Bridge Converter With Minimized Current Stress
- Automatic Triple Phase-Shift Modulation for DAB Converter With Minimized Power Loss
- Artificial-Intelligence-Based Hybrid Extended Phase Shift Modulation for the Dual Active Bridge Converter With Full ZVS Range and Optimal Efficiency
- AI-Based Design With Data Trimming for Hybrid Phase Shift Modulation for Minimum-Current-Stress Dual Active Bridge Converter
- Deep Reinforcement Learning-Enabled Distributed Uniform Control for a DC Solid State Transformer in DC Microgrid
- Layered Cathode Materials: Precursors, Synthesis, Microstructure, Electrochemical Properties, and Battery Performance
- Effects of Nb-doping on cycle life, self-discharge and crack resistance of Ni-rich LiNi0.94Co0.02Al0.04O2 cathode for Li-ion batteries
- Enhancing cycle life of LiNi0.95Co0.04Mn0.01O2 cathode by bulk W-doping and surface Co-doping
- Stabilizing the surface of LiNi0.815Co0.15Al0.035O2 by a facile pre-oxidation-coating strategy on the precursor
- Dual modification of LiNi0.95Co0.04Mn0.01O2 for enhancing its cycling stability in lithium-ion batteries
- Layered Cathode Materials: Precursors, Synthesis, Microstructure, Electrochemical Properties, and Battery Performance
- Effects of Nb-doping on cycle life, self-discharge and crack resistance of Ni-rich LiNi0.94Co0.02Al0.04O2 cathode for Li-ion batteries
- Enhancing cycle life of LiNi0.95Co0.04Mn0.01O2 cathode by bulk W-doping and surface Co-doping
- Stabilizing the surface of LiNi0.815Co0.15Al0.035O2 by a facile pre-oxidation-coating strategy on the precursor
- Dual modification of LiNi0.95Co0.04Mn0.01O2 for enhancing its cycling stability in lithium-ion batteries
- Layered Cathode Materials: Precursors, Synthesis, Microstructure, Electrochemical Properties, and Battery Performance
- Effects of Nb-doping on cycle life, self-discharge and crack resistance of Ni-rich LiNi0.94Co0.02Al0.04O2 cathode for Li-ion batteries
- Enhancing cycle life of LiNi0.95Co0.04Mn0.01O2 cathode by bulk W-doping and surface Co-doping
- Stabilizing the surface of LiNi0.815Co0.15Al0.035O2 by a facile pre-oxidation-coating strategy on the precursor
- Dual modification of LiNi0.95Co0.04Mn0.01O2 for enhancing its cycling stability in lithium-ion batteries
- Data-Driven Modeling With Experimental Augmentation for the Modulation Strategy of the Dual-Active-Bridge Converter
- Temporal Modeling for Power Converters With Physics-in-Architecture Recurrent Neural Network
- PE-GPT: A New Paradigm for Power Electronics Design
- Data-Light Physics-Informed Modeling for the Modulation Optimization of a Dual-Active-Bridge Converter
- STAR: One-Stop Optimization for Dual-Active-Bridge Converter With Robustness to Operational Diversity
- Artificial-Intelligence-Based Triple Phase Shift Modulation for Dual Active Bridge Converter With Minimized Current Stress
- Artificial-Intelligence-Based Hybrid Extended Phase Shift Modulation for the Dual Active Bridge Converter With Full ZVS Range and Optimal Efficiency
- Particle swarm optimization with state-based adaptive velocity limit strategy
- Feature-aware conditional GAN for category text generation
- Artificial-Intelligence-Based Design for Circuit Parameters of Power Converters
- Temporal Modeling for Power Converters With Physics-in-Architecture Recurrent Neural Network
- Data-Light Physics-Informed Modeling for the Modulation Optimization of a Dual-Active-Bridge Converter
- Droplet deposition characteristics detection method based on deep learning
- Evaluation of UAV spraying quality based on 1D-CNN model and wireless multi-sensors system
- Adaptive spraying decision system for plant protection unmanned aerial vehicle based on reinforcement learning
- Towards Verifiable Generation: A Benchmark for Knowledge-aware Language Model Attribution
- MMEKG: Multi-modal Event Knowledge Graph towards Universal Representation across Modalities
- Towards Verifiable Generation: A Benchmark for Knowledge-aware Language Model Attribution
- Effects of Nb-doping on cycle life, self-discharge and crack resistance of Ni-rich LiNi0.94Co0.02Al0.04O2 cathode for Li-ion batteries
- Enhancing cycle life of LiNi0.95Co0.04Mn0.01O2 cathode by bulk W-doping and surface Co-doping
- Dual modification of LiNi0.95Co0.04Mn0.01O2 for enhancing its cycling stability in lithium-ion batteries
- Data-Driven Modeling With Experimental Augmentation for the Modulation Strategy of the Dual-Active-Bridge Converter
- Deep Reinforcement Learning-Enabled Distributed Uniform Control for a DC Solid State Transformer in DC Microgrid
- Hybrid Duty Ratio Phase-Shift Modulation for a Si + SiC Neutral-Point-Clamped Dual-Active-Bridge Converter
- Data-Driven Modeling With Experimental Augmentation for the Modulation Strategy of the Dual-Active-Bridge Converter
- Temporal Modeling for Power Converters With Physics-in-Architecture Recurrent Neural Network
- PE-GPT: A New Paradigm for Power Electronics Design
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