Defining the future

Selected Research

Research at the intersection of physical systems, trustworthy AI, and engineering automation.

Research Directions

AI for power electronics

Simulation and modeling, maintenance and reliability, and intelligent process automation across the converter lifecycle.

AI for semiconductor manufacturing

Digital twins, virtual metrology, and process optimization for semiconductor fabrication and qualification.

Core AI themes

Physical AI, explainable AI, and agentic AI grounded in engineering knowledge and real systems.

Research vision

From AI-aided workflows toward adaptive, autonomous, and eventually self-sustained engineering systems.

Research Highlights

One-stop AI-based solutions for the modulation design of dual-active-bridge converters, 2020~2023 Expand
One-stop AI-based solutions for the modulation design of dual-active-bridge converters, 2020~2023 — slide 1

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Associated papers

  • X. Li, X. Zhang, F. Lin, C. Sun and K. Mao, "Artificial-Intelligence-Based Triple Phase Shift Modulation for Dual Active Bridge Converter With Minimized Current Stress," in IEEE Journal of Emerging and Selected Topics in Power Electronics, vol. 11, no. 4, pp. 4430-4441, Aug. 2023, doi: 10.1109/JESTPE.2021.3105522
  • F. Lin, X. Zhang, X. Li, C. Sun, W. Cai and Z. Zhang, "Automatic Triple Phase-Shift Modulation for DAB Converter With Minimized Power Loss," in IEEE Transactions on Industry Applications, vol. 58, no. 3, pp. 3840-3851, May-June 2022, doi: 10.1109/TIA.2021.3136501
  • F. Lin et al., "AI-Based Design With Data Trimming for Hybrid Phase Shift Modulation for Minimum-Current-Stress Dual Active Bridge Converter," in IEEE Journal of Emerging and Selected Topics in Power Electronics, vol. 12, no. 2, pp. 2268-2280, April 2024, doi: 10.1109/JESTPE.2022.3232534
  • X. Li, X. Zhang, F. Lin, C. Sun and K. Mao, "Artificial-Intelligence-Based Hybrid Extended Phase Shift Modulation for the Dual Active Bridge Converter With Full ZVS Range and Optimal Efficiency," in IEEE Journal of Emerging and Selected Topics in Power Electronics, vol. 11, no. 6, pp. 5569-5581, Dec. 2023, doi: 10.1109/JESTPE.2022.3185090
  • X. Li et al., "Data-Driven Modeling With Experimental Augmentation for the Modulation Strategy of the Dual-Active-Bridge Converter," in IEEE Transactions on Industrial Electronics, vol. 71, no. 3, pp. 2626-2637, March 2024, doi: 10.1109/TIE.2023.3265027
Physics-in-architecture neural networks (PANN) for time-domain modeling of power converters, 2023~Now Expand
Physics-in-architecture neural networks (PANN) for time-domain modeling of power converters, 2023~Now — slide 1

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Associated papers

  • X. Li et al., "Temporal Modeling for Power Converters With Physics-in-Architecture Recurrent Neural Network," in IEEE Trans. on Ind. Electron., vol. 71, no. 11, pp. 14111-14123, Nov. 2024.
  • X. Li, F. Lin, X. Zhang, H. Ma and F. Blaabjerg, "Data-Light Physics-Informed Modeling for the Modulation Optimization of a Dual-Active-Bridge Converter," in IEEE Trans. on Power Electron., vol. 39, no. 7, pp. 8770-8785, July 2024.
  • F. Lin, X. Li, X. Zhang and H. Ma, "STAR: One-Stop Optimization for Dual-Active-Bridge Converter With Robustness to Operational Diversity," in IEEE J. Emerg. Sel. Topics Power Electron., vol. 12, no. 3, pp. 2758-2773, June 2024.
  • X. Li et al., "A Generic Modeling Approach for Dual-Active-Bridge Converter Family via Topology Transferrable Networks," in IEEE Transactions on Industrial Electronics, vol. 72, no. 2, pp. 1524-1536, Feb. 2025, doi: 10.1109/TIE.2024.3406858
  • X. Li, F. Lin, J. J. Rodríguez-Andina, J. M. Guerrero, H. A. Mantooth and H. Ma, "NeurPecs: Physics-Informed AI-Based Adaptive Circuit Simulator for Power Converters," in IEEE Transactions on Industrial Electronics, vol. 73, no. 1, pp. 494-506, Jan. 2026, doi: 10.1109/TIE.2025.3582591
PE-GPT – the first AI agent in Power Electronics, 2023~Now Expand
PE-GPT – the first AI agent in Power Electronics, 2023~Now — slide 1

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Associated papers

  • F. Lin, X. Li, W. Lei, J. J. Rodriguez-Andina, J. M. Guerrero, C. Wen, X. Zhang and H. Ma, "PE-GPT: A New Paradigm for Power Electronics Design," in IEEE Transactions on Industrial Electronics, vol. 72, no. 4, pp. 3778-3791, 2024, doi: 10.1109/TIE.2024.3454408
Quantum computing for smart grid – cover story of Nature Review Electrical Engineering, 2026 Expand
Quantum computing for smart grid – cover story of Nature Review Electrical Engineering, 2026 — slide 1

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Associated papers

  • F. Lin, Z. Wang, C. Ren, X. Li, J. J. Rodríguez-Andina, S. Vazquez, H. A. Mantooth, M. Skoglund, T. van der Laan and M. Usman, "Quantum computing for smart grid," Nature Reviews Electrical Engineering, pp. 1-15, 2026, doi: 10.1038/s44287-026-00295-6
Physics-informed machine learning for power semiconductor fabrication modeling and optimization – Ion implantation and annealing as examples, 2026~Now Expand

Ion implantation

Physics-informed machine learning for power semiconductor fabrication modeling and optimization – Ion implantation and annealing as examples, 2026~Now — Ion implantation — slide 1

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Annealing

Physics-informed machine learning for power semiconductor fabrication modeling and optimization – Ion implantation and annealing as examples, 2026~Now — Annealing — slide 1

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Fundamentals of AI for power electronics – a comprehensive guideline from practitioners, 2026 Expand
Fundamentals of AI for power electronics – a comprehensive guideline from practitioners, 2026 — slide 1

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Associated papers

  • X. Li et al., "Fundamentals of Artificial Intelligence for Power Electronics," IEEE Transactions on Industrial Electronics, 2026.

Awards

  • Outstanding Mentor Award, University of Arkansas (2026)
  • IAAI Deployed Application Award, AAAI (2026)
  • Geneva International Exhibition of Inventions — Silver Award
  • ESI Highly Cited Paper — AI-based triple-phase-shift modulation
  • IEEE Industry Applications Society Prize Paper Award — Second Prize
  • NTU Graduate College Collaborative Research Award (2023–2024)
  • IEEE APEC Outstanding Presentation Award (2023)