Xiaojie Qiu | Smart Grid | Best Researcher Award

Best Researcher Award

Xiaojie Qiu
The State Key Laboratory of Industrial Control Technology

                            Xiaojie Qiu
Affiliation The State Key Laboratory of Industrial Control Technology
Country China
Scopus ID 57211005876
Documents 10
Citations 289
h-index 5
Subject Area Smart Grid
Event Technology Scientists Awards
ORCID 0000-0003-0024-7794

Xiaojie Qiu is a researcher associated with The State Key Laboratory of Industrial Control Technology, China, whose scholarly work focuses on smart grid systems, distributed control strategies, cyber-secure power networks, and data-driven control methodologies. Through contributions to resilient microgrid control and distributed intelligent systems, the researcher has established a measurable academic presence supported by publications, citations, and collaborative research activities within modern energy and automation domains.[1]

Abstract

Xiaojie Qiu’s research activities are centered on smart grid technologies, distributed control systems, resilient microgrids, and secure energy management frameworks. The research emphasizes data-driven control strategies, event-triggered communication mechanisms, and cyberattack-resilient operation of interconnected power systems. Published studies contribute to voltage restoration, current sharing optimization, and distributed coordination in microgrids and multi-agent networks. These contributions support the advancement of reliable, intelligent, and secure energy infrastructures while addressing practical challenges associated with distributed energy resources, communication constraints, and modern smart grid deployment requirements.[2]

Keywords

Smart Grid, DC Microgrid, Distributed Control, Data-Driven Systems, Multi-Agent Systems, Event-Triggered Control, Cybersecurity, Voltage Restoration, Current Sharing, Industrial Control Technology.

Introduction

Modern smart grids require secure, resilient, and distributed control architectures capable of maintaining stability under communication limitations and cyber threats. Xiaojie Qiu’s research addresses these challenges through innovative control methodologies for microgrids and multi-agent systems, supporting reliable energy distribution, operational security, and efficient coordination across increasingly complex power infrastructures.[2]

Research Profile

The research profile of Xiaojie Qiu demonstrates sustained engagement in smart grid control, distributed automation, and intelligent energy systems. With scholarly outputs indexed in Scopus and measurable citation impact, the researcher contributes to advancing secure control frameworks, data-driven optimization methods, and resilient operation strategies for contemporary electrical power networks.[1]

Research Contributions

Key contributions include distributed resilient control techniques for DC microgrids under deception attacks, secure voltage restoration mechanisms, adjustable current-sharing approaches, and fully distributed event-triggered control algorithms. These studies improve robustness, communication efficiency, and system stability while addressing practical implementation challenges in distributed energy and automation environments.[2][3]

Publications

  • Edge-Event-Based Distributed Resilient Control of DC Microgrid Against Multipattern Deception Attacks. This study proposes resilient distributed control mechanisms that enhance microgrid security and operational stability under coordinated cyberattacks while reducing communication burden through edge-event-triggered strategies.[2]
  • Distributed Data-Driven Control for Adjustable Current Sharing and Secure Voltage Restoration in DC Microgrids. The publication develops data-driven methodologies for voltage regulation and current sharing, improving distributed coordination and operational reliability in microgrid applications.[3]
  • Data-driven-based Fully Distributed Event-Triggered Control for Nonlinear Multi-Agent Systems. The research introduces event-triggered distributed control approaches that reduce communication requirements while maintaining system performance and coordination across nonlinear networked agents.[4]

Research Impact

The research has contributed to the broader understanding of secure distributed energy management and intelligent control systems. Citation performance and scholarly visibility indicate relevance within smart grid and automation communities. The developed methodologies provide practical value for enhancing resilience, scalability, and operational efficiency in modern power infrastructures.[1]

Award Suitability

Xiaojie Qiu demonstrates strong alignment with the objectives of the Technology Scientists Awards through contributions to smart grid innovation, resilient microgrid control, and distributed intelligent systems. The combination of academic publications, measurable citation metrics, and practical technological relevance supports recognition within research excellence and technology advancement categories.[2]

Conclusion

The body of work associated with Xiaojie Qiu reflects a focused commitment to advancing secure, distributed, and data-driven control methodologies for smart grids and multi-agent systems. Through research addressing cybersecurity, resilience, and operational efficiency, the researcher contributes valuable knowledge supporting the development of next-generation intelligent energy networks.[1]

References

  1. Elsevier. (n.d.). Scopus author details: Xiaojie Qiu, Author ID 57211005876. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57211005876
  2. Qiu, X., et al. (2025). Edge-Event-Based Distributed Resilient Control of DC Microgrid Against Multipattern Deception Attacks. IEEE Transactions.
    https://ieeexplore.ieee.org/document/11300711/
  3. Qiu, X., et al. (2025). Distributed Data-Driven Control for Adjustable Current Sharing and Secure Voltage Restoration in DC Microgrids. IEEE Transactions.
    https://ieeexplore.ieee.org/document/11220903/
  4. Qiu, X., et al. (2025). Data-driven-based Fully Distributed Event-Triggered Control for Nonlinear Multi-Agent Systems. Nonlinear Analysis: Hybrid Systems.
    https://linkinghub.elsevier.com/retrieve/pii/S0096300325000347

Lei Tian | Embedded Systems | Best Paper Award

Assoc Prof. Dr. Lei Tian | Embedded Systems | Best Paper Award

Laboratory Director at Xi’an University of Posts and Telecommunications | China

Lei Tian is a laboratory director at Xi’an University of Posts & Telecommunications whose work spans embedded systems, new semiconductor materials, and optoelectronic interconnection. He has focused on the analysis, modeling, and design of photoelectric coupling systems, including conversion‑efficiency optimization and noise‑reduction modeling. He has led and completed provincial and municipal R&D projects, contributed to State Grid initiatives, and authored both a monograph and a ministry‑planned textbook. His publication record includes more than sixty papers across SCI, EI, and core journals, with recent articles in the International Journal of Hydrogen Energy, Diamond & Related Materials, Physica Status Solidi B, and on power‑management circuits. Tian’s recent research advances 2D/Janus heterostructures for water splitting and gas sensing, and investigates device‑level co‑design strategies where materials inform embedded hardware architectures. His work targets sustainable energy, intelligent sensing, and robust, low‑noise, high‑efficiency systems suitable for real‑world deployment.

Professional Profile

Scopus

Education 

Lei Tian earned a Ph.D. in Circuits and Systems from Xidian University, emphasizing the intersection of signal integrity, noise modeling, and device‑level architectures for mixed‑signal and optoelectronic systems. Postdoctoral training at the Institute of Modern Physics, Northwest University, strengthened his first‑principles and multi‑physics modeling toolkit, including density‑functional workflows that bridge material properties to circuit‑level specifications. This background shaped a research style that connects quantum‑scale material parameters with embedded‑system requirements such as power budgets, spectral response, and noise floors. Coursework and mentoring activities have centered on semiconductor devices, optoelectronic interfaces, embedded firmware for instrumentation, and algorithm‑hardware co‑optimization. Tian’s graduate and postdoctoral path fostered collaborations across materials science, device physics, and systems engineering, informing a translational approach from theory to prototypes. The resulting expertise supports end‑to‑end pipelines—from ab initio predictions and sensor stack design to embedded control, calibration routines, and system‑level validation for power, reliability, and real‑time performance.

Experience 

As Laboratory Director at Xi’an University of Posts & Telecommunications, Lei Tian leads a group focused on optoelectronic interconnection and embedded hardware–software co‑design. The team develops modeling frameworks for photoelectric conversion efficiency, designs low‑noise coupling schemes, and validates concepts through simulations and targeted prototypes. He has steered key provincial R&D programs and municipal science projects, as well as multiple State Grid engagements, delivering deployable insights for power and sensing infrastructure. Tian’s portfolio extends from novel 2D/Janus heterostructures and graphene‑based stacks to practical power‑management ICs such as high‑voltage, low‑quiescent‑current LDOs with stability‑oriented impedance buffers. He regularly collaborates with materials scientists and circuit designers to translate computed properties into embedded constraints, addressing latency, energy, thermal limits, and field robustness. Alongside publications and books, his experience includes curriculum and lab development, fostering hands‑on training that connects material innovation with firmware, drivers, diagnostics, and system bring‑up.

Research Focus

Tian’s research targets the convergence of embedded systems with novel semiconductor and 2D materials. The thrusts include first‑principles discovery of van der Waals and Janus heterojunctions optimized for hydrogen evolution and gas sensing  photoelectric conversion analysis and noise‑reduction modeling for optoelectronic coupling embedded co‑design, where device physics informs circuit topologies, firmware routines, and on‑board diagnostics; and power‑management solutions such as high‑voltage LDOs with ultra‑low quiescent current for edge instrumentation. A defining feature is the “materials‑to‑metrics” pipeline—mapping band alignments, excitonic effects, and defect physics to embedded KPIs like SNR, dynamic range, and power efficiency. This enables predictive selection of sensor stacks and control algorithms prior to fabrication, accelerating time‑to‑prototype. Recent studies on MoSSe‑based heterostructures for water splitting exemplify this approach, linking catalytic descriptors to embedded monitoring strategies and stability management for scalable, field‑ready hydrogen‑generation systems.

Publication Top Notes

Title: Z-scheme WSTe/MoSSe van der Waals heterojunction as a hydrogen evolution photocatalyst: First-principles predictions
Year: 2025

Title: First-principles exploration of hydrogen evolution ability in MoS₂/hBNC/MoSSe vdW trilayer heterojunction for water splitting
Year: 2025

Title: Research of Power Inspection Based on Intelligent Algorithm
Year: 2025.

Conclusion

Lei Tian’s research exhibits high originality, technical depth, and relevance to global energy challenges, making the candidate a strong contender for the Best Paper Award. The contributions to hydrogen evolution photocatalysts using novel van der Waals heterojunctions represent valuable advancements in computational materials science. With further emphasis on experimental validation and broader impact demonstration, the works could achieve even greater recognition. Overall, the candidate’s publications align well with the award’s objectives, and the research output shows significant promise for long-term influence in sustainable energy technologies.