Xiaoming Zhang | Integrated Energy System | Best Researcher Award

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Dr. Xiaoming Zhang | Integrated Energy System | Best Researcher Award

Lecturer at Inner Mongolia University Of Science and Technology, China.

Dr. Xiaoming Zhang is a researcher in the field of thermal and renewable energy systems. He obtained his Ph.D. from Beijing University of Technology, specializing in Power Engineering and Engineering Thermophysics. With a multidisciplinary background and academic appointments, his work integrates experimental analysis, system modeling, and advanced optimization methods including AI-driven tools for improving energy system efficiency and sustainability. He has contributed to over 10 academic papers and co-authored 2 monographs in his field.

Professional Profile 

Scopus Profile

Education 🎓📚

  • B.Eng. in Thermal Energy and Power Engineering, Inner Mongolia University of Science and Technology, China (2004–2008)

  • M.Eng. in Power Engineering, Inner Mongolia University of Technology, China (2012–2015)

  • Ph.D. in Power Engineering and Engineering Thermophysics, Beijing University of Technology, China (2015–2020)

Professional Experience 🧑‍🏫💼

Dr. Xiaoming Zhang currently serves as a faculty member at the School of Information Engineering, Inner Mongolia University of Science and Technology, where he has been engaged in teaching and scientific research since July 2020. Over the past years, he has actively contributed to the advancement of new energy systems and thermal engineering. Dr. Zhang has successfully led multiple research projects, including one funded by the Inner Mongolia Natural Science Fund, one provincial and ministerial-level talent project, and one enterprise-collaborated horizontal project.

Research Interest 🔬📈

  • New energy development and utilization

  • Integrated energy system planning and optimization

  • Thermal energy storage using molten salt technology

  • Organic Rankine Cycle (ORC) systems

  • Application of machine learning in energy systems

  • Solar thermal power systems

Publications Top Note 📝

1. Zhang X., Ding C., Liang G., Yang P., Wang X.

Title: Research on integrated energy system planning based on the correlation between wind power and photovoltaic output
Journal: IET Renewable Power Generation
Year: 2024
Pages: 1–12
Highlights:

  • Investigates coordinated planning methods for integrated energy systems

  • Focuses on wind-PV output correlation to enhance energy system efficiency

2. Zhang X. M., Zhang C. C., Wu Y. T., Lu Y. W.

Title: Experimental research of high temperature dynamic corrosion characteristic of stainless steels in nitrate eutectic molten salt
Journal: Solar Energy
Volume: 209
Year: 2020
Pages: 618–627
Highlights:

  • Examines corrosion behavior of stainless steel in high-temperature molten salt

  • Provides experimental data for thermal energy storage design

3. Zhang X. M., Wu Y. T., Ma C. F., et al.

Title: Experimental Study on Temperature Distribution and Heat Losses of a Molten Salt Heat Storage Tank
Journal: Energies
Volume: 12(10)
Year: 2019
Article ID: 1943
Highlights:

  • Focus on thermal analysis of heat storage tanks using molten salt

  • Supports optimization of thermal storage in solar power plants

4. Zhang Xiaoming, Wu Yuting

Title: Energy and General Analysis of Trough Solar Thermal Power System
Journal: Journal of Solar Energy
Volume: 42(12)
Year: 2021
Pages: 9–16
Highlights:

  • Provides modeling and efficiency analysis of trough solar thermal systems

  • Useful for improving solar thermal plant design

5. Zhang Xiaoming, Wu Yuting, et al.

Title: Structure Design, Temperature Distribution and Stress Analysis of Large Molten Salt Tank
Journal: Journal of Beijing University of Technology
Volume: 47(9)
Year: 2021
Pages: 1064–1073
Highlights:

  • Covers mechanical stress and heat behavior in large-scale energy storage tanks

  • Combines finite element analysis with experimental validation

Conclusion 🌟🎯

Dr. Xiaoming Zhang is an outstanding candidate for the Research for Best Researcher Award, particularly in the field of Integrated Energy Systems. His research aligns with urgent global priorities—clean energy transition, system resilience, and optimization through AI. With high-quality publications, solid project leadership, and impactful research contributions, Dr. Zhang demonstrates the excellence and forward-thinking innovation the award intends to recognize.

Aimon Mirza Baig | Power Grid Stability | Best Researcher Award

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Aimon Mirza Baig | Power Grid Stability | Best Researcher Award

Mrs. Aimon Mirza Baig, Imperial College London, United Kingdom.

Aimon Mirza Baig is a PhD candidate at Imperial College London, specializing in Electrical and Electronics Engineering. His research focuses on real-time modeling of flexible assets for power grid stability in renewable energy-dominated systems. Aimon has contributed to innovative solutions for enhancing power grid security, co-optimizing ancillary services, and integrating zero-carbon sources like flexible nuclear power plants. He has presented his work at multiple international conferences and published in top journals. Aimon is passionate about teaching and mentoring future engineers, having held teaching roles at Imperial College London and in Saudi Arabia. 🌍⚡🔬

Publication Profile 

Scopus
Orcid

Education And Experiance

  • PhD in Electrical and Electronics Engineering, Imperial College London (2019-present)
    • Research: Real-time modeling for power grid stability with renewable energy sources ⚡
  • MSc in Advanced Electrical Engineering, Queen Mary University (2018-2019)
    • Dissertation: Optimizing lithium-ion battery state of charge 📊🔋
  • BEng in Electrical Engineering, University of Greenwich (2015-2018)
    • First-class honors 🎓
  • Graduate Teaching Assistant at Imperial College London (2020-present)
    • Taught optimization models and supervised PhD students 🧑‍🏫
  • Teaching Experience at Universal Enrichment Program, Riyadh, Saudi Arabia (2024)
    • Delivered STEM lectures and workshops for high school students 🌍🎓

Suitability For the Award

Mrs. Aimon Mirza Baig is an exceptional researcher specializing in power grid stability and renewable energy integration. His groundbreaking work, including the development of stochastic unit commitment models and co-optimization of ancillary services from zero-carbon sources, has significantly advanced the field. With a PhD from Imperial College London and multiple high-impact publications, Baig’s innovative contributions to energy systems, particularly in the context of flexible nuclear power and renewable integration, make him a highly deserving candidate for the Best Researcher Award. His expertise and research have the potential to shape the future of sustainable energy systems.

Professional Development

Aimon has continuously developed his skills in both research and teaching. At Imperial College London, he developed expertise in computational optimization models, using Python and C++ for real-time data simulations and system modeling. He also gained valuable teaching experience by assisting students in courses like “Control Systems Lab” and “Mathematics.” His ability to convey complex concepts to undergraduate students has honed his communication and mentoring skills. Aimon’s experience with international conferences and research publications further enriched his professional growth, allowing him to stay at the forefront of advancements in electrical engineering and renewable energy integration. 📚🌐💡

Research Focus

Aimon’s research is focused on power grid stability and renewable energy integration. He specializes in stochastic unit commitment models, optimizing ancillary services like inertia and frequency response from zero-carbon sources, including flexible nuclear power plants. His work aims to enhance system stability in grids with high penetration of renewable energy sources (RES). Aimon’s contributions to bi-level optimization and market design for virtual power plants help address the challenges of balancing energy production with grid security. His innovative models support the decarbonization goals of the UK and other nations. 🌱⚡🔧

Awards And Honors

  • PhD Scholarship at Imperial College London, funded by the IDLES Project (EDF Energy) 🎓💰
  • Awarded Distinction for MSc in Advanced Electrical Engineering, Queen Mary University 🏅
  • First-Class Honors for BEng in Electrical Engineering, University of Greenwich 🎖️
  • Conference Presentations at 6 international conferences in the UK and Europe 🎤🌍
  • Publications in High-Impact Journals: IEEE, Applied Energy, and International Journal of Electrical Power and Energy Systems 📑

Publication Top Notes 

  • Importance of Linking Inertia and Frequency Response Procurement: The Great Britain Case (2021) – Cited by 3 📚🔋
  • Market Design for Ancillary Service Provisions of Inertia and Frequency Response via Virtual Power Plants: A Non-Convex Bi-Level Optimisation Approach (2024) – Cited by 4 ⚡🔌
  • Co-optimising Frequency-Containment Services from Zero-Carbon Sources in Electricity Grids Dominated by Renewable Energy Sources (2025)  🌱🔋

Dr. yongliang shi | Reconstruction | Best Researcher Award

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Dr. yongliang shi | Reconstruction | Best Researcher Award

Dr. yongliang shi, Qiyuan Lab, China

Shi Yongliang is a dedicated researcher specializing in Navigation, Embodied AI, and 3D/4D Reconstruction. Currently serving as a Postdoctoral Researcher at Tsinghua University, his research focuses on advancing intelligent systems, particularly in robotics and autonomous navigation. He earned his Ph.D. in Bionics and Robotics from the Beijing Institute of Technology, where he cultivated his expertise in cutting-edge robotics technologies. Shi has published several notable works in top-tier journals and conferences, contributing significantly to the fields of robotic navigation, neural semantic mapping, and localization. His work aims to push the boundaries of AI-driven systems for real-world applications, particularly in smart cities and autonomous vehicles. Shi’s research has been recognized for its innovative approach to solving complex challenges in AI and robotics.

Professional Profile

scopus

Google scholar

Summary of Suitability for the Best Researcher Award

Shi Yongliang is an outstanding candidate for the Best Researcher Award. His research not only demonstrates innovation and technical mastery but also addresses real-world challenges in robotics and AI. His contributions to large-scale systems, combined with a consistent record of high-impact publications, make him highly suitable for this award.

🎓 Education 

Shi Yongliang holds a Ph.D. in Bionics and Robotics from the Beijing Institute of Technology, completed in 2021. His doctoral studies focused on developing advanced robotic systems and AI integration. Prior to that, he earned an M.Sc. in Precision Instruments and Machinery from North University of China in 2016, where he gained hands-on experience in machine design, instrumentation, and control systems. Shi began his academic journey with a Bachelor of Engineering in Vehicles Engineering from the same institution in 2013. His educational background has been instrumental in shaping his research in AI and robotics, providing a strong foundation in mechanical engineering, automation, and intelligent systems. Shi’s multidisciplinary education allows him to approach his research from a holistic perspective, integrating hardware and software solutions for robotics and autonomous systems.

 💼 Experience 

Shi Yongliang’s professional journey began with his role as a Postdoctoral Researcher at Tsinghua University’s Department of Computer Science and Technology, where he worked from October 2021 to December 2023. During this time, he contributed to several groundbreaking projects in the fields of robotics, navigation, and AI. Shi’s expertise spans the areas of 3D/4D reconstruction, semantic mapping, and global localization in large-scale environments. Before joining Tsinghua, he completed his Ph.D. at the Beijing Institute of Technology, focusing on robotics and AI integration. His early career also includes earning his Master’s degree in Precision Instruments and Machinery and Bachelor’s in Vehicles Engineering from North University of China, laying the groundwork for his advanced research. Shi’s work consistently pushes the frontiers of AI and robotics, making him a key contributor to the development of future intelligent systems.

 🏅Awards and Honors 

Shi Yongliang has been recognized with several prestigious awards for his contributions to robotics and AI. As a Postdoctoral Researcher at Tsinghua University, he received the “Best Paper Award” at the IEEE International Conference on Robotics and Automation (ICRA) in 2023 for his groundbreaking work on robotic global localization. During his Ph.D., he earned the “Excellence in Research Award” from the Beijing Institute of Technology for his innovative research on neural semantic mapping. Shi was also awarded the “Outstanding Graduate Researcher” title at North University of China during his Master’s studies. His achievements highlight his dedication to advancing autonomous systems and his impactful contributions to the fields of embodied AI, 3D/4D reconstruction, and smart city applications. Shi’s consistent performance in research and development has earned him a reputation as an emerging leader in AI and robotics.

🌍 Research Focus 

Shi Yongliang’s research focuses on three major areas: Navigation, Embodied AI, and 3D/4D Reconstruction. His work aims to address the challenges of robotic navigation in complex environments, with a particular emphasis on city-scale neural semantic mapping. Shi has developed innovative methods for robotic localization and mapping, applying AI to improve the accuracy and efficiency of autonomous systems. His research on 3D/4D reconstruction leverages AI to create dynamic, real-time representations of environments, which are essential for autonomous navigation. Shi is also actively exploring Embodied AI, which integrates physical systems with AI to enable robots to perform tasks in real-world environments more effectively. His work has significant implications for the development of autonomous vehicles, smart cities, and intelligent navigation systems, pushing the boundaries of AI-driven robotics.

 📖 Publication Top notes

  • Mars: An instance-aware, modular and realistic simulator for autonomous driving
    • Cited by: 63
  • Latitude: Robotic global localization with truncated dynamic low-pass filter in city-scale nerf
    • Cited by: 36
  • Design of a hybrid indoor location system based on multi-sensor fusion for robot navigation
    • Cited by: 30
  • Robotic binding of rebar based on active perception and planning
    • Cited by: 25
  • LCPF: A particle filter lidar SLAM system with loop detection and correction
    • Cited by: 23

Dr. Elaheh Yaghoubi | Power System Awards | Best Researcher Award

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Dr. Elaheh Yaghoubi | Power System Awards | Best Researcher Award

Dr. Elaheh Yaghoubi, Karabuk University, Turkey

Elaheh Yaghoubi is a Ph.D. candidate in Electronic and Electrical Engineering at Karabuk University, Turkey, with a perfect GPA of 4.0. Her research focuses on power system analysis, microgrids, power control in smart grids, model predictive control (MPC), and renewable energy. Elaheh earned her M.Sc. in Electrical Engineering from Islamic Azad University, Iran, and has a strong background in quality control, having worked as a senior manager in electronics companies and as a representative for the Iran Standard Organization. She is proficient in various programming languages and software tools and is actively involved in the PEDAR research group. Her notable research includes optimizing power control for grid-connected distributed generation and enhancing security in smart power microgrids.

Professional Profile:

Google Scholar

Evaluation for Elaheh Yaghoubi’s Suitability for the Best Researcher Award

Elaheh Yaghoubi’s exceptional research in power systems, smart grids, and renewable energy, combined with her perfect academic record and practical experience, position her as an excellent candidate for the Best Researcher Award. Her contributions to optimizing power control and enhancing smart grid security, along with her commitment to academic and research excellence, make her a deserving recipient of this prestigious recognition.

🎓Education:

Elaheh Yaghoubi is currently pursuing a Ph.D. in Electronic and Electrical Engineering at Karabuk University, Turkey, where she maintains a perfect GPA of 4.0. Her research focuses on optimal power control of grid-connected distributed generation within a hierarchical framework based on Model Predictive Control (MPC). She earned her M.Sc. in Electrical Engineering from Islamic Azad University, Qaemshahr, Iran, also with a perfect GPA of 4.0, where her thesis involved developing a routing algorithm for a large-scale chip grid. She completed her B.Sc. in Electrical Engineering at Aryan Institute of Science and Technology University, Iran, graduating with a GPA of 4.0, and holds an Associate’s Degree in Electrical Engineering from the University College of Rouzbahan, Iran, with a GPA of 3.5.

🏢Work Experience:

Elaheh Yaghoubi is currently a Principal Researcher at the Power Electrical Developing Advanced Research (PEDAR) Group, a position she has held since 2023. Prior to this, she worked as a Website Designer at WebCore Company from 2019 to 2021. She also has experience as a Senior Manager at Rico Electronics Company (2018-2019) and at Kati Kabl Tabarestan Factory (2015-2018).

🏅Awards and Honors:

Elaheh Yaghoubi has been recognized with the Best Researcher Award, highlighting her significant contributions and achievements in her field of study.

Publication Top Notes:

  • The Role of Mechanical Energy Storage Systems Based on Artificial Intelligence Techniques in Future Sustainable Energy Systems
    • Citations: 14
  • Triple-Channel Glasses-Shape Nanoplasmonic Demultiplexer Based on Multi Nanodisk Resonators in MIM Waveguide
    • Citations: 12
  • Electric Vehicles in China, Europe, and the United States: Current Trend and Market Comparison
    • Citations: 10
  • Tunable Band-Pass Plasmonic Filter and Wavelength Triple-Channel Demultiplexer Based on Square Nanodisk Resonator in MIM Waveguide
    • Citations: 10
  • Reducing the Vulnerability in Microgrid Power Systems
    • Citations: 9