Muhammad Sohaib Tahir | Renewable Energy | Best Researcher Award

Mr. Muhammad Sohaib Tahir | Renewable Energy | Best Researcher Award

Muhammad Sohaib Tahir at Shanghai Jiao Tong University Pakistan.

Muhammad Sohaib Tahir is a multidisciplinary researcher and doctoral candidate at the China-UK Low Carbon College, Shanghai Jiao Tong University, jointly with The University of Edinburgh. With a diverse academic background in electronic, electrical, and mechanical engineering, he focuses on power engineering, thermophysics, and renewable energy systems. With over five years of industry experience and several international recognitions, Mr. Tahir actively contributes to research on photovoltaic-thermoelectric integration, electric vehicle modeling, and inverter design. He is a registered engineer with the Pakistan Engineering Council and a member of IEEE, demonstrating a strong commitment to innovation in low-carbon technologies.

Professional Profile.

Scopus

Orcid

Education 

  • Ph.D. in Mechanical Engineering (Power Engineering & Thermophysics)
    China-UK Low Carbon College
    Shanghai Jiao Tong University, China / University of Edinburgh, UK

  • M.Sc. in Electrical Engineering (Electric Power & Automation)
    Shanghai Jiao Tong University, China

  • B.Sc. in Electronic Engineering
    The Islamia University of Bahawalpur, Pakistan

Professional Experience 

Mr. Tahir has rich experience in both industry and academia. He worked as a Technical Support Engineer at ZKTeco Co. Ltd. in Shenzhen, China, where he contributed to hardware/software development, electric control systems, and PLC programming. Prior to that, he served as an Operation Site Engineer at Mobilink Telecom in Pakistan, managing BTS equipment and leading fault-handling operations for Huawei and Alcatel systems. His technical exposure includes simulation tools like MATLAB/Simulink, SolidWorks, and OriginLab, making him proficient in both energy system modeling and embedded control solutions.

Research Interest 

  • Renewable Energy Systems and Hybrid Technologies

  • Thermoelectric Cooling in Photovoltaic Modules

  • Electric Power & Automation Systems

  • Energy Storage and Inverter Design

  • Integration of Technology in Engineering Education

  • Electric Vehicle Ecosystem and Sustainability

Publications Top Noted

  1. Tahir, M.S., Dong, X., Khan, M.M.
    Mathematical and Simulation Modeling of Photovoltaic Systems Utilizing Thermoelectric Modules for Effective Thermal Management
    Results in Engineering, 2025. [DOI: https://doi.org/10.1016/J.RINENG.2025.106344]

  2. Tahir, M.S., Xu, J., Wang, Y.
    Novel CoolMosfet Clamping Three-Level Neutral-Point-Clamping Inverter for Low and Medium Power Applications
    IFEEC 2017 – ECCE Asia, IEEE International Conference, pp. 1949–1953.
    IEEE Accession No: 20174704419540

Conclusion 

Muhammad Sohaib Tahir exemplifies a rising talent in the fields of power engineering, sustainable energy, and automation. With his rich academic background, impactful publications, and cross-cultural research engagements, he represents a new generation of globally minded engineers. His proactive attitude, technical competence, and dedication to clean energy innovation make him a worthy candidate for international recognition. As he continues to contribute to research, technology integration, and global energy solutions, his future as a leader in sustainable engineering is promising.

Dr. Chunyan Zang | Renewable Energy | Best Researcher Award

Dr. Chunyan Zang | Renewable Energy | Best Researcher Award

Dr. Chunyan Zang, Huazhong University of Science and Technology, China

Dr. Chunyan Zang is a distinguished electrical engineer with over 24 years of experience in power systems, renewable energy, and AI-driven fault detection. As a Lecturer at Huazhong University of Science & Technology and a Guest Scholar at Lund University, Sweden, she has led groundbreaking research on smart grids, state evaluation, and power system optimization. She holds a Ph.D. in Electrical Engineering and has contributed to multiple high-impact projects, generating over 1 billion yuan in economic benefits. An active IEEE senior member, she has earned prestigious awards for her contributions to electrical engineering and scientific innovation.

🌍 Professional Profile:

Scopus

🏆 Suitability for Best Researcher Award

Dr. Chunyan Zang is an exemplary candidate for the Best Researcher Award due to her extensive contributions to electrical engineering, particularly in power transmission, smart grids, and renewable energy integration. Her research has significantly advanced fault detection and predictive maintenance, optimizing power systems’ efficiency and reliability. With numerous patents and over two decades of impactful research, she has pioneered innovative approaches using AI and data-driven technologies. Her leadership in major industry projects, academic mentoring, and recognition through prestigious awards further establish her as a leading researcher in the field.

🎓 Education

Dr. Chunyan Zang has an outstanding academic background, holding multiple degrees from Huazhong University of Science & Technology, China. She earned her Ph.D. in Electrical Engineering (2006), specializing in power system optimization and AI applications. She also holds an M.Sc. in High Voltage and Insulation Technology (2003), a B.Sc. in Electric Power Systems and Automation (2000), and a Minor in Computer Science (2000). Her education has provided her with a strong interdisciplinary foundation in electrical engineering, power systems, and computational methodologies, enabling her to drive cutting-edge innovations in the field.

💼 Professional Experience

Dr. Chunyan Zang has served as a Lecturer at Huazhong University of Science & Technology since 2006, teaching and mentoring undergraduate and postgraduate students. She has led numerous state-funded research projects on power generation, transmission, and distribution, contributing to advancements in smart grids and renewable energy. Currently, she is a Guest Scholar at Lund University, Sweden, researching 5G and 6G applications in strong electromagnetic environments. Her expertise in AI, fault detection, and power system diagnostics has been instrumental in shaping modern energy infrastructures and intelligent monitoring systems.

🏅 Awards & Honors

Dr. Chunyan Zang has been recognized with numerous prestigious awards, including the 2023 Prize for Outstanding Female Scientist Award and the Outstanding Volunteer Award from IEEE PES China. Her contributions have been honored with multiple Scientific and Technological Progress Awards, including in Hubei Province (2022), Shanxi Province (2021), and State Grid Shanxi Electric Power Company (2021). Additionally, she secured the First Prize of Science and Technology Progress Award from Tianjin Electric Power Corporation (2018). Her accolades reflect her groundbreaking research and leadership in electrical engineering.

🔍 Research Focus

Dr. Chunyan Zang’s research primarily focuses on renewable energy, AI-driven power system diagnostics, fault detection, and smart grids. She has pioneered new methodologies in green power electrolytic hydrogen technology, integrating sustainable energy solutions into modern power networks. Her work on state evaluation, risk assessment, and predictive maintenance has enhanced the reliability and efficiency of power transmission. She also explores wireless sensor networks for power grid monitoring, applying machine learning and data mining to optimize power infrastructure performance.

📖 Publication Top Notes 

  1. Comprehensive Evaluation of Proton Exchange Membrane Fuel Cell-Based Power System Fueled with Ammonia Decomposed Hydrogen
    • Year: 2025
  1. A New Popular Transition Metal-Based Catalyst: SmMn₂O₅ Mullite-Type Oxide
    • Year: 2024
    • Citations: 5
  2. Metallic Co with Reactive Element Oxide Composite Coatings for Solid Oxide Fuel Cell Interconnect Applications
    • Year: 2023
    • Citations: 2
  1. Research Progress on Metal Particle Issues Inside Gas-Insulated Lines (GIL)
    • Year: 2024
  2. Intelligent Diagnosis Model of Mechanical Fault for Power Transformer Based on SVM Algorithm
    • Year: 2023
    • Citations: 8