Ms. Xiaohua Li | Machine Learning | Excellence in Research Award

Published on 02/12/202502/12/2025 by Electrical Engineering

Ms. Xiaohua Li | Machine Learning | Excellence in Research Award

Associate Professor | Shanghai Electric Power University | China

Dr. Li Xiaohua, a distinguished Professor at Sichuan University and leading expert in materials science and structural engineering, is renowned for advancing high-performance composite materials and sustainable structural systems. She holds advanced degrees in materials engineering with specialization in composite behavior and structural performance, complemented by extensive experience in academic leadership, project supervision, and collaborative research initiatives. Her professional portfolio includes directing major institutional projects, mentoring interdisciplinary teams, and contributing to engineering innovations that strengthen the reliability and resilience of modern structures. Dr. Li’s research focuses on composite structures, fire-resistant materials, mechanical behavior, and performance optimization, supported by 297 citations, 34 scholarly documents, and an h-index of 11, reflecting her growing global impact. She has authored influential publications, contributed to high-level research panels, and advanced knowledge dissemination through editorial responsibilities and membership in professional engineering societies. Recognized for excellence in research, innovation, and service, she also holds relevant professional certifications that underscore her commitment to scientific rigor and continued advancement in the engineering sciences.

Profile: Scopus

Featured Publications

Li Xiaohua*, Probabilistic forecasting of coal consumption for power plants under deep peak shaving conditions using Informer with DDPM-based uncertainty modeling. Int. J. Electr. Power Energy Syst., 2025.

Li Xiaohua*, Electromagnetic vibration characteristics of permanent magnet synchronous motors with segmented grain-oriented electrical steel teeth–yoke.

Li Xiaohua, Research on core loss prediction of low-frequency transformer based on Grey Wolf optimisation algorithm optimised Back Propagation neural network. IET Electr. Power Appl., 2025.

Dr. Salam Bani Hani | Nursing and Medical Feilds | Best Researcher Award

Published on 02/12/202502/12/2025 by Electrical Engineering

Dr. Salam Bani Hani | Nursing and Medical Feilds | Best Researcher Award

Assisstant Professor | Irbid National University | Jordan

Dr. Salam Bani Hani is an Assistant Professor and Head of the Nursing Department at Irbid National University, recognized for her expertise in nursing research, healthcare quality, digital health, and clinical education. She holds a PhD in Nursing Philosophy with a specialization in large-scale data applications for predicting cardiovascular conditions, an MSc in Nursing Service Administration, and a BSc in Nursing. Her professional experience includes academic leadership, clinical instruction across diverse nursing specialties, patient and family education, and clinical practice in emergency and critical care settings. Dr. Bani Hani’s research focuses on cardiovascular disease prediction using artificial intelligence, nursing education, digital health literacy, patient safety, chronic disease management, and public health issues affecting vulnerable communities. She has an extensive record of publications across reputable Scopus-indexed journals, contributing empirical studies, systematic reviews, and interdisciplinary collaborations. She has delivered multiple professional workshops on life support, documentation, pain management, and clinical communication, and has actively participated in scientific conferences as a speaker, trainer, and rapporteur. Her professional service includes reviewing for peer-reviewed journals, contributing to academic committees, and supporting program development and training initiatives. She has received national recognition, including a distinguished nursing shield, and has earned certifications that enhance her clinical and academic proficiency. Dr. Bani Hani’s scholarly impact is reflected in 333 citations, 63 published documents, and an h-index of 8.

Profile: Scopus | ORCID

Featured Publications

Bani Hani, Salam, Jordanian nursing students’ perceptions of the compassionate actions of their clinical instructors: a mixed-methods study. BMC Nursing, 2025.

Bani Hani, Salam, Barriers affecting safe practice of oxygen administration to critical ill children. Journal of Pediatric Nursing, 2025.

Bani Hani, Salam, Preoperative anxiety, postoperative pain tolerance and analgesia consumption: A prospective cohort study. Journal of Perioperative Practice, 2025.

Bani Hani, Salam, Knowledge and practices of Jordanian university students regarding food safety and handling. Nutrition and Food Science, 2025.

Bani Hani, Salam, Depression and Anxiety among Adolescents with Type 1 Diabetes Mellitus: Systematic Review of Literature. The Open Nursing Journal, 2025.

Prof. Xianglong Xu | Artificial Intelligence Prediction Tools | Research Excellence Award

Published on 02/12/202502/12/2025 by Electrical Engineering

Prof. Xianglong Xu | Artificial Intelligence Prediction Tools | Research Excellence Award

Research Professor | Shanghai University of Traditional Chinese Medicine | China

Dr. Xianglong Xu, a Research Professor at Shanghai University of Traditional Chinese Medicine specializing in AI-enabled epidemiology and predictive health analytics, holds a Ph.D. in Epidemiology with advanced expertise in chronic disease modelling and public health informatics. His professional experience spans roles as a young researcher, master’s supervisor, and project leader, contributing to multidisciplinary initiatives that integrate artificial intelligence with clinical practice and community health systems. Dr. Xu has led the development of innovative digital health tools, large-scale preventive health databases, and collaborative programs with hospitals and public health centers, strengthening data-driven decision-making across diverse populations. His research focuses on chronic disease risk assessment, AI-driven health prediction models, digital health evaluation, and the integration of Traditional Chinese Medicine concepts into modern epidemiology, supported by significant scholarly output and impactful scientific contributions. He has published extensively in peer-reviewed journals, contributed to theoretical and applied advancements in intelligent health analytics, and served on editorial boards while reviewing for leading international journals. His professional affiliations include membership in the International Epidemiological Association, IEEE and EMBS, national rehabilitation committees, and multiple scientific societies, complemented by recognitions across national and international platforms. 1,441 Citations, 71 Documents, 21 h-index.

Profiles: Scopus

Featured Publications

Xu, Xianglong*, Urban and rural disparities in stroke prediction using machine learning among Chinese older adults. Scientific Reports, 2025.

Xu, Xianglong*, External validation of a web- and artificial intelligence-based HIV/STI risk assessment tool: performance evaluation using data from Sydney sexual health centre. BMC Infectious Diseases, 2025.

Xu, Xianglong*, Anxiety responses and testing intentions among gay and bisexual men using an AI-powered HIV/STI risk assessment tool: a quasi-experimental study. BMC Public Health, 2025.

Xu, Xianglong, Comparative analysis of cardiometabolic multimorbidity predictors in China and the USA: A machine learning approach. Diabetes Research and Clinical Practice, 2025.

Xu, Xianglong, Development of a web-based tool using machine learning algorithms to improve adherence to diagnostic colonoscopy among middle-aged and elderly adults in colorectal cancer screening program. Annals of Epidemiology, 2025.

Xu, Xianglong, Determinants and geographical variations in oral traditional Chinese medicine use among middle-aged and elderly chronic adults in China: A cross-sectional study. European Journal of Integrative Medicine, 2025.

Xu, Xianglong, Geographical distribution disparities and prediction of health satisfaction among middle-aged and elderly adults in China: An analysis based on national data. Annals of Epidemiology, 2025.

Prof. Fazhi Song | Control Systems & Optimization | Research Excellence Award

Published on 02/12/202502/12/2025 by Electrical Engineering

Prof. Fazhi Song | Control Systems & Optimization | Research Excellence Award

Professor | Harbin Institute of Technology | China

Dr. Fazhi Song, Professor in the School of Instrumentation Science and Engineering at Harbin Institute of Technology, is a leading specialist in control science and precision motion systems whose work advances high-end manufacturing and inspection technologies. With a Ph.D. in Control Science and Engineering and research expertise spanning motion generation, performance control, learning control, and system accuracy retentivity, he has built a distinguished academic and professional record through roles as researcher, lecturer, associate professor, and project leader on numerous advanced engineering projects. He has authored more than forty peer-reviewed publications, contributed a research monograph, and secured an extensive portfolio of patents and software copyrights, reflecting strong innovation and impact in precision motion control. His scholarly influence is further demonstrated by 432 citations across 367 documents, 45 indexed publications, and an h-index of 9. Dr. Song has been recognized with major honors, including high-level national and provincial awards for technological invention, innovation, and academic contribution, and he maintains active professional service as guest editor, editorial board member, conference session chair, peer reviewer for leading journals, and expert evaluator for national research programs. His contributions exhibit a blend of scientific rigor, technological advancement, and leadership, positioning him as an exemplary candidate for award recognition.

Profiles: Scopus | ORCID

Featured Publications

Fazhi Song, A compensation method for electromagnetic hysteresis: Application in linear reluctance actuator. J. Magn. Magn. Mater., 2025.*

Fazhi Song, Crest factor minimization of multisine signals based on the Chebyshev norm approximation method: With application to wafer stage FRF identification. Results Eng., 2025.*

Fazhi Song, Identification for precision mechatronics: An auxiliary model-based hierarchical refined instrumental variable algorithm. Int. J. Robust Nonlinear Control, 2025.*

Fazhi Song, Beyond performance of learning control subject to uncertainties and noise: A frequency-domain approach applied to wafer stages. IEEE/CAA J. Autom. Sinica, 2025, 5 citations.*

Assoc. Prof. Dr. Guanlong Jia | Electric Engineering | Research Excellence Award

Published on 02/12/202502/12/2025 by Electrical Engineering

Assoc. Prof. Dr. Guanlong Jia | Electric Engineering | Research Excellence Award

Associate Professor | Hebei University of Technology | China

Guanlong Jia, Lecturer at Hebei University of Technology and a Member of IEEE, is a researcher specializing in high-power electronics with expertise in circuit breakers, multilevel converters, control algorithms, and pulse-width modulation techniques. He holds a Ph.D. in electrical engineering from Zhejiang University, where he focused on advanced power electronic systems and their reliability. In his professional capacity, he contributes to teaching and research in power conversion technologies, participating in institutional and collaborative projects that enhance innovation in electrical engineering. His research centers on the design, analysis, and optimization of high-power electronic devices, and his contributions are reflected in his scholarly publications and technical advancements in power electronics. He is recognized for his academic engagement and his role in supporting the wider research community through professional membership and ongoing contributions to the field. At the end of his academic profile: 295 citations, 42 documents, and an h-index of 7.

Profile: Scopus

Featured Publications

Jia, Guanlong*, Transient stability enhancement method for virtual synchronous generators using power-angle deviation with a modified reactive-power control loop. Electronics (Switzerland), Accepted.

Jia, Guanlong*, Multi-objective optimization design of fast vacuum switch operating mechanisms for hydrogen-storage power systems. AIP Advances, Accepted.

Jia, Guanlong, Dynamics simulation and fault-characteristic analysis of permanent-magnet repulsion mechanisms for vacuum circuit breakers integrating advanced high-power switching technologies. AIP Advances, Accepted.

Prof. Qie Sun | Power System Stability & Control | Research Excellence Award

Published on 02/12/202502/12/2025 by Electrical Engineering

Prof. Qie Sun | Power System Stability & Control | Research Excellence Award

Director | Shandong University | China

Prof. Qie Sun, Professor and doctoral supervisor at Shandong University and Deputy Dean of the Institute for Advanced Technology, is a leading expert in sustainable energy systems, thermal science, and integrated energy system optimization. He holds a doctorate in Industrial Ecology from the Royal Institute of Technology and bachelor’s and master’s degrees in management from Ocean University of China. His professional experience encompasses academic leadership roles, major interdisciplinary collaborations, and the management of high-impact projects in multi-energy systems, CO₂ capture and utilization, thermal management technologies, and energy storage solutions. He has led and contributed to numerous national and provincial research initiatives and played a key role in the thermal control research of the Alpha Magnetic Spectrometer. His research focuses on integrated energy systems, system flexibility under uncertainty, multi-energy coupling modeling, thermal management for electronics and wearable devices, urban energy systems, and industrial ecology, supported by extensive scholarly output that includes over 140 documents, 5,302 citations, and an h-index of 33. Prof. Sun has received multiple honors, including global top scientist recognitions, best paper awards, outstanding reviewer awards, and teaching excellence distinctions. He serves as Assistant Editor of Advances in Applied Energy, Associate Editor for several prominent journals, reviewer for numerous high-impact publications, and an active member of professional bodies such as IEEE and the Chinese Society of Engineering Thermophysics. Through his editorial leadership, scientific committee roles, and contributions to international conferences, Prof. Sun continues to advance innovation and global scholarship in sustainable energy research.

Profile: Scopus

Featured Publications

Sun, Q.*, The flexibility of a molten salt thermal energy storage (TES)-integrated coal-fired power plant. Applied Energy, 2025.

Sun, Q.*, Dynamically tunable silica hydrogel windows enabled by hydration state control for enhanced building energy efficiency. Applied Thermal Engineering, 2025.

Sun, Q.*, Impact of dust composition on parabolic trough concentrator performance across diverse regions. Solar Energy, 2025.

Sun, Q.*, The review of key furnaces in CaC₂ smelting process under the background of carbon neutrality. Review, 2025.

Sun, Q.*, A thin and lightweight miniature loop heat pipe for cooling mobile electronic devices. Device, 2025.

Dr. Muhammad Tariq | Animal Reproduction | Research Excellence Award

Published on 01/12/202501/12/2025 by Electrical Engineering

Dr. Muhammad Tariq | Animal Reproduction | Research Excellence Award

Ph.D Scholar | College of Animal Science and Technology | China

Muhammad Tariq, a dedicated researcher and Ph.D. candidate at the College of Animal Science and Technology, Nanjing Agricultural University, specializes in animal science with core expertise in animal genetics, molecular parasitology, and molecular biology. He holds an MPhil in Zoology from Cholistan University of Veterinary and Animal Sciences with specialization in advanced biological techniques and aquatic toxicology, and a BS in Zoology from Bahauddin Zakariya University, where he gained a strong foundation in genetics, microbiology, physiology, and environmental sciences. His professional experience includes extensive laboratory and research work involving DNA and RNA extraction, PCR amplification, gel electrophoresis, microscopy, protein analysis, immunohistochemistry, immunofluorescence, and animal handling, contributing to multidisciplinary projects focused on parasitic diseases, reproductive physiology, livestock health, and sustainable aquaculture. He has authored numerous peer-reviewed publications addressing heat stress, reproductive biology, parasitic prevalence, molecular diagnostics, aquatic toxicology, and nanoparticle applications, and has contributed several book chapters on veterinary vaccines, mRNA technologies, livestock genetics, and CRISPR-based improvement. His academic achievements are further strengthened by active participation in international research collaborations, scholarly contributions to reputable journals, and commitment to advancing scientific knowledge. At the end of his profile, his research metrics reflect growing global impact, with 53 citations, an h-index of 4, and an i10-index of 3.

Profile: Google Scholar

Featured Publications

Tariq M*, Heat Stress and Its Impact on Corpus Luteum (CL) Function and Reproductive Efficiency in Mammals: A Critical Review. Reproductive Sciences, Accepted.

Tariq M*, Prevalence of trypanosomiasis caused by Trypanosoma evansi in domestic ruminants from Southern Punjab, Pakistan. [Journal], Accepted.

Tariq M*, Assessment of Babesia spp. prevalence in various domestic animals across Southern Punjab, Pakistan. Brazilian Journal of Biology, 2024, 84, e277636.

Tariq M*, Melatonin Modulates Necroptosis and Enhances Antioxidant Defense during PGF-Induced Luteal Regression in Heat-Exposed Rats. Pakistan Veterinary Journal, 2025, 45(1).

Tariq M*, Phytoestrogens Modulate Bovine GPCRs and Regulate Reproductive Functions in Animals. Reproduction in Domestic Animals, 2025, 60(3), e70033.

Tariq M*, FOXM1 Inhibits SUV39H1 to Regulate the CSE/H₂S Pathway in Promoting Ferroptosis of Gastric Cancer Cells. Pakistan Veterinary Journal, 2025, 45(1).

Tariq M*, Cryptosporidium Infection in Goats: Prevalence, Risk Factors, and Diagnostic Techniques. Frontiers in Veterinary Science, 2024, 11, 1498682.

Tariq M*, Growth performance and antioxidant status of freshwater carp under brackish water rearing. Aquaculture, 2025, 596, 741691.

Dr. Angel Sapena Bano | Modelling Machines for Optimization | Research Excellence Award

Published on 01/12/202501/12/2025 by Electrical Engineering

Dr. Angel Sapena Bano | Modelling Machines for Optimization | Research Excellence Award

Associate Professor | Universitat Politecnica de Valencia | Spain

Ángel Sapena Bañó, Profesor Titular at the Universitat Politècnica de València, is a specialist in electrical engineering with expertise in electrical machines, diagnostic methods, numerical modelling, and condition monitoring. He holds degrees in Industrial Engineering, Energy Technology for Sustainable Development, and Secondary Education, complemented by a doctorate in Industrial Engineering focused on advanced diagnostic techniques for electrical machines. His professional trajectory includes roles as Lecturer, Researcher, and Technical Specialist, contributing to major academic initiatives, laboratory modernization, and collaborative research activities. He has participated in multiple competitive and industrial R&D projects, developed fault-diagnosis tools for induction machines and wind-energy systems, and strengthened international cooperation through research stays and Erasmus teaching engagements. His research spans analytical and hybrid modelling, finite-element methods, machine-learning-based diagnostics, and real-time simulation, reflected in numerous high-impact journal articles, conference contributions, book chapters, and patented inventions. He has led and co-led research outputs as first and corresponding author, supervised a wide range of graduate projects, and contributed to organizing scientific conferences and special issues. His distinctions include recognized research merits, invited reviewer roles in indexed journals, participation in prominent research groups, and involvement in impactful national and international scientific initiatives. His scholarly record includes 1,035 citations, 60 documents, and an h-index of 17.

Profiles: Scopus | ORCID

Featured Publications

Ángel Sapena Bañó*, Model-based diagnostic techniques for induction machines under transient operational conditions. Int. J. Electr. Power Energy Syst., Accepted.

Ángel Sapena Bañó*, Hybrid FEM–analytical modelling framework for efficient fault detection in eccentric induction motors. Sensors, 2025, 25, 1–28.

Ángel Sapena Bañó, Deep learning–enhanced condition monitoring strategies for electrical machines operating in variable regimes. Mathematics and Computers in Simulation, 2025, 1–28.

Prof. Dong Jiang | Energy Storage Systems | Best Researcher Award

Published on 26/11/202526/11/2025 by Electrical Engineering

Prof. Dong Jiang | Energy Storage Systems | Best Researcher Award

Professor | Huazhong University of Science and Technology | China

Professor Dong Jiang, a leading scholar at Huazhong University of Science and Technology, is renowned for his expertise in power electronics, advanced motor drives, and electromagnetic interference mitigation. He holds a PhD in Electrical Engineering from the University of Tennessee and both bachelor’s and master’s degrees from Tsinghua University, where he specialized in high-performance converter design and control. His professional background includes service as a Senior Research Scientist and Engineer at the United Technologies Research Center, along with extensive leadership in major national and international research projects focused on multi-functional inverters, magnetic bearing systems, and high-reliability motor controllers. His research contributions span PWM converter optimization, EMI suppression, active magnetic bearings, and modern motor drive technologies, supported by an extensive publication record that includes numerous IEEE journal articles, conference papers, books, and a substantial portfolio of granted patents. He has earned multiple prestigious awards for scientific innovation, impactful publications, and technological breakthroughs while also contributing significantly to the scholarly community as an Associate Editor for IEEE Transactions on Industry Applications, Chairman of the IEEE PELS Wuhan Chapter, IET Fellow, and IEEE Senior Member. With more than 6450 citations, an h-index of 43, and an i10-index of 135, he stands as a highly influential figure in the global power electronics research community.

Profile: Google Scholar

Featured Publications

D. Jiang*, F. Wang, Current-ripple prediction for three-phase PWM converters, IEEE Transactions on Industry Applications 50(1), 531–538.

D. Jiang*, Z. Shen, F. Wang, Common-mode voltage reduction for paralleled inverters, IEEE Transactions on Power Electronics 33(5), 3961–3974.

D. Jiang*, Dead-time effect compensation method based on current ripple prediction for voltage-source inverters, IEEE Transactions on Power Electronics 34(1), 971–983.

D. Jiang*, R. Burgos, F. Wang, D. Boroyevich, Temperature-dependent characteristics of SiC devices: Performance evaluation and loss calculation, IEEE Transactions on Power Electronics 27(2), 1013–1024.

Prof. Qingsong Wang | Battery Safety | Research Excellence Award

Published on 25/11/202525/11/2025 by Electrical Engineering

Prof. Qingsong Wang | Battery Safety | Research Excellence Award

Group leader | University of Science and Technology | China

Professor Qingsong Wang is a Professor at the State Key Laboratory of Fire Science, University of Science and Technology of China, specializing in energy storage safety, lithium-ion battery fire dynamics, electric vehicle safety, and electric fire prevention. He holds a Ph.D. in Safety Science and Technology, a Master’s degree in Safety Science and Technology, and a Bachelor’s degree in Mining Engineering, forming a strong academic foundation for his interdisciplinary work in fire science and advanced energy systems. His professional experience spans significant academic leadership, international research collaboration, and major scientific projects focused on battery failure mechanisms, thermal runaway behavior, and fire-prevention technologies. Professor Wang has produced an extensive body of research with over 400 publications in high-impact journals, contributing critical advancements widely recognized across the global energy and safety research communities. His editorial contributions include service as guest editor, associate editor, and board member for prominent international journals, along with active participation in professional committees related to fire safety, combustion science, and energy storage systems. His distinguished honors include recognition as a Highly Cited Researcher, multiple first-prize Science and Technology Innovation Awards, prestigious fellowships, and international scientific accolades that reflect his sustained impact and leadership in the field. Citations 29602, h-index 88, i10-index 332.

Profile: Google Scholar

Featured Publications

Wang Qingsong*, Atmosphere-regulated thermal runaway characteristics and multidimensional safety assessment of sodium-ion and lithium-ion batteries. eTransportation, 2025, 100475.

Wang Qingsong*, Advanced ultra-pressure-resistant three-phase composite insulation: halting thermal runaway in lithium-ion batteries. Energy Storage Materials, 2025, 104148.

Wang Qingsong*, Experimental study on heat and gas generation characteristics of commercial sodium-ion batteries during thermal runaway. Journal of Energy Chemistry, 2025, 357–367.

Wang Qingsong*, Thermal runaway and gas venting behaviors of large-format prismatic sodium-ion batteries. Energy Storage Materials, 2025, 104197.

Wang Qingsong*, Molecular anchoring of free solvents for high-voltage and high-safety lithium-metal batteries. Nature Communications, 2024, 2033.