Jawad Faiz | Electrical Machines | Research Excellence Award

Published on by Global Energy Awards

Research Excellence Award

Jawad Faiz
University of Tehran, Iran
Jawad Faiz
Affiliation University of Tehran
Country Iran
Scopus ID 7005657474
Documents 7740
Citations 10456
h-index 55
Subject Area Electrical Machines
Event Global Energy Awards

Jawad Faiz is an academic researcher associated with the University of Tehran and is recognized for extensive scholarly contributions in the field of electrical machines and energy-related engineering research. His publication record, citation impact, and sustained engagement with scientific advancement demonstrate a notable academic profile within international engineering communities.[1]

Abstract

This article presents an overview of Jawad Faiz and his academic achievements in electrical machines research. His scholarly work spans machine design, performance analysis, energy systems, and industrial applications. The breadth of publications and measurable citation influence indicate a sustained contribution to engineering knowledge and technological advancement.[2]

Keywords

Electrical Machines, Induction Motors, Permanent Magnet Machines, Energy Conversion, Power Engineering, Electromagnetic Design, Fault Diagnosis, Rotating Machinery, Sustainable Energy Systems, Engineering Research Excellence.

Introduction

The field of electrical machines remains central to modern power and energy infrastructures. Researchers working in this discipline contribute to efficiency improvements, reliability enhancement, and advanced machine modeling. Jawad Faiz has participated in these developments through extensive academic investigations and peer-reviewed scholarly output.[3]

Research Profile

With thousands of indexed documents and a significant citation record, Jawad Faiz maintains a visible presence within international engineering literature. His research portfolio reflects long-term engagement in machine analysis, design optimization, and practical engineering applications that support academic and industrial communities alike.[1]

Research Contributions

Major contributions associated with his work include electromagnetic modeling techniques, advanced motor performance evaluation, fault diagnosis methodologies, and innovative machine configurations. These studies have supported improved understanding of rotating electrical systems and contributed to engineering education and industrial practice.[4]

Publications

The publication record of Jawad Faiz includes journal articles, conference papers, technical reviews, and collaborative engineering studies. His scholarly output frequently addresses electrical machine design, electromagnetic performance, and power conversion systems. Many of these works have been cited by researchers investigating modern machine technologies and energy applications. The consistency of publication activity demonstrates sustained academic engagement over multiple years.[5]

Research Impact

Citation metrics and scholarly visibility suggest that his research has influenced subsequent investigations in electrical engineering. Academic recognition is reflected through references to his work in journals, conference proceedings, and technical studies. Such indicators support the relevance of his contributions within the broader research ecosystem.[2]

Award Suitability

The documented publication volume, citation impact, and specialization in electrical machines align with evaluation criteria commonly applied to international research recognition programs. His academic record reflects sustained scholarly productivity and contribution to engineering knowledge, supporting consideration for recognition within the Global Energy Awards framework.

Conclusion

Jawad Faiz represents an established academic profile in electrical engineering with measurable scholarly influence. Through extensive research output, citation performance, and contributions to electrical machine technologies, he has participated in advancing engineering understanding and supporting continued innovation within the field.

References

  1. Tizbakhsh, A., Faiz, J., & Ghods, M. (2026). High-fidelity thermal modeling and experimental validation of V-shaped PM vernier motors for electric mobility. Thermal Science and Engineering Progress.
    https://www.sciencedirect.com/journal/thermal-science-and-engineering-progress
  2. Abareshi, S., Faiz, J., & Mohammadi, F. (2026). Investigation of the Flux-Weakening Capability and Performance of Flux Modulation Motors from Start up to 5 Times the Rated Speed. Arabian Journal for Science and Engineering.
    https://link.springer.com/article/10.1007/s13369-025-10704-x
  3. Faiz, J., Haghvirdiloo, S., & Ghaffarpour, A. (2025). Different Types of Electrical Generators for Converting Wave Energy into Electrical Energy – A Review.
    https://link.springer.com/article/10.1007/s11804-025-00621-8
  4. Ghods, M., Tabarniarami, Z., Faiz, J., & Abedini, M. (2025). Diagnosis of Demagnetization in Permanent Magnet Flux Modulation Machines With Fractional Slot Concentrated Winding. IEEE Transactions on Industrial Electronics.
    https://ieeexplore.ieee.org/document/10891252
  5. Ghods, M., Faiz, J., Bazrafshan, M. A., Gorginpour, H., & Toulabi, M. S. (2025). A Mathematical and Dynamical Model for Analyzing H-Shaped PM Vernier Motor for Electric Motorcycle Mid-Drive Applications. IEEE Transactions on Energy Conversion.
    https://ieeexplore.ieee.org/document/10634793

Hemaraju Pollayi | Stability of Slopes | Innovative Research Award

Published on by Global Energy Awards

Innovative Research Award

Hemaraju Pollayi
Affiliation GITAM Deemed to be University Hyderabad
Country India
Scopus ID 24341843600
Documents 61
Citations 61
h-index 4
Subject Area Stability of Slopes
Event Global Energy Awards
ORCID 0009-0002-1450-4309

Hemaraju Pollayi
GITAM Deemed to be University Hyderabad, India

Machine learning in physics has emerged as a multidisciplinary research domain that combines computational intelligence with engineering and physical sciences. Research contributions associated with Hemaraju Pollayi include applications of machine learning, structural health monitoring, computational modelling, seismic analysis, soil–structure interaction, and infrastructure engineering. These studies demonstrate the integration of data-driven approaches with physical modelling frameworks for improved engineering decision-making and predictive analysis.[1]

Abstract

This article summarizes the academic profile of HEMARAJU POLLAYI with emphasis on machine learning applications in physics-based engineering systems. The body of work includes computational modelling, structural monitoring, climate-related prediction frameworks, and intelligent infrastructure analysis. Research outputs demonstrate the adoption of artificial intelligence techniques alongside traditional analytical approaches for solving engineering challenges.[2]

Keywords

Machine Learning, Physics, Structural Health Monitoring, Artificial Intelligence, Soil–Structure Interaction, Climate Modelling, Seismic Engineering, Wireless Sensor Networks, Infrastructure Analytics, Computational Engineering.

Introduction

Recent advances in machine learning have enabled researchers to address complex physical and engineering phenomena through data-driven methodologies. Contributions by HEMARAJU POLLAYI illustrate how computational intelligence can complement theoretical and experimental investigations. The resulting studies contribute to predictive modelling, optimization, and reliability assessment in engineering systems.[3]

Research Profile

HEMARAJU POLLAYI is affiliated with GITAM Deemed to be University Hyderabad and maintains a documented research profile through ORCID and Scopus. Published work spans journal articles, conference papers, and book chapters covering artificial intelligence, structural engineering, composite materials, and computational mechanics. The profile reflects sustained engagement in interdisciplinary engineering research.[1]

Research Contributions

Research contributions include machine learning-based structural health monitoring of bridges, climate modelling using deep learning frameworks, earthquake engineering applications, and soil–structure interaction modelling. Several studies integrate Python-based computational methods with engineering analysis, demonstrating the practical use of artificial intelligence in physical systems. These contributions support improved monitoring, prediction, and infrastructure management strategies.[2]

Publications

Selected publications include studies on IoT-based bridge monitoring, machine learning approaches for reinforced concrete structures, climate crisis modelling, seismic performance analysis, and healthcare-oriented artificial intelligence systems. The publication record demonstrates continuing interest in applying computational intelligence across diverse engineering and scientific domains while maintaining relevance to real-world applications.[4]

Research Impact

The documented citation record and publication portfolio indicate measurable academic engagement within engineering and applied science communities. Research outputs have contributed to discussions on infrastructure resilience, computational modelling, and intelligent monitoring technologies. The interdisciplinary nature of the work supports knowledge exchange across multiple scientific fields.[5]

Award Suitability

The research profile aligns with themes commonly recognized by international innovation and engineering award programs. Areas such as machine learning, sustainable infrastructure, intelligent monitoring, and computational engineering correspond with contemporary priorities in global energy and technology sectors. Such alignment provides a scholarly basis for consideration within research-focused recognition initiatives.

Conclusion

Machine learning continues to influence modern engineering and physics-oriented research through enhanced predictive capabilities and analytical efficiency. The body of work associated with HEMARAJU POLLAYI demonstrates the integration of artificial intelligence with engineering science, contributing to structural monitoring, computational modelling, and infrastructure assessment. These activities reflect ongoing engagement with emerging interdisciplinary research directions.

References

  1. Elsevier. (n.d.). Scopus author details: HEMARAJU POLLAYI, Author ID 24341843600. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=24341843600
  2. Chakali, D., Pollayi, H., & Rao, P. (2024). IoT based structural health monitoring of bridges using wireless sensor networks. Asian Journal of Civil Engineering.
    https://doi.org/10.1007/s42107-024-01152-3
  3. Chakali, D., Rao, P., Pollayi, H., & Khan, M.A. (2024). Machine Learning based Structural Health Monitoring of Bridge using K-Means Clustering Algorithm in Python. AIP Conference Proceedings.
    https://doi.org/10.1063/5.0193881
  4. Pollayi, H., Rao, P., Chakali, D., & Bandaru, P. (2024). Development of deep learning models for climate change within python framework. Computational Modeling Applications for Climate Crisis.
    https://doi.org/10.1016/B978-0-443-21905-4.00008-0
  5. Pollayi, H., Rao, P., & Bandaru, P. (2022). Machine Learning-Based Approach for Modelling Soil-Structure Interaction Effects on Reinforced Concrete Structures Subjected to Earthquake Excitations. Handbook of Research on Applied Artificial Intelligence and Robotics for Government Processes.
    https://doi.org/10.4018/978-1-6684-5624-8.ch014

Dr. Yali Liu | Exoskeleton Robots | Best Researcher Award

Published on by Global Energy Awards

Dr. Yali Liu | Exoskeleton Robots | Best Researcher Award

Beijing Institute of Technology | China

Dr. Yali Liu is an accomplished researcher and Assistant Professor at the School of Mechatronics Engineering, Beijing Institute of Technology, specializing in exoskeleton robotics, biomechanics, and human–machine interaction. Her research focuses on developing high-power assistive and load-bearing exoskeleton systems, emphasizing mechanical design, ergonomic performance, gait analysis, and adaptive control. As a Principal Investigator for several major projects—including the High-Power Exoskeleton Robot Development, Ergonomic Performance Analysis of Protection-Carrying Systems, and Expandable Backpack-Carrying Systems—Dr. Liu has advanced innovative technologies to improve human mobility, load assistance, and comfort in wearable robotics. Her postdoctoral work concentrated on biomechanical modeling and physiological simulation, supported by national and military science foundations. She has led projects on motion pattern recognition, posture prediction, and human performance evaluation, contributing significantly to the design and control of lower-limb exoskeletons. Dr. Liu has published extensively, with over 14 SCI-indexed papers and several EI-indexed publications in leading journals such as IEEE Journal of Biomedical and Health Informatics, IEEE Sensors Journal, Robotics and Autonomous Systems, and Computers in Biology and Medicine. Her studies cover key areas like continuous gait prediction, sEMG-based motion estimation, sensor optimization, and adaptive exoskeleton control algorithms. Through her comprehensive expertise in human motion analysis, assistive robotics, and neural network–based control systems, Dr. Liu has established herself as a leading researcher in wearable robotics, contributing both theoretical insights and practical innovations that enhance human performance and rehabilitation technologies.

Profile:  Scopus |Orcid

Featured Publications

Xinyu Guan; Hanyu Chen; Yali Liu; Ziwei Zhang; Linhong Ji (2025). Predicting ground reaction forces and center of pressures from kinematic data in crutch gait based on LSTM. Medical Engineering & Physics

Xunju Ma; Yali Liu; Xiaohui Zhang; Lorenzo Masia; Qiuzhi Song (2025). Real-Time Continuous Locomotion Mode Recognition and Transition Prediction for Human With Lower Limb Exoskeleton. IEEE Journal of Biomedical and Health Informatics

Liping Huang, Jianbin Zheng, Yifan Gao, Qiuzhi Song & Yali Liu (2025). A Lower Limb Exoskeleton Adaptive Control Method Based on Model-free Reinforcement Learning and Improved Dynamic Movement Primitives. Journal of Intelligent and Robotic Systems Theory and Applications

Ye Liu, Qiuzhi Song, Hongbin Deng, Yali Liu, Pengwan Chen & Kun Huang (2025). Analysis of electrical characteristics of electric explosion wire in different environments based on normal model. Electrical Engineering

Yue Liu; Yali Liu; Qiuzhi Song; Dehao Wu; Dongnan Jin (2024). Gait Event Detection Based on Fuzzy Logic Model by Using IMU Signals of Lower Limbs [J]. IEEE Sensors Journal,

Zharilkassin Iskakov | Theoretical Advances | Best Researcher Award

Published on by Global Energy Awards

Prof. Dr. Zharilkassin Iskakov | Theoretical Advances | Best Researcher Award

Prof. Dr. Zharilkassin Iskakov | Institute of Mechanics and Engineering named after academician U.A. Dzholdasbekov | Kazakhstan

Prof. Zharilkassin Iskakov is a distinguished Kazakh mechanical engineer and physicist with over 50 years of academic and research experience. He has held key positions in top scientific institutions, notably the Institute of Mechanics and Machine Science in Almaty, where he currently leads the Laboratory of Nonlinear Dynamics of Gyroscopic Rotary Machines. His career began in 1974 as a physics lecturer, steadily advancing through roles of increasing responsibility. Professor Iskakov has made significant contributions to nonlinear mechanics, rotor dynamics, and vibration systems, earning national recognition and multiple prestigious grants. He has also served in educational leadership roles, including department head and associate professor at renowned Kazakh universities. His dedication to advancing engineering education and scientific research has earned him high-level academic titles, including Full Professor in Mechanical Engineering. A pioneer in his field, Professor Iskakov’s work continues to shape the understanding and development of complex mechanical systems in Kazakhstan and beyond.

Author Profile

Scopus | ORCID

Education 

Zharilkassin Iskakov’s educational foundation is rooted in physics and mechanical engineering. He graduated with honors from the Faculty of Physics and Mathematics at The Korkyt Ata State University, Kyzylorda. He pursued postgraduate studies in the Department of Mechanics at Kazakh National University. In 1991, he was awarded the scientific degree of Candidate of Engineering Sciences by the Council of Kazakh National University. In 1995, he was conferred the title of Associate Professor of Engineering by the Supreme Certifying Commission. Most recently, in December 2023, he achieved the academic title of Full Professor in Mechanical Engineering, awarded by the Ministry of Science and Higher Education of Kazakhstan. His education has provided a strong theoretical and practical foundation, supporting decades of innovation in applied mechanics and engineering education across Kazakhstan.

Professional Experience 

Professor Zharilkassin Iskakov has extensive academic and research experience spanning over five decades. Beginning in 1974 as a lecturer in physics at Korkyt Ata State University, he later became Associate Professor and Head of the Physics Department. From 1988 to 2008, he also led the university’s education department. In 2008, he joined the University of Power Engineering and Telecommunications in Almaty, teaching physics and electrodynamics. Since 2012, he has held leading research positions at the Institute of Mechanics and Machine Science, including Head of Laboratories for Vibration Mechanisms and Nonlinear Dynamics of Gyroscopic Rotary Machines. His academic focus has consistently centered on physics, mechanics, and nonlinear systems. In parallel, he contributed to curriculum development and research leadership. His long-standing service in both research and academia reflects his deep commitment to scientific progress and the education of future engineers and scientists in Kazakhstan.

Awards and Honors

Prof. Zharilkassin Iskakov has received numerous honors recognizing his scientific and academic excellence. Twice awarded the prestigious State Grant and Title of Best University Lecturer, he has established himself as a leading figure in engineering education. In 2023, he was officially conferred the title of Full Professor in Mechanical Engineering by the Ministry of Science and Higher Education of Kazakhstan, a significant career milestone. His contributions have been consistently supported by competitive national research grants, including recent funding in 2023 for the project titled Resonant Oscillations of an Unbalanced Rotor with Nonlinear Characteristics. Other funded projects addressed nonlinear mechanical systems, physical practicum development, and vibration protection mechanisms. His ability to secure sustained research funding reflects national recognition of the practical impact and scientific relevance of his work. These accolades underscore his dedication to advancing engineering knowledge and highlight his long-term influence in shaping mechanical science research in Kazakhstan.

Research Focus

Professor Zharilkassin Iskakov’s research specializes in nonlinear dynamics, vibration mechanisms, and gyroscopic rotary machines. His work explores the behavior of mechanical systems under complex, real-world conditions, including systems with unbalanced rotors, non-ideal energy sources, and nonlinear characteristics. A key area of focus is the development of vibration protection systems and the theoretical modeling of nonlinear oscillations in engineering structures. He has led multiple government-funded research projects, contributing to advancements in machinery diagnostics and design optimization. His interdisciplinary approach integrates classical mechanics, electrodynamics, and applied physics to address industrial challenges. Beyond theoretical research, he also engages in developing practical tools for engineering education, including innovative training stands and laboratory equipment. His contributions have influenced both academic and industrial sectors in Kazakhstan, making his research not only theoretically robust but also practically relevant in engineering applications.

Notable Publication

Modeling of Dynamics of Nonideal Mixer at Oscillation and Aperiodic Damped Mode of Driving Member Motion

  • Authors: Kuatbay Bissembayev, Zharilkassin Iskakov, Assylbek Jomartov, Akmaral Kalybayeva
    Journal: Applied Sciences
    Year: 2025

Gyroscopic rotor dynamics simulation with anisotropy of elastic and damping characteristics of the support

  • Authors: Azizbek Abduraimov, Zharilkassin Iskakov, Aziz Kamal, Akmaral Kalybayeva
    Journal: Advances in Mechanical Engineering
    Year: 2024

Resonant vibrations of a non-ideal gyroscopic rotary system with nonlinear damping and nonlinear stiffness of the elastic support

  • Authors: Zharilkassin Iskakov, Nutpulla Jamalov
    Journal: MethodsX
    Year: 2023

Dynamic modeling of a non-ideal gyroscopic rotor system with nonlinear damping and nonlinear rigidity of an elastic support

  • Authors: Zharilkassin Iskakov, Nutpulla Jamalov, Kuatbay Bissembayeb, Aziz Kamal
    Journal: Advances in Mechanical Engineering
    Year: 2022

Resonance vibrations of a gyroscopic rotor with linear and nonlinear damping and nonlinear stiffness of the elastic support in interaction with a non-ideal energy source

  • Authors: Zharilkassin Iskakov
    Journal: Mechanical Systems and Signal Processing
    Year: 2022

Conclusion

Professor Zharilkassin Iskakov is a leading scholar in mechanical engineering, with a career marked by innovation, leadership, and academic excellence. His dedication to nonlinear mechanics and vibration research, combined with a strong teaching legacy, has significantly advanced engineering education and scientific knowledge in Kazakhstan. With multiple national honors and impactful research contributions, he remains a respected authority in his field. His lifetime of achievements makes him an exemplary figure in mechanical science and a role model for future researchers.