Hiyam Farhat | Digital twins | Best Researcher Award

Dr. Hiyam Farhat | Digital twins | Best Researcher Award

Lecturer | Tennessee Tech University | United States

Dr. Hiyam Farhat, a Lecturer and Assistant Director at the DOE Industrial Assessment Center in the Department of Mechanical and Nuclear Engineering at Tennessee Technological University, is a materials and mechanical engineering specialist whose work integrates advanced materials, manufacturing technologies, turbomachinery performance, and energy-efficiency research. She holds a PhD in Mechanical and Industrial Engineering, an MS in Mechanical and Materials Engineering, and a BS in Mechanical Engineering, underpinning a career that spans academic, research, and leadership roles across major engineering organizations. Her professional experience includes directing industrial assessment initiatives, managing engineering programs in the turbomachinery sector, contributing to quality and inspection systems, and teaching a broad range of engineering courses with demonstrated excellence. Her research focuses on AI-driven modeling, digital-twin development, materials degradation prediction, and clean-energy technologies, resulting in influential publications in areas such as hybrid digital-twin frameworks, gas turbine performance, flexible operation lifing criteria, and energy-storage applications. She has delivered invited presentations and contributed chapters to leading technical references, with her work supported by collaborations with national and international partners. Her recognitions include awards for technical presentations, and she maintains active engagement through memberships in professional societies such as ASME, KEEN, and the European Turbine Network. She also holds certifications in research ethics, nondestructive testing, welding inspection, quality auditing, and safety oversight. Dr. Farhat’s record reflects sustained innovation, cross-disciplinary expertise, and impactful contributions to advancing energy sustainability and intelligent engineering systems.

Profiles: Google Scholar | Scopus

Featured Publications

1. Farhat, H., & Salvini, C. (2022). Novel gas turbine challenges to support the clean energy transition. Energies, 15(15), 5474.

2. Farhat, H. (2021). Operation, maintenance, and repair of land-based gas turbines.

3. Farhat, H. (2021). Materials and coating technologies. In Operation, maintenance, and repair of land-based gas turbines (pp. 63–87).

4. Farhat, H., & Salvini, C. (2022). New lifing criterion for land-based gas turbines in flexible operation mode. Energy Reports, 8, 379–385.

5. Farhat, H. (2021). Lifetime extension: Assessment and considerations. In Operation, maintenance, and repair of land-based gas turbines (pp. 175–196).

Dr. Hiyam Farhat’s work advances intelligent energy systems by integrating AI-driven modeling, digital-twin technologies, and materials degradation analytics to enhance performance, reliability, and sustainability in turbomachinery and clean-energy applications. Her contributions support industry and national energy goals by improving efficiency, reducing emissions, and enabling data-informed lifecycle management for next-generation power systems.

Xiaoxu Liu | Engineering | Best Researcher Award

Dr. Xiaoxu Liu | Engineering | Best Researcher Award

Associate Professor at Shenzhen Technology University, China

Dr. Xiaoxu Liu is an accomplished Associate Professor at the Sino-German College of Intelligent Manufacturing, Shenzhen Technology University. He holds a Ph.D. in Electrical Engineering from the University of Northumbria and specializes in robust fault diagnosis, fault-tolerant control, stochastic systems, and multi-agent systems. Dr. Liu has published extensively in top-tier journals such as IEEE Transactions on Industrial Electronics and Automatica, and has served as Associate Editor for IEEE Transactions on Industrial Informatics. He has led multiple nationally funded research projects, securing over 3 million RMB in grants. His work integrates control theory with data-driven methods, addressing challenges in cyber-physical systems. Recognized as a Shenzhen Overseas High-level Talent, he has received numerous awards for research excellence and student mentorship. With international research experience and significant editorial contributions, Dr. Liu is a prominent figure in intelligent systems and control, demonstrating both academic leadership and impactful research contributions.

Professional Profile 

Scopus Profile

Education

Dr. Xiaoxu Liu possesses a strong and progressive academic background in engineering and applied mathematics. He earned his Ph.D. in Electrical Engineering from the University of Northumbria in the UK (2014–2018), where he specialized in fault-tolerant control systems and robust estimation. Prior to this, he completed a Master’s degree in Operations Research and Cybernetics at Northeastern University (2012–2014), and a Bachelor’s degree in Information and Computing Science at the same university (2008–2012). His educational path reflects a solid foundation in both theoretical and applied aspects of control systems, cybernetics, and intelligent systems. This combination of mathematical rigor and engineering application has laid the groundwork for his interdisciplinary research approach. His international academic journey has also helped him build a global perspective and a collaborative mindset, both of which have been instrumental in his subsequent professional and research achievements.

Professional Experience

Dr. Xiaoxu Liu has built an impressive academic and research career marked by rapid progression and leadership. Since December 2021, he has served as an Associate Professor at the Sino-German College of Intelligent Manufacturing, Shenzhen Technology University. Before that, he was an Assistant Professor at the same institution from 2018 to 2021. He also held research and teaching positions internationally, including as a Research Associate at the Faculty of Mathematics, City University of Hong Kong, and as a Lecturer at the University of Northumbria. Throughout these roles, Dr. Liu has led cutting-edge research projects, mentored students, and contributed to institutional development. He has acted as the principal investigator for numerous funded research programs, reflecting his capacity to lead independently and strategically. His experience demonstrates not only academic proficiency but also a sustained commitment to advancing intelligent systems research and fostering interdisciplinary collaboration in both teaching and applied engineering contexts.

Research Interest

Dr. Xiaoxu Liu’s research spans several high-impact areas within intelligent systems and control engineering. His primary interests include robust fault diagnosis, fault-tolerant control, stochastic nonlinear systems, and multi-agent systems. He also ocuses on cyber-physical systems and data-driven control, areas highly relevant to Industry 4.0 and autonomous system applications. Dr. Liu’s work often combines theoretical rigor with practical relevance, leveraging modern tools like deep reinforcement learning and Takagi-Sugeno fuzzy models to address real-world challenges such as actuator faults in UAVs or wind turbine resilience. His interdisciplinary approach blends classical control theory with artificial intelligence, enhancing system adaptability and reliability. His research outputs—published in top-tier journals like IEEE Transactions on Industrial Electronics—demonstrate not only novelty but also applicability to emerging technologies. Dr. Liu’s ability to connect robust theory with practical implementations positions him as a thought leader in intelligent manufacturing and autonomous system control.

ward and Honor

Dr. Xiaoxu Liu has received multiple awards that recognize his research excellence, academic leadership, and contributions to engineering education. He was honored as a Shenzhen Overseas High-level Talent in 2019, highlighting his strategic value to China’s academic and technological development. He has earned several Best Paper and Best Presentation Awards from prestigious conferences and journals, such as the IEEE Industrial Electronics Society and Processes. Dr. Liu also received the IEEE IES Student Paper Travel Award and various recognitions for his mentorship of student teams who achieved national-level prizes in robotics and circuit design competitions. These accolades underscore both the quality and impact of his scholarly work and his dedication to student development. His involvement as an Associate Editor for IEEE Transactions on Industrial Informatics and reviewer for top IEEE journals further validates his status as a trusted expert in his field. These honors collectively reflect his rising prominence in the global research community.

Conclusion

In summary, Dr. Xiaoxu Liu stands out as a highly capable and accomplished researcher in the field of intelligent control systems. With a solid educational foundation, diverse professional experience across top institutions, and a research portfolio that blends theoretical innovation with real-world application, he exemplifies academic excellence. His focus on robust fault diagnosis, resilient control systems, and data-driven approaches addresses some of the most pressing challenges in cyber-physical systems and smart manufacturing. Recognized nationally and internationally through numerous awards, editorial roles, and funded projects, Dr. Liu has established himself as a leader in his domain. He continues to advance the field through impactful publications, student mentorship, and collaborative projects. His trajectory reflects not only technical expertise but also a broader commitment to scientific progress and educational excellence. As such, Dr. Liu is highly deserving of recognition through accolades such as the Best Researcher Award.

Publications Top Notes

  • Title: Joint Observer Based Fault Tolerant Control for Discrete-Time Takagi-Sugeno Fuzzy Systems With Immeasurable Premise Variables

    • Authors: Xiaoxu Liu, Risheng Li, Zhiwei Gao, Bowen Li, Tan Zhang

    • Year: 2025

  • Title: Multiagent Formation Control and Dynamic Obstacle Avoidance Based on Deep Reinforcement Learning

    • Authors: Zike Yuan, Chenhao Yao, Xiaoxu Liu, Zhiwei Gao, Wenwei Zhang

    • Year: 2025

  • Title: Fault Estimation for Cyber–Physical Systems with Intermittent Measurement Transmissions via a Hybrid Observer Approach

    • Authors: Jingjing Yan, Chao Deng, Weiwei Che, Xiaoxu Liu

    • Year: 2024

    • Citations: 5

  • Title: Reinforcement Learning-Based Fault-Tolerant Control for Quadrotor UAVs Under Actuator Fault

    • Authors: Xiaoxu Liu, Zike Yuan, Zhiwei Gao, Wenwei Zhang

    • Year: 2024

    • Citations: 12

S Anita Shanthi | Fuzzy sets and systems | Best Researcher Award

Dr. S Anita Shanthi | Fuzzy sets and systems | Best Researcher Award

Associate Professor, Annamalai University, India

Dr. S Anita Shanthi, an Associate Professor at Annamalai University, India, has been honored with the prestigious Best Researcher Award for her pioneering work in the field of fuzzy sets and systems. 🏆 Her research contributions have significantly advanced our understanding of fuzzy logic and its applications, particularly in the realms of decision-making, pattern recognition, and artificial intelligence. Dr. Shanthi’s dedication to pushing the boundaries of knowledge and her commitment to excellence in research have garnered widespread recognition within the academic community. Her innovative approaches and insights continue to inspire and shape the future of fuzzy logic research. 🌟

Profile

Google Scholar

Educational Details 📚

Dr. S. Anita Shanthi pursued her Doctor of Philosophy in Mathematics at Annamalai University, Chidambaram, after completing her Master of Philosophy in Mathematics at Ramanujan Institute for Advanced Study in Mathematics, Madras University, Chennai. Her academic journey began with a Master of Science in Mathematics from Seethalakshmi Ramasamy College, Bharathidasan University, Thiruchirapalli.

Experience Details 💼

Dr. S. Anita Shanthi has been serving as an Associate Professor in Engineering Mathematics at Annamalai University, Tamilnadu, since January 2018. Prior to this, she held the position of Assistant Professor at the same institution for thirteen years, from January 2005 to 2018.

Research Interests 🔍

Dr. Shanthi’s research interests primarily focus on fuzzy mathematics, particularly in the areas of fuzzy normed linear spaces, intuitionistic fuzzy sets, fuzzy topology, and their applications in decision-making and pattern recognition.

Publications Top Notes  📝

“Interval valued fuzzy nnormed linear space” (2008)

“Some fixed point theorems in intuitionistic fuzzy n-normed linear spaces” (2009)

“On lacunary statistical convergence in intuitionistic fuzzy n-normed linear spaces” (2011)

“A decision making method based on similarity measure of interval valued intuitionistic fuzzy soft set of root type” (2015)

“A Study on Q-Level Subsemiring of (Q,L)- Fuzzy Subsemiring of a Semiring” (2015)