Nick Eleftheroglou – Predictive Analytics Award – Best Researcher 

Assist Prof Dr. Nick Eleftheroglou - Predictive Analytics Award - Best Researcher 

Delft University of Technology/ Faculty of Aerospace Engineering - Netherlands

Author Profile

Early Academic Pursuits

Assist Prof Dr. N. Eleftheroglou began their academic journey with a Diploma in Mechanical Engineering and Aeronautics from the University of Patras, where they graduated Cum Laude. This foundation laid the groundwork for their pursuit of higher education, leading to a Doctor of Philosophy degree, earned with distinction from the Faculty of Aerospace Engineering at Delft University of Technology. Their early academic pursuits reflect a strong commitment to engineering principles and aeronautical sciences, setting the stage for their groundbreaking research in the field of Sustainable AI for Diagnosis, Prognosis, and Health Management.

Professional Endeavors

Following their academic achievements, Assist Prof Dr. Eleftheroglou delved into various professional roles, including a stint as a Business Consultant at ORTEC and later as a Postdoctoral Researcher at Delft University of Technology. These experiences allowed them to bridge the gap between academia and industry, gaining practical insights into real-world applications of their research. Currently, as an Assistant Professor at Delft University of Technology, they continue to shape the future of engineering education and research.

Contributions and Research Focus On Predictive Analytics Award

Assist Prof Dr. Eleftheroglou's research is pioneering in the field of Sustainable AI for Diagnosis, Prognosis, and Health Management of structures and engineering systems. Their focus on developing novel physics-informed AI models highlights a dedication to advancing both the accuracy and environmental sustainability of AI applications. Their expertise spans machine learning models, stochastic processes, Bayesian statistics, and health/condition monitoring techniques, all aimed at improving the performance and longevity of critical engineering infrastructure.

Accolades and Recognition

The academic and professional community has recognized  Assist Prof Dr. Eleftheroglou's contributions through various awards and scholarships. Their excellence in research has been acknowledged with prestigious honors such as the Euro bank EFG Award and scholarships from the National Foundation for outstanding performance. Additionally, they have received research scholarships from TU Delft, underscoring their significant contributions to the field of prognostics and composite structures.

Impact and Influence

Assist Prof Dr. Eleftheroglou's impact extends beyond their research publications and academic achievements. Their involvement in organizations like ASME, the PHM Society, and CBM Academy showcases their commitment to advancing the field and fostering collaboration. Moreover, their invited seminars and presentations at renowned institutions and conferences globally highlight their influence in shaping discussions around AI for sustainability and structural health monitoring.

Legacy and Future Contributions

As Assist Prof Dr. Eleftheroglou continues to push the boundaries of Sustainable AI and prognosis for engineering systems, their legacy grows stronger. Their research not only contributes to the academic discourse but also has tangible implications for industries reliant on structural integrity and predictive maintenance. Looking ahead, their future contributions are poised to further revolutionize the intersection of AI, sustainability, and engineering, leaving an indelible mark on the field for generations to come.

Citations

  • Citations   445
  • h-index       9
  • i10-index    8

Notable Publication

Hamidreza Eskandari – Predictive Analytics – Best Researcher Award

Assist Prof Dr. Hamidreza Eskandari - Predictive Analytics - Best Researcher Award 

Swansea University - United Kingdom 

Author Profile

Early Academic Pursuits

Assist Prof Dr. Hamidreza Eskandari embarked on his academic journey with a strong foundation in engineering, earning a Bachelor of Science in Electrical Engineering from the University of Tehran in 1998. Building upon this, he pursued a Master of Science in Socio-Economic Systems Engineering from Iran University of Science and Technology in 2001, where his thesis focused on developing Multiple Attribute Decision Making Models under Uncertainty. His academic pursuit culminated in a Ph.D. in Industrial Engineering and Management Systems from the University of Central Florida in 2006, with a concentration in Systems Simulation. His dissertation titled "Multi-objective Simulation Optimization Using Evolutionary Algorithm Approaches" underscored his early commitment to research at the intersection of industrial engineering and computational methods.

Professional Endeavors

Assist Prof Dr. Eskandari's professional journey is characterized by a diverse range of roles and responsibilities across academia, industry, and consultancy. From serving as a Research Scientist in Artificial Intelligence at Red Lambda Inc. to founding and managing SimTek Company in Tehran, Iran, he demonstrated a versatile skill set and entrepreneurial spirit. His academic tenure at Tarbiat Modares University in Tehran, Iran, marked a significant period where he held positions as Assistant and Associate Professor, alongside directing the Advanced Simulation Lab. His contributions extended beyond the classroom, including consultancy for national organizations and private companies, as well as serving as a member of the Board of Directors for the Iran Logistics and Supply Chain Scientific Society.

Contributions and Research Focus On Predictive Analytics

Assist Prof Dr. Eskandari's research portfolio reflects his expertise in areas such as Explainable Machine Learning, Forecasting Energy Consumption and CO2E, Simulation Modeling and Analysis, Big Data Analytics & Data Science, Evolutionary Computation, and Logistics and Supply Chain. His publications, with notable appearances in prestigious journals and conferences, showcase the depth and breadth of his contributions to academia. Through his work, he has addressed complex problems in multi-objective optimization, decision making under uncertainty, supply chain management, and transportation systems, among others.

Accolades and Recognition

Assist Prof Dr. Eskandari's contributions have garnered significant recognition, as evidenced by his publication record and academic affiliations. With a Google Scholar H-Index of 20 and a Scopus H-Index of 17, he has established himself as a leading figure in his field. His research has been published in esteemed journals such as Energy, Applied Soft Computing, and Transportation Research Part A, reflecting the impact and relevance of his work in academia and industry.

Impact and Influence

Assist Prof Dr. Eskandari's research and teaching endeavors have made a substantial impact on the academic community and beyond. His work has influenced the development of methodologies and tools in areas such as simulation optimization, multi-criteria decision analysis, and machine learning. Through his teaching, mentoring, and professional engagements, he has inspired and guided numerous students and practitioners in the field of industrial engineering and management.

Legacy and Future Contributions

As Assist Prof Dr. Eskandari continues his academic journey, his legacy is characterized by a commitment to excellence, innovation, and societal impact. With ongoing research projects and collaborations, including prospective postdoctoral fellowships and grant-funded initiatives, he is poised to make further contributions to advancing knowledge and solving real-world challenges in his areas of expertise. His dedication to education, research, and service underscores his enduring commitment to shaping the future of industrial engineering and management systems.

Citations

  • Citations   1539
  • h-index       20
  • i10-index    28

Notable Publication