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