Mr. Alireza Ahmadi | Lean Manufacturing | Excellence in Research

Mr. Alireza Ahmadi | Lean Manufacturing | Excellence in Research

Politecnico di Milano/Universidad Politecnica da Madrid, Italy

Author Profile

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🎓 Early Academic Pursuits

From his earliest studies in reservoir engineering at Petroleum University of Technology Ahwaz, Alireza Ahmadi demonstrated a passion for understanding complex systems and optimizing resource use. Immersed in fluid dynamics and subsurface modeling, he built a foundation that would later evolve into a broader fascination with organizational and operational systems. His subsequent MSc in Reservoir Engineering at Islamic Azad University – Science and Research Branch (2016) deepened his technical expertise, while a parallel Master of Specialization in Project Engineering from Tose’e Higher Education Institute honed his ability to translate technical insights into actionable project plans. This blend of rigorous engineering training and project management perspectives paved the way for his MBA in Innovation Management from École des Ponts ParisTech in 2020, equipping him with strategic frameworks for fostering creativity and leading change. Today, as he pursues a dual PhD in Management Engineering and Organizational Management at Politecnico di Milano and Universidad Politécnica de Madrid, his academic trajectory reflects a seamless evolution from mastering technical subsurface problems to interrogating the structures, processes, and human dynamics that drive organizations forward. His early academic journey, marked by curiosity, interdisciplinary study, and a steady build-up of analytical rigor, laid the groundwork for his transformative approach to both engineering and management challenges.

💼 Professional Endeavors

Over more than 15 years, Alireza’s professional path has woven through varied industries and roles, each contributing to his multidisciplinary acumen. Beginning as a Retail Sales Specialist, he cultivated interpersonal skills and an appreciation for customer-centric thinking. Transitioning into program management with the Iranian Ministry of Oil, he oversaw monitoring and control of mega-projects, developing early expertise in large-scale coordination and stakeholder engagement. As Senior Project Control Manager for a €400M EPC gas condensate refinery project at Kasra Refinery, he managed intricate budgets, negotiated with international partners, and led cross-functional teams, sharpening his capacity for strategic oversight under pressure. Shifting to consultancy roles in Tehran and Paris, he performed economic and technical analyses for energy market ventures and designed geothermal drilling solutions, blending technical proficiency with market insight. His tenure as International Business Development Manager at SOCOTEC Monitoring and ESTD expanded his skillset into strategic expansion and revenue planning in diverse markets. At Politecnico di Milano, he now channels this rich background into research fellow responsibilities and PhD work, optimizing business processes, applying lean methodologies in academic-industry collaborations, and mentoring students. Each professional chapter reflects his ability to adapt, lead multicultural teams, and drive operational excellence, forging a profile that bridges engineering detail, strategic thinking, and innovation leadership.

🔬 Contributions and Research Focus

Alireza’s research interests lie at the nexus of operational excellence, lean systems, and data-driven decision-making within Industry 4.0 contexts. He has contributed to studies on workload control and human-machine interfaces, exploring how organizations harness technology to enhance productivity and adaptability. His dual PhD work examines how management engineering principles can optimize processes in uncertain markets, integrating advanced analytics and digital transformation strategies. In academic-industry projects, he has deployed lean methodologies to streamline workflows, reduce inefficiencies, and foster continuous improvement. Through publications on workload control and Industry 4.0 interfaces, he offers actionable insights into balancing automation with human factors, ensuring that technological advances drive not only efficiency but also employee engagement and organizational resilience. By leveraging his engineering roots, he approaches management challenges with a systems-thinking lens, modeling processes akin to complex engineering systems and applying data analytics to reveal hidden patterns and opportunities. His multidisciplinary background allows him to frame research questions that intersect technical feasibility, economic viability, and human considerations, positioning his contributions at the forefront of operational innovation in modern enterprises.

🏅 Accolades and Recognition

Throughout his journey, Alireza’s dedication to excellence and innovation has garnered respect among peers and mentors. His acceptance into dual PhD programs at leading European institutions attests to his academic rigor and the relevance of his research proposals. Achieving an MBA from a prestigious French school and excelling in earlier engineering degrees signal consistent high performance. In professional spheres, being entrusted with multimillion-euro project controls and spearheading international business development initiatives reflect recognition of his leadership and strategic acumen. Within academic and industry networks—such as the Project Management Institute and the Society of Petroleum Engineers—he has contributed ideas, participated in competitions, and shared best practices, building his reputation as a thought contributor. Although formal awards or honors may not all be publicly listed, the trajectory of roles entrusted to him, combined with published research outputs and mentorship roles, underscores a career marked by achievement and peer acknowledgment.

🌍 Impact and Influence

Alireza’s work has influenced both technical projects and organizational practices. By applying lean and data-driven frameworks to academic-industry collaborations, he has helped teams achieve measurable performance improvements, demonstrating how principles rooted in manufacturing and engineering can translate to broader contexts. His analyses of market entry strategies and feasibility studies for energy ventures have shaped decision-making in corporate settings, underscoring his capacity to bridge technical detail with strategic forecasting. In mentoring students at Politecnico di Milano, he passes on applied consulting insights, influencing the next generation of problem solvers. His multicultural experiences—navigating projects in Iran, France, and Italy—enhance his ability to foster inclusive collaboration, encouraging diverse perspectives in tackling complex challenges. Through publications on human-machine interfaces in Industry 4.0, he informs practitioners and researchers on designing systems that harmonize automation with human roles, potentially impacting technology adoption and workforce development approaches in multiple sectors.

🔮 Legacy and Future Contributions

Looking ahead, Alireza Ahmadi is poised to leave a lasting mark on how organizations harness engineering-inspired methodologies and digital tools for sustainable growth. His legacy will be defined by integrating rigorous analytical models with human-centric process design, guiding companies through transformation in uncertain markets. As he completes his dual PhD, the frameworks and case studies he develops may serve as blueprints for operational excellence in diverse industries. His future contributions are likely to include collaborative research projects that bring together academia and industry, leveraging data analytics, lean thinking, and emerging technologies such as AI and IoT to enhance decision-making. By continuing to mentor and share knowledge, he will multiply his impact, empowering teams worldwide to adopt resilient, efficient practices. With a foundation built on interdisciplinary learning and a track record of driving real-world improvements, Alireza’s evolving work promises to influence both theory and practice, cementing his role as a visionary in management engineering and organizational innovation.

📝Notable Publications

The impact of labor flexibility on operational efficiency in industry 5.0: a systematic literature review

Authors: Alireza Ahmadi, Alessandra Cantinia, Víctor Gómez Frías, Alberto Portioli Staudacher
Journal: International Journal of Production Research
Year: 2025

A Bibliometric Perspective of Integrating Labor Flexibility in Workload Control

Authors: Alireza Ahmadi, Alessandra Cantini, Alberto Portioli Staudacher
Book/Series: In Advances in Production Management Systems (IFIP Advances in Information and Communication Technology, vol. 730)
Year: 2024

 Applying a process-centric approach to the digitalization of operations in manufacturing companies: a case study

Authors: Matteo Rossini, Alireza Ahmadi, Alberto Portioli Staudacher
Journal/Proceedings: Procedia Computer Science
Year: 2024

Enhancing Labor Flexibility in Workload Control: The Development and Application of a Framework

Authors: Alireza Ahmadi, Alessandra Cantini, Federica Costa, Alberto Portioli Staudacher
Book/Series: In Advances in Production Management Systems (IFIP Advances in Information and Communication Technology, vol. 730)
Year: 2024

 Integration of Lean Supply Chain and Industry 4.0

Authors: Matteo Rossini, Alireza Ahmadi, Alberto Portioli Staudacher
Journal/Proceedings: Procedia Computer Science
Year: 2024

Dr. Hai Xue | Edge computing | Best Researcher Award

Dr. Hai Xue | Edge computing | Best Researcher Award

University of Shanghai for Science and Technology,

Profile

Google Scholar

🎓 Early Academic Pursuits

Dr. Hai Xue embarked on his academic journey in the field of computer engineering with a Bachelor of Science in Information and Communication Engineering from Konkuk University, Seoul, South Korea, in 2014. Driven by an insatiable curiosity for software and computing, he pursued his Master’s degree at Hanyang University, Seoul, where he specialized in Computer and Software under the guidance of Prof. Inwhee Joe. This period was crucial in shaping his foundational knowledge and research skills, which later fueled his contributions to edge computing and network science. Dr. Xue culminated his formal education with a Ph.D. in Computer Engineering from Sungkyunkwan University, Suwon, in 2020, where he worked under the mentorship of Prof. Hee Yong Youn. His doctoral research laid the groundwork for his future breakthroughs in dynamic resource allocation and federated learning.

🌟 Professional Endeavors

Dr. Xue’s professional career is marked by a series of prestigious positions that reflect his growing influence in the field of computer engineering. After earning his Ph.D., he served as a Research Professor at Korea University, Seoul, from September 2020 to September 2021. During this tenure, he collaborated with renowned researcher Prof. Sangheon Pack, contributing significantly to the domains of edge computing and network optimization. In September 2021, he transitioned to his current role as an Assistant Professor at the University of Shanghai for Science and Technology (USST), Shanghai, China. Here, he continues to engage in high-impact research, mentoring young scholars, and advancing cutting-edge technological solutions.

🔮 Contributions and Research Focus

Dr. Xue’s research interests are deeply rooted in dynamic resource allocation, federated learning, and edge computing. His contributions have led to substantial advancements in these areas, including:

  • Dynamic Pricing in Edge Offloading: His recent work on dynamic pricing-based near-optimal resource allocation is set to redefine how computational resources are distributed efficiently across networks.
  • Energy Harvesting in Edge Computing: His paper on dynamic differential pricing-based edge offloading systems with energy harvesting devices has been accepted by IEEE Transactions on Network Science and Engineering, highlighting his expertise in sustainable and energy-efficient computing.
  • Federated Learning Incentive Mechanisms: His study on Yardstick-Stackelberg pricing-based incentive mechanisms for federated learning in edge computing, accepted by Computer Networks, sheds light on optimizing collaborative learning models.
  • Neural Network Optimization: His work on dynamic pseudo-mean mixed-precision quantization (DPQ) for pruned neural networks, published in Machine Learning, underscores his ability to push the boundaries of artificial intelligence efficiency.

🏆 Accolades and Recognition

Dr. Xue’s contributions have not gone unnoticed. His publications in high-impact journals such as IEEE Transactions, Computer Networks, and Machine Learning underscore his academic excellence. His research has been classified under prestigious rankings, including CAS Q2 and JCR Q1, affirming its significance within the scientific community. These accolades reflect his unwavering commitment to innovation and the quality of his scholarly output.

🌐 Impact and Influence

Dr. Xue’s research has far-reaching implications in both academia and industry. His work in dynamic pricing mechanisms is influencing how network providers optimize their resource allocation, while his advancements in federated learning are paving the way for more secure and efficient decentralized AI applications. His insights into energy harvesting in edge computing hold promise for sustainable technological solutions, a pressing need in today’s energy-conscious world.

🌟 Legacy and Future Contributions

Looking ahead, Dr. Xue is poised to make even more significant contributions to computer engineering. His ongoing projects aim to refine the synergy between AI and edge computing, ensuring smarter, more adaptive network solutions. As an educator, he remains dedicated to nurturing the next generation of computing professionals, equipping them with the knowledge and skills necessary to tackle future challenges in technology.

📝Notable Publications

Dynamic load balancing of software-defined networking based on genetic-ant colony optimization

Author(s): H. Xue, K.T. Kim, H.Y. Youn
Journal: Sensors
Year: 2019

 Detection of falls with smartphone using machine learning technique

Author(s): X. Chen, H. Xue, M. Kim, C. Wang, H.Y. Youn
Journal: 2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)
Year: 2019

Packet Scheduling for Multiple‐Switch Software‐Defined Networking in Edge Computing Environment

Author(s): H. Xue, K.T. Kim, H.Y. Youn
Journal: Wireless Communications and Mobile Computing
Year: 2018

 Dynamic pricing based near-optimal resource allocation for elastic edge offloading

Author(s): Y. Xia, H. Xue, D. Zhang, S. Mumtaz, X. Xu, J.J.P.C. Rodrigues
Journal: arXiv preprint arXiv:2409.18977
Year: 2024

DPQ: dynamic pseudo-mean mixed-precision quantization for pruned neural network

Author(s): S. Pei, J. Wang, B. Zhang, W. Qin, H. Xue, X. Ye, M. Chen
Journal: Machine Learning
Year: 2024