Shahin Gelareh — Co-Founder
I am a mathematician, operations researcher, and data scientist working at the intersection of optimization, artificial intelligence, and data-driven decision-making, with a strong focus on translating rigorous theory into deployable solutions for complex real-world systems. My expertise spans combinatorial optimization, logistics, scheduling, and supply chain analytics, with applications in transportation networks, resource management, and sustainable operations. My work aligns with emerging trends in hybrid AI–OR systems, prescriptive analytics, and digital twins, combining optimization models, machine learning, and simulation to support robust and explainable decision intelligence. I have contributed to research and consultancy projects in container terminal operations, liner shipping network design, traffic and mobility management, hospital and urban logistics, and workforce scheduling, often through the development of decision-support systems evaluated via discrete-event, multi-agent, and system dynamics simulations. Technologically, I leverage Python, C++, Java, SQL, and industrial-grade solvers such as CPLEX and Gurobi, alongside IoT-enabled data pipelines and digital-twin frameworks to analyze operational performance, resilience, and carbon-aware strategies. In parallel, my pedagogical approach reflects contemporary trends in active and experiential learning, emphasizing project-based instruction, flipped classrooms, and data-driven experimentation using tools such as Jupyter Notebooks and simulation platforms, with the objective of developing analytical rigor, interdisciplinary thinking, and practical problem-solving skills. Across research, teaching, and consultancy, my overarching goal is to advance sustainable, efficient, and evidence-based decision-making while fostering strong links between academic innovation and industrial impact.
Stackforce AI infers this person is a Data Science and Operations Research expert with a focus on optimization in logistics and supply chain.
Location: Lille, Hauts-de-France, France
Experience: 25 yrs 1 mo
Skills
- Operations Research
- Mathematics
- Data Science
- Optimization
- Consultancy
- Software Development
Career Highlights
- Expert in optimization and data-driven decision-making.
- Strong background in operations research and machine learning.
- Experience in developing predictive maintenance solutions.
Work Experience
IÉSEG School of Management
Adjunct Professor (6 mos)
Chinese Academy of Sciences
Visiting Fellow (4 mos)
Paris School of Business
Programme Director for Master/MSc in Data Management (9 mos)
Sharkey Predictim Globe
Co-Founder (1 yr 8 mos)
خلوت
آن کار دیگر (6 yrs 3 mos)
ITBA - Information Technology and Business Analytics
Co-Founder (1 yr 2 mos)
University of Portsmouth
Visiting Assocoate Professor in Operations Research and Business Analytics (11 mos)
Polytech Lille
Researcher (1 yr 2 mos)
Technical University of Denmark
Postdoctoral Researcher (1 yr 6 mos)
Independent
Consultant in data, decision and IT projects (9 yrs 5 mos)
National University of Singapore
Research Fellow (1 yr 6 mos)
Fraunhofer ITWM
PhD student (3 yrs)
Self-employed
Freelance Developer and Business Analyst (4 yrs 8 mos)
University of Sistan and Baluchestan
Master student (2 yrs)
SouthCoastNet Ltd
Managing Director (2 yrs 1 mo)
Self-employed
System and Network Administrator (1 yr 4 mos)
Education
Habilitation a Diriger des Recherches at Universite de Lorraine
PhD at Technische Universität Kaiserslautern, Germany
M.Sc at University of Sistan and Baluchestan
Bachelor of Science at Ferdowsi University of Mashhad
