Prof. Abderrahmane Abbou | Operations Research | Best Researcher Award
Assistant Professor at University Mohammed VI Polytechnic, Morocco
Dr. Abderrahmane Abbou is an accomplished Assistant Professor at the Africa Business School, UM6P, Morocco, with a robust interdisciplinary background in operations research, industrial engineering, and decision sciences. Holding dual citizenship in Canada and Morocco, he brings international academic and industry exposure to his role. His academic trajectory includes a PhD and MEng from the University of Toronto, and a BEng from Concordia University. Dr. Abbou’s career is defined by a deep focus on sequential decision-making under uncertainty, integrating advanced mathematical modeling with practical applications in maintenance, inventory routing, and risk management. His expertise spans optimization, probability theory, and computational analytics, supporting both theoretical contributions and real-world problem solving. He has collaborated with renowned institutions and companies such as CIBC and WSP, reflecting his capacity to bridge academic rigor with industry demands. A frequent contributor to top-tier journals and conferences, Dr. Abbou also maintains a strong presence in teaching and mentoring, having taught at UM6P and the University of Toronto. Fluent in Arabic, English, and French, his multicultural fluency enhances his ability to engage with diverse scholarly and business communities. He stands out as a dedicated scholar, educator, and innovator in systems engineering and analytics.
Profile
Education
Dr. Abbou’s educational journey reflects a consistent pursuit of excellence in operations research and industrial systems. He earned his PhD in Operations Research from the University of Toronto (2015–2020), within the Department of Mechanical & Industrial Engineering. His doctoral thesis, titled Maintenance Optimization of Partially Observable Complex Systems, was supervised by Professor Viliam Makis and emphasized stochastic control models and real-time decision making. Prior to his doctoral studies, he completed a Master of Engineering (MEng) also at the University of Toronto in 2015, focusing on Multi-Echelon Spare Parts Inventory Control under the same supervisor. His foundational training came from Concordia University in Montreal, where he earned a Bachelor of Engineering (BEng) in Industrial Engineering with distinction (2008–2013). Across all these programs, Dr. Abbou demonstrated strong analytical and programming skills, mastery of mathematical modeling, and applied optimization in real-world scenarios. His academic path not only provided a solid theoretical grounding in engineering systems and statistical modeling, but also enabled the development of tools and techniques that have practical relevance in logistics, quality control, and infrastructure reliability.
Professional Experience
Dr. Abbou’s professional trajectory showcases a seamless integration of academia and industry research. He currently serves as an Assistant Professor at Africa Business School, UM6P, where he lectures on data analytics and operations management. His academic experience is complemented by rich research tenures, including a postdoctoral role at the University of Delaware (2021–2022), where he contributed to projects on earthquake risk management of critical infrastructure under Prof. Rachel Davidson. Previously, he was a research assistant at the University of Toronto (2015–2019), contributing to maintenance optimization projects with Prof. Viliam Makis. At Concordia University (2013–2014), he participated in preventive healthcare facility network design projects. In the industry, he has worked as a risk modeling researcher at CIBC (2020), focusing on capitalization of non-modellable risk factors. Additionally, he completed a MITACS internship at WSP (2018–2019), undertaking a reliability study for urban transit systems. His early career also includes a capstone project at Remco on warehouse operation optimization. This dual exposure to both academic rigor and real-world applications positions Dr. Abbou as a dynamic professional capable of addressing complex systems through a data-driven, analytical lens.
Research Interests
Dr. Abbou’s research interests revolve around the development of models and algorithms for dynamic decision-making under uncertainty. His core focus is on Dynamic Resource Allocation, particularly using methodologies such as restless bandits, index policies, and linear programming relaxation. These models find practical applications in inventory routing, multitasking environments, and maintenance planning. A significant branch of his research is Statistical Process Control, where he employs optimal stopping rules, Bayesian control charts, and the EM algorithm to address quality control and condition-based maintenance challenges, as well as cybersecurity applications like intrusion detection. Additionally, he explores Wiener Disorder Detection, using stochastic differential equations and first-passage time theory to design threshold-based policies for problems in quantitative finance and risk management. Across these domains, Dr. Abbou integrates theory and practice, leveraging advanced statistical inference and simulation to address real-world problems. His research is characterized by methodological rigor, relevance to contemporary industrial challenges, and a commitment to creating scalable and interpretable decision-support tools.
Research Skills
Dr. Abbou brings a comprehensive toolkit of research competencies in both mathematical modeling and computational analysis. His mathematical expertise includes optimization (e.g., mathematical programming, Markov decision processes), stochastic modeling (e.g., renewal theory, Poisson processes, Markov chains), and statistical methods (e.g., Bayesian analysis, MLE, simulation). These tools enable him to tackle problems involving uncertainty, system dynamics, and decision optimization. He is proficient in probabilistic inference, particularly with hidden Markov models and diffusion approximations—vital for applications in maintenance and quality control. On the computational side, Dr. Abbou is skilled in programming languages including C++, Python, and R, and has experience with platforms such as Arena, CPLEX, GAMS, Minitab, SQL, and VBA. His ability to synthesize mathematical formulations with algorithmic solutions and real-time data analysis makes him adept at building decision-support systems. These skills, combined with domain-specific knowledge in infrastructure systems and industrial operations, form the backbone of his applied research, allowing him to develop robust, scalable models for academia and industry.
Awards and Honors
Dr. Abbou’s academic excellence and research contributions have been recognized with several prestigious awards and scholarships. During his doctoral studies at the University of Toronto, he was awarded the Department of Mechanical & Industrial Engineering Fellowship from 2015 to 2019, acknowledging his outstanding academic performance and research output. He also received a MITACS Accelerate Award in 2018–2019, supporting his collaborative research with WSP on transit bus reliability. His early promise in academia was evident during his undergraduate years at Concordia University, where he was named to the Dean’s List for 2012–2013, a distinction reserved for top-performing students. These accolades reflect not only his scholarly capabilities but also his ability to translate theoretical research into practical, impactful solutions. Dr. Abbou’s recognition by both academic institutions and applied research bodies highlights the cross-disciplinary value of his work and positions him as a promising scholar-practitioner in the fields of operations research, analytics, and systems engineering.
Publications
Dr. Abbou has made significant contributions to top-tier academic journals and conferences. His recent journal publications include an article co-authored with Prof. Viliam Makis titled “Event-triggered Bayesian control chart,” published in Operations Research (2025), showcasing innovations in process monitoring. He also contributed to a multidisciplinary study on infrastructure resilience in Journal of Infrastructure Systems (2022). His earlier paper, “Group maintenance: A restless bandits approach,” was published in INFORMS Journal on Computing (2019), reflecting his early work on dynamic resource allocation. He is currently developing working papers on Bayesian multiprocess control and stochastic inventory routing, targeted to Management Science and Operations Research. His conference contributions span six IISE Annual Conferences, covering topics from real-time process control to maintenance scheduling. Additionally, he has presented at the CIBC Seminar Series on applications of Wiener switching disorders in finance. These publications and presentations underscore his active engagement in disseminating research that intersects analytics, engineering, and decision theory.
Conclusion
Dr. Abderrahmane Abbou exemplifies the modern scholar who integrates analytical depth, computational skill, and real-world engagement. His academic and professional journey, rooted in premier institutions such as the University of Toronto and Concordia University, has produced a versatile researcher and educator in operations research. Through his teaching at UM6P and earlier at the University of Toronto, he has influenced future engineers and analysts with a practical, data-informed approach. His research blends rigorous mathematical modeling with actionable insights in maintenance optimization, inventory routing, quality control, and infrastructure risk management. Industry collaborations with organizations like CIBC and WSP further attest to his ability to bridge theory and practice. Fluent in three languages and active across global academic and professional networks, Dr. Abbou brings a multicultural perspective to problem-solving and research. His trajectory suggests a commitment to impact, whether through advancing the boundaries of stochastic modeling or mentoring the next generation of engineering leaders. His profile stands as a model of academic excellence, professional integrity, and innovative thinking.