Stochastic Modeling and Closed-Loop Control Professors and Supervisors

Marc SalomonView profile

Professor

University of AmsterdamNetherlands

Marc Salomon is a Professor at the Faculty of Economics and Business, University of Amsterdam, where he is affiliated with the Amsterdam Business School. His office is located at Plantage Muidergracht 12, room M4.27, in Amsterdam. He can be reached via email at M.Salomon@uva.nl or by phone at +31 (0)20 525 4221. Professor Salomon's research spans several key areas in operations research and supply chain management. His primary interests include reverse logistics, remanufacturing, inventory control, production planning, and scheduling. He has made significant contributions to the understanding of closed-loop supply chains, particularly in the context of remanufacturing and disposal. His work also extends to transportation and railway operations, where he has developed decision support systems for network design and rolling stock allocation. His publication record over the past three decades demonstrates a consistent focus on optimization problems in logistics and operations. Early work centered on lotsizing and scheduling, while later research expanded into reverse logistics and remanufacturing. A notable trend is the application of operations research techniques to real-world problems, as evidenced by his award-winning paper in the EURO best applied paper competition in 1997. His recent work includes studies on resistance to change in professional contexts and joint route planning under market fluctuations. His scientific achievements have been recognized with the following award: EURO best applied paper competition 1997 Information about Professor Salomon's advising activities and research grants is not available in the provided text. Details about specific research labs or teams led by Professor Salomon were not provided in the available information.

Official University Profile

Moritz FleischmannView profile

Professor

University of MannheimGermany

Professor Moritz Fleischmann serves as Vice President for Sustainability and International Affairs at the University of Mannheim , while holding the Chair of Supply Chain Management in its Business School. With a background in Mathematics, Business, and Economics from Bayreuth, Bordeaux, and Ulm, he earned his PhD in General Management (2000) at Erasmus University Rotterdam, focusing on reverse logistics. Assistant Professor (Quantitative Methods), Erasmus University Rotterdam (until 2004) Associate Professor (Supply Chain Management), Erasmus University Rotterdam (2004–2009) Chair of Supply Chain Management, University of Mannheim (2009–present) Academic Director, ESSEC–Mannheim Modular Executive MBA Program (2011–2019) Interim Acting Dean (2019) and Vice Dean (2019–2020), Mannheim Business School His research spans reverse logistics , sustainable supply chains , inventory control , and dynamic pricing . A pioneer in closed-loop supply chain modeling, he has developed frameworks for recycling credit allocation, attended home delivery optimization, and vendor-managed inventory systems. His work bridges theoretical operations research with practical applications in plastics production, e-commerce, and agrochemical industries. From 2023 to 2024, he led institutional sustainability initiatives and international collaborations. His 15 most recent publications (2025–2020) focus on tackling contemporary challenges like circular economy strategies , crisis logistics , and AI-driven inventory optimization , reflecting his commitment to sustainability and innovation in supply chain operations.

Official University Profile

Enrico TronciView profile

Professor

Sapienza University of RomeItaly

Enrico Tronci is a Full Professor in the Department of Computer Science at Università degli Studi di Roma La Sapienza , Italy. His research focuses on model checking, formal verification, and synthesis of cyber-physical systems, with applications to mission-critical and safety-critical domains such as space systems, smart grids, and healthcare. He leads the Model Checking Lab (MCLab) and has coordinated numerous national and international research projects funded by organizations including the European Community (EC), European Space Agency (ESA), and Italian Ministry of University and Research (MUR). Research Highlights : Automatic control software synthesis from closed-loop specifications Model checking algorithms for hybrid and stochastic systems Technology transfer in sectors like energy, transportation, and aerospace Teaching : Undergraduate: Software Engineering (Fall 2024) Graduate: Automatic Verification of Intelligent Systems (Fall 2024), Verification and Validation of Intelligent Systems (Spring 2025) Scientific Awards : Recipient of the IBM-Italia 1987 prize for best thesis in Artificial Intelligence Publications Trends : 2024: Scaling up model checking for cyber-physical systems via HPC 2023: Hormonal impact on behavior and fault-tolerant sensor deployments 2021-2022: In silico clinical trials, smart grid management, and scenario enumeration 2020: AI-guided diabetes patient modeling and forensic psychiatry applications Software Tools : QKS (Quantized Kontrol Synthesizer) NashMV (MAD systems verification) CMurphi (Hybrid systems model checker) FHP-Murphi (Probabilistic verification) BSP (Boolean symbolic programming)

Official University Profile

Tobias Kasper Skovborg RitschelView profile

Assistant Professor

Max Planck Institute for Dynamics of Complex Technical SystemsGermany

Tobias Kasper Skovborg Ritschel serves as Assistant Professor (Tenure Track) in the Department of Applied Mathematics and Computer Science (DTU Compute) at the Technical University of Denmark. His research bridges theoretical advances in control systems with practical implementation across energy systems, bioreactors, epidemiology, and medical applications. Ritschel directs a productive research program focusing on computational methods for complex dynamical systems with rigorous thermodynamic foundations. His educational background demonstrates deep technical training: PhD in Applied Mathematics (2015-2018), Technical University of Denmark MSc in Mathematical Modeling and Computation (2013-2015), Technical University of Denmark BSc in Mathematics and Technology (2010-2013), Technical University of Denmark Ritschel's research expertise spans multiple domains of control theory and mathematical modeling. His core competencies include stochastic adaptive control, model predictive control, and optimal control frameworks applied to nonlinear dynamical systems. He specializes in numerical methods for differential equations (stochastic, partial, delay, and differential-algebraic) with computational implementations in MATLAB, C/C++, and Python. His application areas demonstrate remarkable breadth: from oil reservoir management and nuclear power systems to bioreactor operations, epidemiological modeling, and diabetes management technologies. Analysis of his publication trajectory reveals a strategic evolution from foundational work on thermodynamically rigorous reservoir simulation toward increasingly diverse applications. Early publications (2017-2019) focused on oil and gas applications with rigorous phase equilibrium modeling, while recent work (2020-2024) addresses pressing societal challenges including pandemic response strategies, power grid flexibility for renewable integration, and biomedical control systems. This demonstrates his ability to transfer core methodological expertise across disparate application domains while maintaining mathematical rigor. Dr. Ritschel actively supervises numerous students across all academic levels, with recent BSc projects focusing on molten salt reactors and demand-side flexibility in power systems. His teaching portfolio includes advanced graduate courses in stochastic adaptive control, dynamical systems, and time series analysis. He maintains strong industry connections through EU-funded projects including COCOP (Horizon 2020) and OPTION (Innovation Fund Denmark).

Official University Profile

Xu SunView profile

Research Fellow

UiT The Arctic University of NorwayNorway

Xu Sun is a Postdoctoral Fellow at the Department of Industrial Engineering, UiT The Arctic University of Norway, Campus Narvik. His research bridges logistics, sustainability, and digital innovation within Industry 4.0/5.0 frameworks, with a focus on practical applications in Norwegian contexts including electric vehicle infrastructure and pandemic response. His research portfolio spans Reverse Logistics, Sustainable Logistics, Closed-Loop Supply Chains, Digital Twins, and Industry 5.0 integration. Key themes include applying generative AI to logistics network design, optimizing charging infrastructure for electric trucks, and developing digital twins for circular economy systems. His work emphasizes multi-objective decision-making to balance environmental, social, and economic sustainability in logistics operations. Analysis of Xu Sun's publication trends reveals a strategic shift toward human-centric digital solutions in logistics. Recent works integrate generative AI, digital twins, and simulation to address Industry 5.0 challenges, with notable emphasis on electric mobility infrastructure (2024-2025) and pandemic-related logistics (2021-2022). His research consistently employs case studies from Norway, demonstrating practical applicability while advancing theoretical models for sustainable supply chains. No scientific awards were documented in the source material. While specific student advising details are absent from the profile, Xu Sun's collaborative publication record indicates active mentorship within research teams. His projects frequently involve multi-institutional partnerships and industry engagement, though explicit grant information is not provided in the available text. Xu Sun contributes to the ArcLog research group's Intelligent Manufacturing and Logistics team and leads the 'Industry 5.0 enabled Smart Logistics' project. His work leverages tools like AnyLogic simulation and digital twin technology to develop human-centered logistics solutions, with physical operations based in Campus Narvik office D2150.

Official University Profile

Shunichi OhmoriView profile

Professor

Waseda UniversityJapan

Shunichi Ohmori , a Professor at the Faculty of Science and Engineering , Waseda University , holds a Doctorate in Engineering from the same institution. His academic journey includes continuous affiliation with Waseda University since 2011, currently serving as a faculty member and concurrently as Director of Research Institute at the Institute of Global Production & Logistics (2022-2026). Education: Doctorate (2009-2012), Master's (2007-2009), and Bachelor's (2004-2007) from Waseda University His research focuses on industrial engineering and operations research , with specific interests in optimization , facility planning , logistics , and supply chain management . He has developed innovative frameworks for: Robust supply chain design under disruption risks Multi-echelon inventory optimization 3D facility layout planning with pipeline arrangements Collaborative vehicle routing cost allocation Green product portfolio strategies under uncertainty His publication record demonstrates expertise in stochastic optimization (15+ peer-reviewed papers) and heuristic algorithms (14+ conference proceedings). He has received multiple Best Paper Awards (2012-2016) and contributed to curriculum development through courses like Advanced Facilities Planning , Supply Chain Transformation , and Logistics at both undergraduate and graduate levels.

Official University Profile

Eren ÇilView profile

Professor

University of OregonUnited States

Eren Çil is a Professor of Operations and Business Analytics and the Robert J. and Leona M. DeArmond Research Scholar at the Lundquist College of Business, University of Oregon. He serves as Academic Director for the Oregon MBA Program and is affiliated with Undergraduate Programs. PhD in Operations Management, Northwestern University (2010) MS in Industrial Engineering, Koc University, Turkey (2006) His research focuses on service operations management, queuing theory, design and contract theory, and strategic pricing under competition. Recent work examines healthcare capacity allocation, product trial structuring, and closed-loop supply chain incentives. Publications appear in Management Science , Production and Operations Management , and Operations Research . Key trends across his 15 most recent articles include applications of queueing theory to healthcare and urban mobility systems, optimization of closed-loop supply chains for sustainability, and game-theoretic models for strategic pricing in competitive markets. Robert J. and Leona M. DeArmond Research Scholar Recognition for Top Research (2018) Çil advises graduate students in operations management and collaborates with research teams at the Lundquist College. His grant activities focus on sustainability incentives and service system optimization, with industry applications in healthcare, retail, and aerospace.

Official University Profile

Ioannis KonstantarasView profile

Associate Professor

University of MacedoniaGreece

Ioannis Konstantaras is an Associate Professor at the Department of Business Administration, University of Macedonia, Thessaloniki, Greece, holding this position since July 2016. He contributes to the Master in International Business, Master in Business Administration, and Master in Business Analytics and Data Science programs. His academic qualifications include: B.Sc. in Mathematics from Aristotelian University of Thessaloniki (1999) M.Sc. in Statistics & Operations Research from University of Ioannina (2001) Ph.D. in Operations Research from University of Ioannina (2006) Konstantaras specializes in mathematical modeling and optimization of inventory systems for supply and reverse logistics chains. His research addresses production planning, deteriorating items, imperfect quality products, and recovery processes through operations research methodologies. He develops analytical models for optimizing decision-making in complex logistics environments. His publication record (2010-2014) shows concentrated research on inventory models for deteriorating items, lot-sizing in recovery systems, and pricing strategies for reverse logistics. Key contributions include extensions to Economic Order Quantity models, optimization of two-warehouse systems, and integration of inspection learning effects in quality control. He serves as Co-Editor for the International Journal of Systems Science: Operations & Logistics since January 2014 and has reviewed for numerous international journals. Konstantaras led the research program "Logistics Management: Quantitative Methods for Inventory Management" funded by the ARCHIMEDES program under EPAYAEK II. No publicly available information lists his doctoral advisees.

Official University Profile

Robin SträsserView profile

Researcher

University of StuttgartGermany

Robin Strässer is a Research Associate at the Institute for Systems Theory and Control Engineering at the University of Stuttgart, where he has been working since October 2020. His research focuses on data-based control methods, particularly using the Koopman operator to derive closed-loop control guarantees for nonlinear systems based on measured data. He is also actively involved in developing an autonomous e-scooter project aimed at reducing the university's CO2 emissions and promoting sustainable urban mobility. His research interests span across data-driven control theory, nonlinear systems analysis, and autonomous vehicle systems. Strässer has made significant contributions to the application of Koopman operator theory in control systems, developing methods that provide stability guarantees for nonlinear systems. His work bridges theoretical control concepts with practical applications in sustainable transportation. He has also explored novel applications of control theory in unexpected domains, such as the analysis of cryptosystems using Koopman operator methods. Analysis of his publications reveals a strong focus on the Koopman operator framework for data-driven control, with particular emphasis on stability guarantees and error bounds. His work demonstrates a progression from theoretical foundations to practical implementations, especially in autonomous vehicle systems. The research shows increasing interdisciplinary connections, linking control theory with sustainable transportation, chemical engineering, and even cryptography. Among his notable achievements are the Best Paper Award at the European Robotics Forum (ERF2025) and the Best Poster Award at the International Conference on Data-Integrated Simulation Science (SimTech2023). Strässer has been actively involved in teaching, having organized and supervised practical courses in control engineering and taught courses on system dynamics fundamentals and data-driven control. He has also completed a research stay at EPFL's Data-Driven Modelling and Control Group, further expanding his expertise in data-driven control methods. His current work includes leading the autonomous e-scooter project at the University of Stuttgart, which serves as both a research platform for advanced control algorithms and a practical solution for sustainable campus transportation.

Official University Profile

Adnène HajjiView profile

Professor

Laval UniversityCanada

Adnène Hajji is a Full Professor at Université Laval's Faculty of Business Administration, specializing in Operations and Decision Systems. His academic journey includes a postdoctoral fellowship at Polytechnique Montréal, Ph.D. from École de technologie supérieure, and bachelor's degree from National Engineering School of Tunis. Research Focus: Professor Hajji's work bridges operations research and artificial intelligence, with core interests in: Production planning and control for unreliable systems Stochastic optimization in manufacturing/remanufacturing Hybrid AI models (deep learning + evolutionary algorithms) Sustainable operations and closed-loop supply chains Project scheduling under uncertainty His 50+ publications demonstrate consistent innovation in integrating predictive maintenance with production planning, developing optimization algorithms for engineer-to-order contexts, and applying data-driven approaches to healthcare and smart cities. Recent work shows strong emphasis on CNN-LSTM architectures and genetic algorithm hybrids. Student Supervision: Actively advises graduate researchers in industrial engineering and operations management, though specific student names aren't publicly listed.

Official University Profile