Find Academic Supervisors

• Model Predictive Control (MPC)
• Optimization Techniques
• Aerospace Engineering
• +3 more

Eric Kerrigan is a Professor of Control and Optimization at Imperial College London's Department of Electrical and Electronic Engineering, part of the Faculty of Engineering. He holds a joint appointment in the Department of Aeronautics. His research focuses on Model Predictive Control (MPC), numerical optimization techniques, and their applications in aerospace, renewable energy, and information systems. Key projects include developing real-time optimization algorithms for embedded systems, co-design frameworks for closed-loop systems, and drag reduction in aerodynamics. He has supervised over 30 PhD students and post-doctoral researchers, many of whom have secured academic positions. Education: PhD in Control Engineering from the University of Cambridge and BSc in Electrical Engineering from the University of Cape Town. Research interests emphasize robust control methods, dynamic optimization, and interdisciplinary applications. Notable contributions include the ICLOCS (Imperial College Optimal Control Software) toolbox and frameworks for energy-efficient UAV communication networks. His work is funded by EPSRC, the European Commission, and industry partners like Siemens and ESA. Funding and collaborations include grants from the Royal Academy of Engineering and Royal Society, with consulting roles in industrial control systems. Editorial roles include Associate Editor for IEEE Transactions on Automatic Control and former Senior Editor for IEEE Transactions on Control Systems Technology . Labs and affiliations include the Control and Power Research Group, Energy Futures Lab, and Space Lab at Imperial College.

Ming XiaoView profile

Associate Professor

• Wireless Communications
• Network Coding
• Machine Learning
• +10 more

Ming Xiao is an Associate Professor in the Division of Information Science and Engineering at KTH Royal Institute of Technology's School of Electrical Engineering and Computer Science (EECS). He is affiliated with the Digital Futures Faculty and leads research in wireless communications, machine learning, and network coding. His work focuses on 6G networks, distributed learning, and secure communications. Affiliations: KTH EECS, Digital Futures, Swedish Research Council, EU Horizon Europe projects Roles: Editor for IEEE Transactions on Wireless Communications, TPC Co-Chair for VTC Fall Research Interests: Dr. Xiao's expertise spans wireless communication systems (e.g., mmWave, NOMA), network coding, machine learning applications in communications, and energy-efficient distributed systems. He has pioneered work on intelligent reconfigurable surfaces (RIS), federated learning in edge computing, and integrated sensing-communications (ISAC). Projects: Ongoing EU-funded projects include ASCENT (autonomous vehicular networks) and COVER (unmanned aerial vehicles for emergency response). Past projects include 6G channel coding and intelligent energy management in smart communities. Grants: Over 12 active grants from VR, EU Horizon Europe, FORMAS, STINT, and VINNOVA Awards: IEEE Vehicular Technologies Society Best Paper Award (2023), World Top 2% Researcher (2020–2023), Highly Cited Researcher in Computer Science/Engineering. Labs/Teams: Leads the KTH Digital Futures initiative, collaborates with RISE Research Institutes, and manages a team of 12 PhD students/postdocs focusing on 6G, distributed ML, and secure IoT.

Theodore B. TrafalisView profile

Professor

• Machine Learning
• Optimization
• Supply Chains
• +6 more

Theodore B. Trafalis is a Professor in the Department of Industrial & Systems Engineering at the University of Oklahoma. He leads the Laboratory of Optimization and Intelligent Systems (LOIS), focusing on optimization, machine learning, and data-driven methods with applications in weather prediction, healthcare, manufacturing, and finance. Education: Ph.D., Industrial Engineering, Purdue University M.S., Industrial Engineering, Purdue University M.S., Mathematics, Purdue University B.S., Mathematics, University of Athens Research Interests: Uses optimization and machine learning to solve real-world challenges such as tornado prediction, supply chain resilience, and fair AI systems. Specializes in federated learning, robust algorithms, and imbalanced data problems. Active in developing mathematical frameworks for data assimilation in geophysical models and medical prognosis systems. Key Achievements: Recipient of OU Regents Award for Superior Research (2004) Editor-in-Chief, Journal of Intelligent Control and Automation Author of over 150 peer-reviewed articles spanning optimization theory, machine learning, and interdisciplinary applications Grants & Collaborations: NASA-funded projects on tornado prediction systems DOE grants for robust optimization in energy networks Industry partnerships with aerospace and manufacturing firms Labs & Teams: Directs the LOIS Lab, which collaborates with institutions globally on AI ethics, risk-aware control systems, and sustainable supply chains.

• Industrial Logistics
• Supply Chain Management
• Digitalization in Logistics
• +7 more

Fabio Sgarbossa is a Full Professor of Industrial Logistics at NTNU's Department of Mechanical and Industrial Engineering, Faculty of Engineering. He holds editorial roles in journals like the International Journal of Production Research and has authored over 150 publications. His research focuses on industrial logistics systems, supply chain resilience, and Industry 4.0 technologies, with a strong emphasis on human-centric design and digital transformation. Education: Master's in Management Engineering (2005) and PhD in Industrial Engineering (2010), both from the University of Padova, Italy. Research Interests: Design and management of industrial logistics; supply chain optimization; digitalization in manufacturing; human factors in production systems; autonomous mobile robots (AMRs); predictive maintenance; and circular economy integration. He leads NTNU's Logistics 4.0 Lab and collaborates on EU-funded projects. Key Contributions: Developed frameworks for Industry 4.0 adoption in logistics, decision support systems for additive manufacturing, and human-centric warehouse design. His work bridges operational efficiency with worker well-being. Grants & Collaborations: Active in EU and national projects focusing on smart manufacturing, resilient supply chains, and aging workforce challenges. Supervises graduate students in logistics systems and technology integration. Labs/Teams: Head of Logistics 4.0 Lab at NTNU, collaborating with industry partners on AMR implementations and digital twin applications.

Rosalba Garcia-MillanView profile

Lecturer

• Non-equilibrium physics
• Active matter
• Stochastic thermodynamics
• +3 more

Rosalba Garcia-Millan is a Lecturer in Disordered Systems at King’s College London, part of the Faculty of Natural, Mathematical & Engineering Sciences and the Department of Mathematics. She holds a PhD in Mathematical Physics from Imperial College London (2020). Prior to joining King’s in 2023, she was a postdoctoral researcher at the University of Cambridge and held an independent Research Fellowship at St John’s College, Cambridge. Her research focuses on non-equilibrium physics, active matter, and stochastic thermodynamics. She applies microscopic field theories to study active matter systems and agent-based models, with applications to biological physics, including DNA organization in cell nuclei, branching growth, and neuronal avalanches. Her work bridges theoretical approaches with interdisciplinary applications in biophysics and complex systems. Recent publications highlight contributions to entropy production in nonreciprocal systems, liquid-state theories for active matter, and chromatin dynamics. Her research emphasizes understanding collective behavior, nonequilibrium dynamics, and thermodynamic principles in both synthetic and biological systems. Rosalba is affiliated with the Disordered Systems group at King’s, known for its leadership in statistical mechanics of complex systems. No scientific awards are explicitly listed in the provided materials. She currently has no listed advisees or grants in the available data.

Masih FadakiView profile

Senior Lecturer

• Supply Chain Analytics
• Approximate Dynamic Programming
• Applied Operations Research
• +3 more

Dr. Masih Fadaki is a Senior Lecturer in the Accounting, Info Sys & Supply Chain Department at RMIT University's City Campus, Australia. He holds a Bachelor of Engineering (First-Class Honours), an MBA in Operations Management, and a PhD in Supply Chain Management. With nearly 20 years of industry experience in analytics, supply chain, and procurement roles, Dr. Fadaki has published in top-tier journals such as Decision Sciences and International Journal of Production Economics . His research focuses on Approximate Dynamic Programming, Supply Chain Analytics, and Stochastic Programming. He has received multiple teaching awards from RMIT and the University of Melbourne, as well as the School Research Award. Education: Bachelor of Engineering with First-Class Honours MBA in Operations Management PhD in Supply Chain Management Research Interests: Approximate Dynamic Programming Supply Chain Analytics Reinforced Learning Stochastic Programming Equitable Allocation Policies Disruption Risk Management Teaching Interests: Covers Supply Chain Management, Operations Research, Big Data Analytics, and Strategic Procurement. He supervises research on humanitarian supply chains, data breach behaviors, and stochastic optimization models. Awards: RMIT University Teaching Awards University of Melbourne Teaching Awards School Research Award Committee Involvement: Served on the School Research Committee at RMIT University since July 2021.

Suresh SethiView profile

Professor

• Supply Chain Management
• Stochastic Inventory Models
• Dynamic Advertising Models
• +4 more

Suresh Sethi is the Eugene McDermott Chair Professor of Operations Management and Director of the Center for Intelligent Supply Networks (C4iSN) at the Naveen Jindal School of Management, University of Texas at Dallas. He holds a PhD in Operations Research (Carnegie Mellon University, 1972) and has authored 11 books and over 400 research papers. His research spans supply chain management , stochastic inventory models , dynamic advertising models , and mathematical finance , with foundational contributions like the Sethi advertising model. Education: PhD (1972) and MS (1971) from Carnegie Mellon; MBA (1969) from Washington State; BTech (1967) from IIT Bombay. His work applies optimal control theory to business problems, including supply chain dynamics, financial engineering, and marketing. He pioneered doctoral programs in operations management at UT Dallas and the University of Toronto. Research Themes: Stochastic processes, game theory, dynamic optimization, and their applications in manufacturing, finance, and logistics. He has received numerous accolades, including Fellowships from the Royal Society of Canada (1994), IEEE (2002), INFORMS (2003), AAAS (2003), POMS (2005), and SIAM (2009). He served as POMS President (2012) and has editorial roles in journals like Production and Operations Management . The Production and Operations Management Society established the Suresh Sethi Best Interdisciplinary Paper Award in 2024. His recent publications focus on supply chain resilience , dynamic advertising , inventory optimization , and stochastic control , reflecting his interdisciplinary approach. Articles analyze game theory in supply chains, blockchain adoption , and epidemic logistics , often combining operations, finance, and marketing perspectives. He has supervised numerous doctoral students and postdoctoral fellows globally. His leadership includes founding the Center for Intelligent Supply Networks, which addresses regional supply chain challenges through faculty and student research.

• Supply Chain Management
• Logistics
• Operations Management
• +7 more

Henk Zijm is a full Professor in the Department of Industrial Engineering & Business Information Systems at the Faculty of Engineering Technology, University of Twente, and is affiliated with the Digital Society Institute. His research spans operations management, logistics, supply chain systems, and stochastic modeling, with a strong focus on practical industrial applications. His research interests include Supply Chain Management , Logistics , Inventory and Spare Parts Control , Multi-Agent Systems , and Digital Transformation in Manufacturing . He has made significant contributions to modeling complex systems under uncertainty, particularly in manufacturing and distribution networks. The 15 most recent articles reflect a consistent focus on supply chain resilience, digital coordination, and sustainable logistics. Key trends include the integration of additive manufacturing in spare parts supply, interactive tools for circular supply chains, and advanced modeling of traffic and production systems. His work bridges theoretical operations research with real-world industrial challenges. Henk Zijm has supervised 24 academic works, indicating active mentorship and PhD guidance. While no specific grants are listed, his extensive publication record and leadership in research areas suggest successful grant acquisition and project leadership. His work has strong interdisciplinary reach, particularly in digital society and systems engineering. He is associated with the Digital Society Institute at the University of Twente, which fosters interdisciplinary research on the societal impact of digital technologies. This affiliation underscores his engagement with broader technological and societal transformations.

• Control Engineering
• Biomedical Systems
• Iterative Learning Control
• +7 more

Dr.-Ing. Maike Stemmler is a researcher and group leader at the Institute of Automatic Control, RWTH Aachen University, where she heads the Biomedical Systems research group. She is currently on parental leave but remains an active contributor to control engineering research with a focus on biomedical applications. Her work bridges advanced control theory and medical technology development. Research Interests: Iterative Learning Control in medical systems Physiological modeling and control of cardiovascular dynamics Robot-assisted rehabilitation and human-robot interaction Deep learning and AI-based control strategies Biomedical cyber-physical systems Ventricular assist device (VAD) control algorithms Her recent publications (2018–2023) demonstrate a strong trend toward integrating machine learning and data-driven modeling with classical control theory, particularly in medical and automotive domains. She frequently applies iterative learning and model predictive control to complex physiological systems, aiming to improve patient outcomes through adaptive, intelligent devices. Her work in robot-assisted training highlights interdisciplinary collaboration between engineering and clinical sciences. Scientific Awards: No awards mentioned in the provided text. Advising and Grants: She completed her PhD in 2023 on iterative learning control in medical applications, indicating mentorship under Prof. Dirk Abel. She has advised or co-supervised junior researchers, as seen in collaborative publications with students and early-career authors (e.g., Xu Chen, Maximilian Basler). No specific grants are listed, but her research is likely supported by institutional and national funding given the scope and publication volume. Labs and Teams: Head of the Biomedical Systems research group at the Institute of Automatic Control, RWTH Aachen. Key collaborator in the IRT (Institute of Automatic Control) and IBF (Institute of Forming Technology) research groups, contributing to interdisciplinary projects involving robotics, AI, and medical devices.

Mohammadreza NematollahiView profile

Assistant Professor

• Sustainable Supply Chain Management
• Supply Chain Coordination Mechanisms
• Environmental and Social Sustainability
• +5 more

Mohammadreza Nematollahi is an Assistant Professor of Management Science at the Edwards School of Business, University of Saskatchewan, since 2023. His research focuses on sustainable supply chain operations, emphasizing coordination mechanisms that balance economic, environmental, and social sustainability goals. He holds a Ph.D. in Industrial Engineering from Iran University of Science and Technology (2017) and has held postdoctoral positions at the Gustavson School of Business (University of Victoria), CIRRELT, and the Dhillon School of Business (University of Lethbridge). Previously, he taught operations management at University Canada West's MBA program. His interdisciplinary research uses analytical modeling and data analytics to address real-world challenges in supply chain sustainability, including agribusiness, pharmaceuticals, and biomass energy. Key themes include supply chain coordination under uncertainty, reverse logistics, and stakeholder collaboration. He has published extensively on topics like dual-channel supply chains, cap-and-trade regulations, and quadruple bottom line frameworks. Teaching courses include Quality Management and Process Improvement (COMM 493.3) and Purchasing and Supply Management (COMM 491.3). His work bridges academic theory with practical applications, aiming to create win-win solutions for businesses and society.

• Machine Learning
• Neural Networks
• Neuromorphic Computing
• +3 more

Marcel van Gerven serves as Professor of Artificial Intelligence at Radboud University, leading the Artificial Cognitive Systems laboratory within the Donders Institute for Brain, Cognition and Behaviour. He holds dual Principal Investigator roles at both the Donders Centre for Cognition and the Donders Institute, while directing the ELLIS Unit Nijmegen as an ELLIS Fellow. His research program bridges artificial and natural intelligence through machine learning and neuromorphic computing, with core expertise in neural networks, brain-computer interfaces, and neuroprosthetics for vision restoration. Current work develops brain-inspired AI systems that enhance computational efficiency while modeling biological neural processes, particularly focusing on cortical stimulation safety and real-time adaptive systems. Analysis of his 2025 publications reveals dominant themes in reinforcement learning for neuroprosthetics, anomaly detection frameworks, and spiking neural network applications. His work consistently integrates medical applications including epilepsy regulation, immunotherapy diagnostics, and prosthetic vision enhancement, demonstrating strong translational impact from fundamental AI research to clinical solutions. Scientific recognition includes: Vidi laureate from the Dutch Research Council ELLIS Fellowship for European AI leadership Professor van Gerven directs significant research funding through national and international grants, including the Vidi award. His laboratory develops specialized frameworks like Abmax and Kozax for agent-based modeling while mentoring students in cognitive AI systems, though specific advisees aren't documented in available sources. The Artificial Cognitive Systems lab operates within the Donders Institute ecosystem, collaborating closely with the ELLIS Unit Nijmegen to advance European neuromorphic computing research. Current initiatives focus on biologically plausible learning rules, efficient neural network architectures for embedded systems, and closed-loop neuroprosthetic control systems.

Suresh P. SethiView profile

Professor

• Supply Chain Management
• Operations Research
• Mathematical Finance
• +3 more

Suresh P. Sethi is the Eugene McDermott Chair Professor of Operations Management and Director of the Center for Intelligent Supply Networks at The University of Texas at Dallas. He holds a Ph.D. in Industrial Administration from Carnegie Mellon University (1972) and has an extensive academic background including roles at the University of Toronto and numerous visiting professorships worldwide. His research focuses on supply chain management, inventory control, dynamic optimization, and mathematical finance. He has authored over 400 papers and 7 books, with notable contributions to operations research and management science. Dr. Sethi's honors include Fellowships from IEEE, INFORMS, AAAS, POMS, and SIAM, as well as the prestigious Royal Society of Canada Fellowship (1994). He has pioneered doctoral programs in operations management and serves on editorial boards of journals like Production and Operations Management and SIAM Journal on Control and Optimization. His research interests span supply chain dynamics, stochastic systems, and optimal control theory applications. Current projects include partially observed inventory models, hierarchical decision-making in manufacturing, and mathematical finance. Teaching focuses on optimal control and operations research. Education: Ph.D. in Industrial Administration, Carnegie Mellon University (1972) M.S.I.A., Carnegie Mellon University (1971) M.B.A., Washington State University (1969) B. Tech. in Mechanical Engineering, Indian Institute of Technology (1967) Professional activities include over 50 invited talks annually at global institutions, leadership roles in POMS, and advisory work for organizations like the IC² Institute. His interdisciplinary contributions bridge academia and industry, addressing real-world challenges in supply chain resilience and financial decision-making.

Mohamad T. ShahabView profile

Assistant Professor

• Control Theory
• Robotics
• Adaptive Control
• +4 more

Mohamad T. Shahab is an Assistant Professor in the Department of Electrical, Computer, and Biomedical Engineering at Toronto Metropolitan University (TMU), where he joined in 2025. His research focuses on control theory and autonomous systems, with particular expertise in adaptive control, robotics, and optimization. Dr. Shahab completed his PhD in Electrical and Computer Engineering at the University of Waterloo in 2020. He received his BSc in Control and Instrumentation Engineering (2007) and MSc in Systems Engineering (Automation and Control) (2015), both from King Fahd University of Petroleum and Minerals (KFUPM). Prior to joining TMU, he held postdoctoral appointments at KAUST working with Professor Eric Feron and worked as an R&D engineer with Baker Hughes. His research spans Control Theory, Robotics, Adaptive Control, Control & Optimization, and Autonomous Systems . Dr. Shahab's work particularly focuses on adaptive control strategies that yield linear-like behavior, robustness analysis of adaptive control systems, and applications to robotics and autonomous aerial vehicles. His recent work has centered on modular tetrahedral-shaped aerial robots and their control under uncertainty. Dr. Shahab has published numerous papers in top-tier journals including IEEE Transactions on Automatic Control, Automatica, and International Journal of Adaptive Control and Signal Processing, as well as in major conferences like IEEE ICRA and AIAA SciTech. His research shows a clear trajectory toward developing more robust and reliable adaptive control strategies for complex systems, particularly in robotics and autonomous vehicles. Dr. Shahab is actively recruiting graduate students (MASc, MEng, PhD) and undergraduate researchers interested in control theory, robotics, and autonomous systems. He encourages students with strong backgrounds in control, optimization, robotics, and machine learning to contact him.

Charles WangView profile

Associate Professor

• Supply Chain Management
• Operations Management
• Sustainable Transportation
• +4 more

Charles Wang is an Associate Professor in the Department of Operations Management and Strategy at the University at Buffalo's School of Management. He is affiliated with the Stephen Still Institute for Sustainable Transportation and Logistics, focusing on advancing sustainable supply chain practices and operational strategies. Dr. Wang holds a PhD and has extensive expertise in supply chain management, behavioral operations, and inventory optimization. His research explores topics including corporate diversification strategies, disruptive technologies in logistics, pricing power dynamics, and risk-averse decision-making in supply chains. He has contributed to understanding closed-loop supply chains, robust pricing models, and markdown strategies for perishable goods. Dr. Wang's work bridges theoretical frameworks (e.g., prospect theory, game theory) with practical applications in inventory control and supply chain coordination. His studies often emphasize sustainability, technological integration, and behavioral economics to address modern operational challenges. No scientific awards or grants are explicitly listed in the provided text. His advising and lab activities are centered at the Stephen Still Institute, though specific student names or lab details are not mentioned. His research trends reflect a focus on balancing efficiency, sustainability, and strategic decision-making in complex supply networks.

Jack UmenbergerView profile

Research Fellow

• Control Theory
• Optimization
• Machine Learning
• +3 more

Jack Umenberger is a Senior Research Fellow at the University of Oxford’s Department of Engineering Science and the ZERO Institute for zero-carbon energy research. He joined Oxford in 2023 as a Departmental Lecturer within the Control Group. Previously, he held postdoctoral positions at MIT (2019-2022) and Uppsala University, Sweden (2017-2019), and earned his PhD from the University of Sydney in 2018 for work on data-driven modeling of dynamical systems. His research focuses on the intersection of control theory, optimization, and machine learning, with applications to energy systems (e.g., battery management with Eatron Technologies) and robotics (e.g., motion planning with Dexai Robotics). Key areas of interest include data-driven system identification, model predictive control, reinforcement learning, and stability guarantees in dynamical systems. Notable projects include work on shortest paths in graphs of convex sets for robotic motion planning, convergence analysis of direct policy search in reinforcement learning, and system identification with stability guarantees. His contributions emphasize blending discrete and continuous decision-making frameworks in optimization and control problems. Umenberger collaborates with industry partners like Eatron Technologies and Dexai Robotics, advancing applications in energy and robotics. His work often bridges theoretical advancements with practical implementations, reflecting a commitment to impactful engineering solutions.