جستجوی استاد راهنمای دانشگاهی

• Mathematical Optimization
• Decomposition Methods
• Machine Learning
• +۳ مورد دیگر

Emiliano Traversi is an Associate Professor in the Department of Information Systems, Data Analytics and Operations at ESSEC Business School. He holds a PhD in Operations Research from the University of Bologna and previously served as a Full Professor at LIRMM, University of Montpellier. His research focuses on mathematical optimization, decomposition methods, and machine learning, with recent emphasis on network slicing in UAV-based 5G systems and multi-drone formation strategies. His work bridges theoretical optimization frameworks with practical applications in telecommunications and autonomous systems. Education: PhD in Operations Research, University of Bologna Habilitation à diriger des recherches, Business Administration, Sorbonne Université (2023) Research Interests: Mathematical Optimization (Convex/Non-Convex) Decomposition Algorithms (e.g., Benders, Dantzig-Wolfe) Network Slicing & Resource Allocation for 5G/6G Autonomous Systems & Multi-Agent Coordination Applications in Telecommunications and Transportation Recent Research Trends: His 2025 publications highlight advancements in UAV-enabled 5G network slicing frameworks (EASIER) and mathematical foundations for drone fleet formations. Earlier work extends to optimization methods for transportation systems, quantum computing challenges, and power grid management through semidefinite relaxations. Professional Contributions: 20+ peer-reviewed articles in top journals/conferences (e.g., Computer Networks, AICA) Development of optimization frameworks with real-world applications Labs/Teams: Active collaborations in ESSEC's data analytics initiatives and international projects on UAV communication systems.

• Quantitative Management
• Logistics
• Regional Science

Daniel Serra is a Full Professor at Pompeu Fabra University, specializing in Quantitative Management, Logistics, and Regional Science. His work focuses on optimizing facility location, emergency service planning, and competitive market strategies. He holds a PhD from Johns Hopkins University. His research explores applications of operations research to real-world problems, such as prioritizing emergency services, analyzing consumer preferences via TURF models, and modeling spatial economic impacts. Notable contributions include studies on sub-national purchasing power parity, aerosol exposure effects, and hierarchical facility districting. Recent publications highlight advancements in facility location theory, queuing systems, and environmental health impacts. His work bridges theoretical models with practical applications in logistics, public health, and regional economics.

Burak Galip Aslanمشاهده پروفایل

مدرس

• Decision-support systems
• Expert systems
• Forecasting
• +۷ مورد دیگر

Burak Galip Aslan is a Lecturer in the Computer Engineering Department at Izmir Institute of Technology (IZTECH). He has been affiliated with the institution since 2000. His academic journey includes a B.Sc. in Electrical and Electronics Engineering from Dokuz Eylul University (2000), an M.Sc. in Computer Software from IZTECH (2003), and a Ph.D. in Computer Engineering from Ege University (2010). Education: B.Sc. Electrical and Electronics Engineering, Dokuz Eylul University (2000) M.Sc. Computer Software, Izmir Institute of Technology (2003) Ph.D. Computer Engineering, Ege University (2010) Research Interests: His work focuses on educational technology, adaptive learning systems, and computational methods in education. Key areas include decision-support systems, Bayesian modeling for academic achievement, cloud-based e-learning architectures, and learning style analysis through behavioral data. He also explores hands-on educational approaches in computer hardware instruction for secondary students. Courses Taught: Core courses include Logic Design (CENG 214), Microprocessors (CENG 384), Probability and Statistics (CENG 222), Professional Ethics in Computer Engineering (CENG 411), and Research Methodology (CENG 518). His teaching integrates laboratory work involving digital circuits, microcontroller programming, and ethical considerations in technology. Publications: His research highlights include studies on Bayesian techniques in language education, cloud deployment for e-learning systems, and learning style validation frameworks. Recent work emphasizes practical educational tools like hardware teaching modules for high school students. Laboratory Contributions: Develops hands-on experiments in digital systems design, including BCD-to-7-segment displays, combinational circuits, and microcontroller-based projects. These labs emphasize troubleshooting, ADC interfacing, and embedded systems development.

Patrick MARCELمشاهده پروفایل

استاد

• Databases
• Exploratory Data Analysis
• OLAP
• +۴ مورد دیگر

Patrick MARCEL is a Full Professor at the Department of Computer Science, University of Orléans, and a member of the LIFO laboratory. He holds a PhD from INSA Lyon (1998) and a Habilitation à Diriger les Recherches from Université de Tours (2012). His research focuses on databases, exploratory data analysis, OLAP, data mining, and recommendation systems. He serves as an associate editor for the DKE journal and leads the Steering Committee of the DOLAP workshop, co-chairing in 2017 and 2021. Education: PhD in Computer Science, INSA Lyon, 1998 Habilitation à Diriger les Recherches, Université de Tours, 2012 Research Interests: Exploratory Data Analysis & OLAP Data Mining and Machine Learning Personalization and Recommendation Systems Context-Aware Data Quality Management Emotional Data Interaction His work emphasizes intention-driven analytics, cube query optimization, and narrative generation in business intelligence. Publications: Over 80 articles spanning OLAP systems, data quality, and recommendation techniques, with recent emphasis on emotional intelligence in query design and matheuristics for optimization problems. His 2024 work explores intentional aspects in data narratives and context-aware methodologies. Awards: None explicitly listed. However, his editorial roles and workshop leadership highlight peer recognition. Advising & Grants: No student names listed, but active in mentoring through research projects. His work is supported by collaborations with industry and academic partners. Labs & Teams: Member of the LIFO lab (Laboratoire d’Informatique Fondamentale d’Orléans), team Pamda. Engaged in interdisciplinary research on data platforms and analytical processing.

Shahin Gelarehمشاهده پروفایل

دانشیار

• Operations Research
• Logistics and Supply Chain Management
• Transportation Planning
• +۹ مورد دیگر

Shahin Gelareh is an Associate Professor in Operations Research and Logistics at the Université d'Artois, France, affiliated with the Department of Networks and Telecommunications at the IUT de Béthune. He holds a PhD in Optimization from the Technical University of Kaiserslautern (2008), an MSc in Applied Mathematics from the University of Sistan and Baluchestan (2005), and a BSc from Ferdowsi University of Mashhad (2003). His research focuses on Locational Analysis , Integer Programming , Metaheuristics , Global Network Design , and applications in Maritime Transport , Supply Chain , and Telecommunications . Notable areas include hub-and-spoke network optimization, liner shipping fleet deployment, and competitive analysis using game theory. Recent publications emphasize innovations in Neural Benders Decomposition for optimization, cross-docking systems , and hub location routing . His work spans theoretical advancements and industry collaborations in transportation and telecom sectors. Professional activities include memberships in leading OR societies (EWGLA, EWGT, VeRoLog) and roles as an ad-hoc reviewer for high-impact journals like Transportation Research Part E and European Journal of Operational Research .

• Decision Making Under Uncertainty
• Stochastic Dynamic Programming
• Operational Research
• +۳ مورد دیگر

Dr. Christopher Kirkbride is a Senior Lecturer in Management Science at Lancaster University's Management School. His research focuses on decision-making under uncertainty, employing methodologies such as stochastic dynamic programming, simulation, and approximate dynamic programming to address challenges in project scheduling, nuclear decommissioning, workforce planning, and asset management. He actively supervises PhD students and participates in interdisciplinary research groups like STOR-i and the Lancaster Intelligent Systems Centre. Key research projects include optimizing nuclear decommissioning processes and developing resource allocation strategies for dynamic environments. He has presented at major conferences such as EURO and IFORS, contributing to both academic and applied operational research communities. His work bridges theoretical advancements with practical applications, emphasizing robust solutions for stochastic systems. Dr. Kirkbride advises PhD students on topics including reinforcement learning applications and optimization for dynamic systems. His grants include projects funded through STOR-i, focusing on reinforcement learning safety and machine learning-optimization integration. He collaborates with teams specializing in simulation, stochastic modeling, and intelligent systems, further enhancing interdisciplinary research impact.

Niki Matinradمشاهده پروفایل

استادیار

• Emergency Response Logistics
• Health Care Logistics
• Quantitative Logistics
• +۵ مورد دیگر

Niki Matinrad is an Assistant Professor at Linköping University, affiliated with the Communications and Transport Systems (KTS) division within the Department of Science and Technology (ITN). Their research focuses on emergency response and healthcare logistics, emphasizing optimization of volunteer networks and resource allocation in crisis scenarios. Collaborating closely with the rescue and healthcare sectors, their work integrates operations research and systems analysis to enhance disaster preparedness and response efficiency. Research interests include volunteer center localization, unmanned aerial systems (UAS) in search and rescue, sustainable supply chain design for crisis management, and predictive modeling for emergency medical service demand. Niki is part of the Center for Advanced Research in Emergency Response (CARER) and contributes to the Quantitative Logistics (KL) research group. Recent publications highlight innovations in rural emergency volunteer networks, UAS dispatch strategies from maritime platforms, and optimal task assignment algorithms for cardiac arrest response. Their interdisciplinary approach bridges technical, organizational, and socio-cultural dimensions of crisis management. As a member of the Junior Faculty network at Linköping University, Niki actively engages in advancing early-career research leadership while maintaining strong ties to industry and governmental stakeholders in emergency logistics and transport systems.

James W. Lark, IIIمشاهده پروفایل

دانشیار

• Computational Statistics
• Simulation/Statistical Modeling
• Risk and Decision Analysis
• +۳ مورد دیگر

James W. Lark, III is an Associate Professor holding a primary appointment at the Center for Applied Mathematics and a joint appointment in the Department of Systems and Information Engineering at the University of Virginia. He has served in multiple roles, including Director of Research at DRA Research and Assistant to the Athletics Director for Special Projects at UVA. His research focuses on computational statistics, stochastic modeling, and optimization. Education: Ph.D. in Systems Engineering (UVA, 1990) and B.S. in Mathematics (Virginia Tech, 1977). He developed the 'Lark algorithm,' a foundational procedure in probabilistic modeling now widely referenced in academic literature. Research Interests include risk analysis, simulation methodologies, and decision-making frameworks. He has taught courses across applied mathematics, statistics, and systems engineering, such as APMA 3080 (Linear Algebra) and SYS 6003 (Optimization I). Awards include the 2011 Outstanding Undergraduate Teaching Award from the International Council on Systems Engineering. His work spans interdisciplinary collaborations, with affiliations extending to the Department of Statistics and institutions like UC Berkeley and Virginia Tech.

• Online Resource Allocation
• Scheduling Algorithms
• Machine Learning
• +۶ مورد دیگر

Qingsong Liu is a Postdoctoral Researcher at the University of Massachusetts Amherst, affiliated with the Lederle Graduate Research Center. His primary focus is on online algorithms, optimization techniques, and their applications in distributed systems, communication networks, and cloud computing. He explores challenges such as fair resource allocation, scheduling under constraints, and privacy-preserving mechanisms. Research interests include adversarial combinatorial bandits, real-time scheduling, and convex optimization with switching costs. His work often addresses multi-agent systems, constraint violations, and time-varying environments, aiming to develop scalable solutions for modern computational problems. Recent publications highlight trends in dynamic regret analysis, decentralized scheduling, and privacy-enhanced DNS services (e.g., T2DNS). While no scientific awards or grants are explicitly listed, his contributions emphasize theoretical foundations and practical implementations in networking and machine learning domains.

Soheil Davariمشاهده پروفایل

مدرس ارشد

• Rare Earth Minerals
• Renewable Energy
• Supply Chain Management
• +۳ مورد دیگر

Dr. Soheil Davari is a Senior Lecturer (Associate Professor) at the University of Bath's School of Management, serving as Director of Accreditations. He holds a PhD in Management Sciences and is a Senior Fellow of the Higher Education Academy (SFHEA). His research focuses on rare earth minerals, renewable energy systems, supply chain resilience, and food resilience. He has over 20 years of industry experience across healthcare, retail, pharmaceuticals, and education sectors. Education: Doctor of Philosophy in Management Science (2007–2012) Master of Science in Industrial Engineering (2005–2007) Bachelor of Science in Industrial Engineering (2000–2005) Research Interests: Dr. Davari's work addresses critical issues in sustainable systems, including rare earth mineral supply chains, renewable energy infrastructure, and healthcare network optimization. His research bridges operations research and real-world applications, with notable contributions to facility location problems, emergency service modeling, and technology adoption studies among older adults. Awards: Senior Fellow of Higher Education Academy (2019) External Roles: External Examiner at Imperial College London (2021–2025) British Academy of Management Consultancy Network Committee Member (2025–present) Academic Board Member at London School of Innovation (2024–present) Key Research Themes: His recent work emphasizes sustainable energy systems, healthcare resource optimization, and digital inclusion challenges. Notable projects include hospital resource models, ambulance demand forecasting systems, and preventive healthcare network design.

Nancy Puccinelliمشاهده پروفایل

استاد

• Consumer Behavior
• Affective Influences on Decision-Making
• Retail Strategies
• +۳ مورد دیگر

Nancy Puccinelli is a Professor in the Department of Management, Marketing, and Business & Society at the University of Bath. Her research focuses on consumer behavior, particularly the role of interpersonal customization and affective influences in retail contexts. She investigates how mood and emotions impact consumer decision-making, nonverbal communication in service interactions, and psychological factors driving retail behavior. Her work spans global contexts including Senegal, Chile, and China. Key research areas include: 1) Affect's impact on tolerance for ambiguity, ad preferences, and retail outlet choices; 2) Salespeople's ability to read nonverbal cues improving perceived service quality; 3) Gender differences in price perception influenced by color (e.g., red vs black pricing). She actively supervises doctoral students with a focus on consumer behavior, offering funded opportunities aligned with her research interests. Her publications analyze meta-analytic integration of affect effects, in-store atmospheric elements, and digital age marketing strategies. She contributes to UN Sustainable Development Goals through consumer-centric retail research. Advising: Offers fully-funded studentships for candidates aligning with her research themes. Grants and collaborations involve cross-cultural studies and experimental marketing methodologies.

Bernardo Martin Iradiمشاهده پروفایل

مدرس

• Public transportation
• On-demand mobility
• Maritime logistics
• +۳ مورد دیگر

Bernardo Martin Iradi is a Lecturer at the Department of Civil, Environmental and Geomatic Engineering at ETH Zurich. He holds a PhD in Operations Research from DTU Management (Technical University of Denmark) and has served as a Postdoctoral researcher and teaching assistant at ETH Zurich since 2023. His professional experience includes roles as a Doctoral researcher at DTU, a routing consultant at AMCS Group, and teaching responsibilities in courses like Logistics and Freight Transportation and Transport Systems. His research focuses on public transportation optimization , on-demand mobility systems , maritime logistics , and network optimization . Notable projects include developing algorithms for railway timetabling stability, cooperative game analysis in multi-port operations, and dynamic capacity planning for multimodal transit systems. Recent work emphasizes microscopic modeling of railway networks, logic-based decomposition approaches for timetabling, and stochastic optimization for demand-responsive transit. He has presented at leading conferences such as RailDresden 2025 and TRISTAN XII, showcasing advancements in transportation systems optimization. Education: PhD in Operations Research (2019–2023), DTU Management MSc in Industrial Engineering and Management (2016–2018), Technical University of Denmark BSc in Industrial Technology Engineering (2011–2015), Polytechnical University of Catalonia Professional contributions include collaborations with industry partners like AMCS Group and involvement in projects like the DADA initiative addressing railway delay propagation. His work bridges theoretical optimization methods with practical transportation challenges.

Sylvie Thiebauxمشاهده پروفایل

استاد

• Artificial Intelligence
• Energy Systems
• Optimization
• +۵ مورد دیگر

Sylvie Thiebaux is a Professor at the School of Computing, Australian National University (ANU). Her research focuses on artificial intelligence, particularly in planning algorithms, heuristic search, and their applications to energy systems and optimization. She holds a Dipl.Eng. from INSA Rennes, an MSc from Florida Tech, and a PhD from Université de Rennes/CNRS. Her work integrates machine learning with classical AI techniques to address challenges in smart grids, renewable energy integration, and multi-objective decision-making. Key projects include optimizing distribution networks with high PV penetration, developing robust control strategies for volt/Var systems, and advancing neuro-symbolic AI for planning under uncertainty. She has contributed to over 90 publications and actively supervises research students in computational planning and energy systems. Her research also explores ethical considerations in AI, including normative compliance in planning systems. Collaborative initiatives with industry and academia have led to advancements in energy market frameworks and distributed resource coordination.

Carolin Bauerمشاهده پروفایل

مدرس ارشد

• Computer Networks
• Wireless Communication
• Cellular Communication
• +۵ مورد دیگر

Carolin Bauer is a Senior Lecturer in the Department of Computing at Staffordshire University. Her expertise spans Computer Networks, Wireless Communication, and Artificial Intelligence, with a focus on Genetic Algorithms and Neural Networks. She holds a PhD in Cellular Communication (2010) and certifications including Cisco CCNA/CCNP Academy Instructor and AWS Academy roles. Education: 1999: Diplom der Technischen Informatik (FH)/BSc, HTWG Konstanz, Germany 2001: MSc by Research in Distributed Systems, Staffordshire University 2010: PhD in Cellular Communication, Staffordshire University Research focuses on evolving network communication technologies, including Cloud Technology and IoT, aiming to enhance real-world applications. Her work bridges theoretical advancements with practical implementation in education and industry. Publications highlight contributions to neural network optimization, cellular handover prediction, and genetic algorithm applications. Awards include the 2013 Fellowship of the Higher Education Academy (FHEA). Teaching spans undergraduate to postgraduate levels, emphasizing Cisco Networking and AWS Cloud Computing. She actively engages in professional development initiatives to integrate cutting-edge technologies into curricula.

D. Marc Kilgourمشاهده پروفایل

استاد

• Game Theory
• Decision Analysis
• Conflict Resolution
• +۵ مورد دیگر

D. Marc Kilgour is a Professor of Mathematics at Wilfrid Laurier University, affiliated with the Faculty of Science. His research focuses on multiple-person decision analysis, game theory, fair division, voting systems, and environmental management. He has contributed to resolving complex conflicts through mathematical models, including water resource allocation disputes and strategic negotiations. His expertise spans international strategy, arms control, and the strategic analysis of voting systems. Kilgour’s work integrates theoretical rigor with practical applications, such as improving fairness in sports (e.g., soccer shootouts and tennis tiebreakers) and optimizing resource distribution algorithms. He has published extensively on conflict resolution frameworks, stability definitions, and multi-criteria decision analysis. Recent research highlights include redefining sequential stability in multi-decision-maker conflicts, analyzing environmental misalignment in logistics, and exploring fair division algorithms for indivisible items. His methodologies often involve graph models, fuzzy preferences, and matrix representations to address uncertainty and complexity in decision-making scenarios. Kilgour’s academic contributions are reflected in over 150 peer-reviewed articles and collaborations on real-world policy issues, such as the US-China trade dispute and urban planning in Brazil. His work bridges theoretical game theory with actionable solutions for environmental, economic, and social challenges.