جست‌وجوی استاد و پژوهشگر

Hasnaa Zidaniمشاهده پروفایل

استاد

• Optimal Control
• Applied Mathematics
• Numerical Analysis
• +۳ مورد دیگر

Hasnaa Zidani is a Professor in applied mathematics at INSA Rouen Normandie, affiliated with the Laboratoire de Mathématiques de l'INSA (LMI), CNRS EA-3226. She holds the Chaire d'excellence 'COPTI' (2021–2025), funded by ANR, Région Normandie, and the EU, focusing on optimal control applications in environmental modeling, transportation, and image processing. Her research emphasizes optimal control theory, Hamilton-Jacobi equations, numerical methods, and stochastic systems. Recent activities include organizing conferences like the “On the Road to New Horizons” event (June 2024) celebrating Witold Respondek and serving as a speaker at the 3rd International Conference on Variational Analysis (2024). She co-leads the Workshop on Optimal Control Theory (2023) and has contributed to the ROC-HJ solver for optimal control problems. Key research interests include multi-objective optimization, stochastic control, and applications in aerospace engineering. Her work bridges theoretical advancements with practical tools like the ROC-HJ software. Awards include the COPTI excellence chair, recognizing her contributions to applied mathematics and control theory. Grants: COPTI Project (ANR, 2021–2025) Labs/Teams: Laboratoire de Mathématiques de l'INSA (LMI), collaboration with CMM (Chile) and Thales Alenia Space

Germano Veigaمشاهده پروفایل

استادیار

• Industrial Robotics
• Robotics and Automation
• Human-Robot Collaboration
• +۳ مورد دیگر

Germano Veiga is an Assistant Professor at the Faculty of Engineering of the University of Porto and Senior Researcher at INESC TEC in Porto. He holds a PhD in Mechanical Engineering (Robotics and Automation) from the University of Coimbra (2010). His research focuses on future industrial robotics, including plug-and-produce technologies, mobile manipulators, and human-robot interfacing. He has led major EU projects such as H2020 ScalABLE4.0 and coordinated teams in FP7 initiatives like CARLoS and STAMINA. His work emphasizes automation in automotive manufacturing, sensor integration, and collaborative robotics. Education: PhD in Mechanical Engineering (Robotics and Automation), University of Coimbra, 2010 Mechanical Engineering Degree Research Interests: Industrial robotics, human-robot collaboration, automated manufacturing systems, 3D sensing, and quality control. His recent projects address challenges in automotive assembly lines, bin-picking robotics, and ergonomic laboratory automation. Recent Projects: Coordinator of H2020 ScalABLE4.0 (2017-?) FP7 ECHORD Executive Committee (2009-2012) FP7 SMErobotics (part of coordination team) Advising & Grants: Supervised 6+ graduate theses in robotics and automation. Active in EU-funded research coordination. Labs & Teams: Leads robotics teams at INESC TEC focusing on Industry 4.0 solutions and cyber-physical systems integration.

Martin Hitzمشاهده پروفایل

استاد

• Human-Computer Interaction
• Usability Engineering
• Smart Home Systems
• +۵ مورد دیگر

Martin Hitz is a Full Professor for Interactive Systems at the University of Klagenfurt , where he founded the Interactive Systems research group (IAS) in 2000. He serves as Chairman of the University Senate (2022-2025) and previously as Vice Rector (2001-2006, 2012-2020) and Dean of the Faculty of Technical Sciences (2007-2012). His academic career includes assistant/associate professor roles at the University of Vienna and visiting positions at Politecnico di Milano, University of Ottawa, and University of Linz.

• Optimization applied to complex problems
• Predictive modeling in healthcare
• Interpretable Machine Learning
• +۹ مورد دیگر

Sara Lumbreras Sancho is a Senior Associate Professor at the ICAI School of Engineering, Universidad Pontificia Comillas, where she graduated in 2006 as the Graduation Prize Winner. She serves as Deputy Director of Research Results at the Technological Research Institute and co-leads the Chair of Science, Technology, and Religion with Jaime Tatay. Her research focuses on decision support techniques for complex problems in energy, healthcare, and finance, leveraging optimization methods like Benders decomposition, heuristics, and AI. She also explores the philosophy of technology, transhumanism, and AI's impact on anthropology. With over 70 academic publications and leadership in over 20 projects, she bridges technical innovation with ethical and anthropological considerations. Education: Bachelor’s Degree in Engineering from ICAI School of Engineering (2006) PhD in Decision Support Methods for Large-Scale Flexible Transmission Planning (2014) Research Interests: Optimization techniques (stochastic, Benders, metaheuristics) Predictive healthcare modeling Interpretable machine learning AI ethics and responsible science Energy systems planning (wind farms, transmission networks) Philosophical implications of technology Grants & Projects: Lead researcher in EU-funded initiatives like DIAMOND and OPEN_ENTRANCE Collaborations with industries like Iberdrola, Enel, and Pharoes Advisory Transnational projects addressing energy transition challenges Awards: Global Shaper (World Economic Forum) Marshall Memorial Fellow Outreach: Chair of Cátedra de Ciencia, Tecnología y Religión Keynote speaker at conferences like EURO 2025 and Science and Religion Forum Author of books and book chapters on AI ethics, transhumanism, and science-religion dialogue

• Process Systems Engineering
• Optimization
• Chemical Engineering
• +۶ مورد دیگر

Matthew J. Realff is a Professor in the School of Chemical and Biomolecular Engineering at the Georgia Institute of Technology. With an extensive publication record spanning over three decades, his work focuses on the intersection of chemical engineering, process systems engineering, and advanced computational methods. His research has made significant contributions to optimization techniques, supply chain management, and sustainable engineering practices. Dr. Realff's research interests span a broad range of topics in process systems engineering, with particular emphasis on optimization under uncertainty, supply chain modeling, and sustainable engineering practices. His work combines rigorous mathematical approaches with practical engineering applications, particularly in the areas of biorefinery systems, carbon capture technologies, and renewable energy integration. He has pioneered methodologies that bridge traditional chemical engineering with modern computational techniques including machine learning and Bayesian statistics. Analysis of his recent publications reveals a consistent focus on addressing complex engineering challenges through advanced computational methods. His work demonstrates a strong trajectory toward integrating data-driven approaches with traditional process engineering, particularly evident in his recent papers on Bayesian experimental design, uncertainty quantification, and machine learning applications in chemical processes. The interdisciplinary nature of his research connects chemical engineering with operations research, environmental science, and computer science. Throughout his career, Dr. Realff has maintained a productive research program with consistent publication output in top-tier chemical engineering and operations research journals. His collaborations span multiple institutions and disciplines, reflecting the interdisciplinary nature of modern engineering research. He has supervised numerous graduate students and contributed significantly to the education and training of future engineers through his academic appointments and research mentorship.

Gao Jieمشاهده پروفایل

استاد

• Algorithms
• Wireless Networks
• Social Networks
• +۳ مورد دیگر

Jie Gao is a Professor of Computer Science at Rutgers University, serving as the Graduate Program Director. Her research focuses on algorithms, computational geometry, wireless networks, and social networks. She holds an office in Hill 411 and can be reached at jg1555@rutgers.edu. Her work emphasizes geometric algorithms, privacy-preserving techniques, and network optimization. Professor Gao teaches advanced courses such as Computational Geometry (CS529), Design and Analysis of Data Structures and Algorithms (CS513/CS514), and Introduction to Discrete Structures (CS205). Her courses blend theoretical foundations with practical applications in geometric computing and algorithm design. Her research group explores geometric algorithms, distributed systems, and privacy-preserving data analysis. Notable projects include developing efficient algorithms for unit-disk graphs, security game theory for patrol scheduling, and methodologies for interpreting health data from wearable devices. She actively contributes to the field through interdisciplinary collaborations, addressing challenges in both theoretical and applied computing domains.

• Operational Research
• Optimization Methods
• Logistics and Supply Chain Management
• +۷ مورد دیگر

Manuel Iori is a Full Professor at the Department of Engineering Sciences and Methods, University of Modena and Reggio Emilia (UNIMORE), Italy. His primary research focuses on operational research, optimization methods, and logistics systems. He specializes in vehicle routing problems, scheduling algorithms, and decision support systems with applications in industrial automation, healthcare, and service industries. Iori is actively involved in teaching advanced optimization courses for engineering students, emphasizing practical applications in data-driven decision-making and simulation. Research Interests: His work addresses complex optimization challenges such as multi-trip vehicle routing with time windows, scheduling under resource constraints, and tool switching in manufacturing systems. He integrates machine learning and metaheuristics to develop innovative solutions for logistics, production planning, and healthcare operations. Collaborations with industry partners (e.g., pharmaceutical distributors, printing companies) ensure practical relevance of his research. Teaching: Iori teaches courses like Optimization Methods for Data-Driven Engineering Processes , Models for Logistics and Production Optimization , and Methods and Algorithms for Optimization in Digital Industries . These courses combine theoretical foundations with hands-on labs using tools like Python, Xpress, and Anylogic. Key Contributions: He developed decision support systems for multi-trip routing in pharmaceutical distribution and supplier selection in facility management. His research on satellite scheduling and attended home delivery systems advances both theoretical and applied domains. As a member of CIRRELT (Canada), he collaborates on logistics optimization projects. Professional Activities: Iori’s work is reflected in over 80 peer-reviewed publications and contributions to conferences. He advises graduate students on optimization challenges and serves as a reviewer for top journals in operations research.

Mario Zanonمشاهده پروفایل

دانشیار

• Optimal Control
• Reinforcement Learning
• Model Predictive Control (MPC)
• +۴ مورد دیگر

Mario Zanon is an Associate Professor at the IMT School for Advanced Studies Lucca, Italy. He holds a B.Sc. in Industrial Engineering (University of Trento, 2008), an M.Sc. in Mechatronics (University of Trento, 2010) and General Engineering (Ecole Centrale Paris, 2010), and a Ph.D. in Electrical Engineering (KU Leuven, 2015). His postdoctoral research (2015–2017) was at Chalmers University of Technology. He joined IMT Lucca in 2018 as Assistant Professor, advancing to his current rank in 2021. His research focuses on Reinforcement Learning, distributed and economic Model Predictive Control (MPC), optimal control of nonlinear systems , with applications in aerospace and automotive domains. He investigates safety-critical systems, autonomous driving, and coordination of vehicles in mixed traffic environments. His work emphasizes theoretical guarantees, computational efficiency, and practical implementation. Recent publications highlight advancements in MPC stability, safe autonomous systems, and optimization algorithms for machine learning. His studies on intersection coordination and disturbance modeling contribute to safer, efficient autonomous vehicle systems. Current research trends include reinforcement learning integration with MPC, data-driven terminal cost design, and scalable optimization for complex systems. Zanon’s work has been applied to real-world scenarios like vaccine distribution optimization during the pandemic and thermal welding modeling. He collaborates with industry partners on autonomous driving and robotics, emphasizing practical, safety-first solutions. Future directions include advancing learning-based MPC and exploring hybrid systems in robotics.

Nina Skorin-Kapovمشاهده پروفایل

دانشیار

• Optimization of Communication Networks
• Wide-Area Optical Networks
• Operations Research
• +۳ مورد دیگر

Dr. Nina Skorin-Kapov is an Associate Professor at the Technical University of Cartagena, associated with the Centro Universitario de la Defensa de San Javier. She holds a PhD in Telecommunications and Informatics from the University of Zagreb and completed a postdoctoral fellowship at Telecom ParisTech. Her research focuses on optimization of communication networks, wide-area optical networks, operations research, and heuristic algorithms. She leads the Computational and Telecommunications Engineering Group (GICOT) and serves on the editorial board of the IEEE/OSA Journal of Optical Communications and Networking. Her academic roles include teaching undergraduate courses on Electromagnetic Exploration Systems and graduate courses on Metaheuristics and Graph Theory. Key research contributions include work on network security, routing algorithms, and capacity planning in optical networks. Notable projects include the Movilidad Ecoeficiente y Conectada para Ciudadanos initiative (2020–2022), funded by IDAE. Her publications span topics like wildfire resource scheduling, drone control systems, and secure optical network design. Dr. Skorin-Kapov’s articles emphasize practical applications of optimization techniques, such as scheduling aerial resources for wildfire management and improving QoE in drone teleoperation. Her work bridges theoretical research with real-world network challenges, particularly in telecommunications and disaster response scenarios.

David Poza Garcíaمشاهده پروفایل

دانشیار

• Additive Manufacturing
• Project Management
• Combinatorial Auctions
• +۱ مورد دیگر

David Poza García is an Associate Professor at the University of Valladolid’s Department of Business Organisation and Market Research. He holds affiliations with INSISOC (GIR UVa, GREX251, UIC086) and professional organizations including ESSA, ADINGOR, and AEIPRO. His certifications include IPMA-D Project Management accreditation. Research focuses on optimization in industrial systems, spanning additive manufacturing, project scheduling, combinatorial auctions, and risk modeling. Key themes include algorithmic efficiency, stochastic analysis, and sustainable operations. Publications emphasize computational methods for industrial challenges, with recent trends in simulation-based scheduling, additive manufacturing economics, and uncertainty management in project frameworks. No advising roles, grants, or lab affiliations are detailed in available texts.

Myra Cohenمشاهده پروفایل

استاد

• Software Engineering
• Search-Based Software Engineering
• Highly-Configurable Software Testing
• +۵ مورد دیگر

Myra B. Cohen is a Professor and the Lanh and Oanh Nguyen Chair in Software Engineering at Iowa State University's Department of Computer Science, part of the College of Engineering. She previously held the Susan J. Rosowski Professorship at the University of Nebraska-Lincoln. Her research focuses on software testing of highly-configurable systems, search-based software engineering, and applications in synthetic biology and bioinformatics. Cohen holds a Ph.D. from the University of Auckland, M.S. from the University of Vermont, and B.S. in Agriculture from Cornell University. Education: Ph.D., Computer Science, University of Auckland, 2004 M.S., Computer Science, University of Vermont, 1999 B.S., School of Agriculture and Life Sciences, Cornell University Research Interests: Testing of cyber-physical systems and scientific software Combinatorial design applications in software assurance Synergies between software engineering and synthetic biology Configuration-aware testing for safety-critical systems Recent Projects: OPERA: Rural broadband solutions through open-source ecosystems Dependable AI-driven computational biology tools for KBase Blockchain fault tolerance modeling and measurement Self-adaptive mechanisms for unmanned aerial systems Awards: NSF CAREER Award AFOSR Young Investigator Award ACM Distinguished Scientist ASE Conference Fellow Leadership Roles: Program Co-Chair: ESEC/FSE 2020, ISSTA 2025 General Chair: ASE 2015 Steering Committee: ASE, ESEC/FSE, ISSTA Labs & Affiliations: Director: LaVA-OPs (Variability-Aware Assurance Lab) Center for Wireless, Communities and Innovation (WiCI) Bioinformatics & Computational Biology Graduate Program

Caroline Chanelمشاهده پروفایل

استاد

• Autonomous Systems
• Decision-Making Algorithms
• Robotics
• +۳ مورد دیگر

Caroline Chanel is a Professor at ISAE-SUPAERO (DCAS), holding the CASAC Chair since 2022. She has extensive experience in research and teaching, with roles including Associate Professor (2019-2024), Research Engineer (2013-2019), and HDR accreditation (2023). Her research focuses on embedded decision-making for autonomous systems, including proactive architectures, multi-robot cooperation, and human-machine interaction. She leads and participates in high-profile projects like SAMURAI (AID), CHIP-GT (ANR-DFG), and HAICO (CASAC Chair). She has supervised numerous PhD students and post-doctoral researchers, collaborating with institutions like ONERA, INRAe, and international partners. Education: PhD in Control and Embedded Systems (University of Toulouse 2013), Master's in Automatic Systems (Université Paul Sabatier 2008-2009), and Engineer Diploma from PUCRS (2002-2008). Awards include the Amelia Earhart Fellowship (2011) and ISAE-SUPAERO Foundation PhD Fellowship (2013). Research interests span decision-making algorithms, multi-agent systems, and neuroergonomics. Key projects address UAV navigation, blockchain integration for autonomous systems, and physiological computing for human-robot interaction. Teaching responsibilities include modules on autonomous systems, control systems, and neuroergonomics at ISAE-SUPAERO's engineering and master's programs. She co-leads the DECISIO doctoral team (ISAE-ONERA) and is involved in executive roles for conferences like EDSYS'.

• Scheduling and Control
• Discrete Event Systems
• Real-Time Systems
• +۳ مورد دیگر

Patrice Bonhomme is a Teacher-researcher at the University of Tours, affiliated with the Polytechnic School of the University of Tours (EPU) and the Fundamental and Applied Computer Science Laboratory of Tours (LIFAT, UR 6300). His primary role involves both teaching and research activities within the Computer Science Department. Patrice holds a PhD from the University of Tours, as evidenced by his 'MEMOIRE DE THESE' published in 2001. His educational background and current position reflect a deep specialization in computer science and engineering disciplines. His research interests focus on Scheduling and Control , Discrete Event Systems , and Real-Time Systems , with particular emphasis on Petri Nets as a modeling framework. He explores advanced control strategies, state estimation techniques, and fault diagnosis methodologies for time-critical systems. Key areas include energy optimization, decentralized control policies, and symbolic analysis of Petri Net-based systems. In recent years, his work has centered on developing novel algorithms for P-Time Petri Nets, addressing challenges in unobservable transitions and partial observability. He has contributed to both theoretical advancements and practical applications in manufacturing and real-time system optimization. Patrice has been actively involved in international conferences, presenting papers at IFAC and IEEE events. Notably, he served as a reviewer for the T-ASE journal (2004-2005) and contributed to proactive/reactive control methodologies for time-critical systems. His research demonstrates a consistent trajectory toward enhancing system efficiency through formal methods and algorithmic innovations. He is part of the Computer Science Laboratory Team at the University of Tours, specializing in the control of discrete event systems. No scientific awards are explicitly listed in his profile, and he has no documented advisees.

• Scheduling
• Flexibility
• Robustness
• +۳ مورد دیگر

Carl Esswein is a Lecturer-researcher in the Computer Science Department of the Polytechnic School of the University of Tours (EPU), affiliated with the Fundamental and Applied Computer Science Laboratory of Tours (LIFAT). His work focuses on scheduling problems with objectives centered on flexibility and robustness. Doctoral thesis, François Rabelais University of Tours (2003) DEA Computer Science, François Rabelais University of Tours (2001) Diploma in Computer Science Engineering for Industry (DIII), François Rabelais University of Tours (2001) Esswein's research explores the intersection of scheduling, flexibility, and robustness in operational research. His publications address multi-criteria optimization, robust shop scheduling, and algorithm design for complex scheduling scenarios. He has contributed to methodological advancements such as revisiting Branch and Bound strategies and analyzing trade-offs between flexibility and makespan efficiency. His work spans theoretical and applied domains, including enumeration complexity in multicriteria scheduling, optimization algorithms for production planning, and computational methods for constraint satisfaction in manufacturing systems. Publications highlight interdisciplinary applications in industrial engineering and computer science. Carl Esswein is actively associated with the LIFAT laboratory, where he collaborates on fundamental and applied research in computer science. His affiliations include the Computer Science Department of Polytech'Tours and the University of Tours.

Majid Eskandarpourمشاهده پروفایل

دانشیار

• Operations Management
• Supply Chain Network Design
• Sustainable Logistics
• +۱ مورد دیگر

Majid Eskandarpour is Associate Professor at IÉSEG, specializing in Operations Management. His research focuses on sustainable supply chain network design, logistics optimization, and renewable energy operations. Dr. Eskandarpour holds a Ph.D. in Management Sciences from Ecole des Mines de Nantes, a Master's in Industrial Engineering from Tarbiat Modares University, and a Bachelor's from Azad University. His research explores multi-objective optimization in healthcare networks, disruption management in distribution systems, and maintenance routing for offshore wind farms. Methodologically, he develops exact algorithms and metaheuristic approaches for complex logistics problems. Before academia, he held industry positions as Production Planning Manager at Iran Booster Co and industrial planning roles at Solico Group.