Find Academic Supervisors

Odile BellenguezView profile

Professor

• Computer Science
• Ethics in Technology
• Operations Research
• +3 more

Professor Odile Bellenguez is a faculty member in the Automation, Production and Computer Sciences department at IMT Atlantique. Her work focuses on integrating ethical considerations into algorithm design, particularly in personnel scheduling and decision support systems. She holds a University Diploma in Philosophy from Université Paris Nanterre, enhancing her interdisciplinary approach. Her research bridges computer science, discrete mathematics, and social sciences, with collaborations in sociology, psychology, and management science. Notable projects include co-supervising a thesis on ethical inclusion in healthcare scheduling and developing fair nurse rostering algorithms. She also pioneered a philosophy-infused framework for algorithmic ethics, addressing fairness and equity in automated systems. Professor Bellenguez actively engages in pedagogy, designing courses that teach ethical implications of algorithms through case studies like traffic navigation and workforce scheduling. Her recent work emphasizes cross-disciplinary dialogue to address societal challenges posed by algorithmic systems. Her contributions span over 50 publications, with a focus on scheduling optimization (RCPSP variants, nurse rostering) and ethical frameworks for automated decision-making. She plans to host a summer school for PhD students exploring ethics in algorithmics.

• Operations Research
• Optimization under Uncertainties
• Scheduling Algorithms
• +4 more

Faicel HNAIEN is a Full Professor at the Université de Technologie de Troyes (UTT), where he leads the Computer Science and Applied Mathematics Academic Department since December 2024. He also heads the Optimization Axis (LIST3N laboratory) with 30 members and oversees the International Master's Track in Logistics and Transport in Togo since 2023. His research focuses on optimization under uncertainties, scheduling algorithms, inventory control, wireless sensor networks, and quantum optimization. His work bridges theoretical advances with practical applications in manufacturing systems, energy management, and logistics. Responsibilities include academic leadership roles, strategic planning for research initiatives, and international program coordination. His recent projects address challenges like energy cost optimization in production scheduling, robust supply chain management under uncertainty, and deployment strategies for sensor networks in hazardous environments. He actively contributes to interdisciplinary research, integrating stochastic modeling, combinatorial optimization, and quantum computing approaches. His publications span high-impact journals such as Annals of Operations Research and European Journal of Industrial Engineering. Research trends emphasize hybrid methods (exact/ heuristic), stochastic programming for inventory systems, and multi-objective optimization in dynamic environments. Current efforts explore quantum formulations for scheduling problems and AI-driven solutions for supply chain resilience.

• Transportation and Distribution Logistics
• Operations Research
• Vehicle Routing Problems
• +4 more

Nacima Labadie is a Full Professor at the University of Technology of Troyes (UTT), leading the Industrial Engineering department since 2018. She holds roles in academic governance, including membership in UTT's Scientific Council (since 2017) and the Computer Science and Digital Society Laboratory Council (since 2021). Her research focuses on Transportation and Distribution Logistics , Operations Research , and Numerical Optimization , with applications in vehicle routing problems, blood supply chains, and sustainable logistics. She pioneered the C2P Collaborative Network VRP and Grey Zone Two-Echelon VRP , addressing urban and eco-friendly delivery challenges. Her work spans metaheuristic algorithms (e.g., GRASP, Iterated Local Search) for stochastic optimization and supply chain design. Notable contributions include models for biomass supply chains, blood distribution systems, and decision support platforms like AidAdom for healthcare coordination. Recent publications emphasize low-emission logistics , urban traffic optimization , and multi-objective decision-making in complex networks. Her research integrates simulation tools (ARENA/CPLEX) and signal processing techniques for graph-based problems. As a department head, she oversees 300+ students and guides the Optimization and Systems Safety master’s program. Her work aligns with UTT’s strategic goals in Operational Research and Digital Society initiatives.

Yves RobertView profile

Professor

• Parallel Computing
• Scheduling Algorithms
• High-Performance Computing (HPC)
• +5 more

Yves Robert is a Professor at the Computer Science Laboratory LIP (Laboratoire de l'Informatique du Parallélisme) at École Normale Supérieure de Lyon (ENS Lyon). He also holds a Visiting Scientist position at the University of Tennessee Knoxville since 2011. His research focuses on resource optimization, parallel algorithms, scheduling techniques, and resilience methods in high-performance computing (HPC). Key areas include fault-tolerant numerical algorithms, energy-efficient scheduling, and iterative application checkpointing strategies. Robert has received prestigious awards such as the 2020 IEEE Computer Society Charles Babbage Award for contributions to parallel algorithms and scheduling. He is an IEEE Fellow (since 2005) and a Senior Member of Institut Universitaire de France. His work bridges theoretical foundations and practical algorithmic solutions, addressing challenges in distributed-memory architectures, workflow scheduling, and resilience at scale. His research spans parallelizing compilers, task graph scheduling, and energy-aware computing. Notable contributions include optimizing checkpointing strategies for HPC platforms, analyzing fault tolerance in iterative applications, and developing resilient scheduling heuristics for parallel jobs. His work often emphasizes scalability and reliability in modern computing systems.

Yusufcan MasatliogluView profile

Professor

• Decision Theory
• Bounded Rationality
• Behavioral Economics
• +3 more

Yusufcan Masatlioglu is a Professor of Economics at the University of Maryland's Department of Economics, part of the College of Behavioral and Social Sciences. He holds a Ph.D. in Economics from New York University (NYU) and previously served on the faculty of the University of Michigan. His research focuses on bounded rationality, decision theory, and the theoretical foundations of reference-dependent choice, time preference, limited attention, and willpower. He has received two National Science Foundation grants for studies on limited attention and random attention, and served as co-editor of Mathematical Social Sciences (2020–2021) and associate editor of the Journal of Political Economy (2021–2024). Education : Ph.D. in Economics, NYU Research Interests : Behavioral economics, cognitive limitations in decision-making, stochastic choice models, and the role of attention in preferences. His work has been published in top journals such as the American Economic Review, Journal of Political Economy, and Review of Economic Studies. He advises students at institutions including Cornell University, Purdue University, and the Brattle Group. Current research explores topics like attention overload, coherent distorted beliefs, and disentangling attention and utility in recommendations.

• Artificial Intelligence
• Neural Networks
• Robotics
• +5 more

Abdullatif Baba is an Assistant Professor in the Department of Computer Engineering at Turkish Aeronautical Association University. His research focuses on interdisciplinary applications of artificial intelligence, robotics, and sustainable energy systems. He develops solutions for smart infrastructure, including AI-driven energy forecasting, autonomous drones for grid maintenance, and hyperspectral imaging techniques. His research interests span: AI/ML Systems : Neural networks, probabilistic forecasting, and FPGA-accelerated deep learning Robotics : Autonomous drones with computer vision for industrial and energy applications Sustainable Energy : Solar-based systems, smart grid optimization, and consumption prediction Security : Chaos-based cryptographic systems for secure communications Recent publications (2020-2024) demonstrate strong trends in practical AI implementations. Key themes include energy forecasting using adaptive neural networks (11 papers), robotics for infrastructure maintenance (4 papers), computer vision for biometrics and imaging (3 papers), and cryptographic systems (2 papers). Methodologies frequently involve hybrid approaches combining ANN, fuzzy logic, and hardware acceleration. No awards, students, or grant details were mentioned in the source material. Research collaborations include institutions in Turkey and the Middle East.

Atul RaiView profile

Associate Professor

• Machine Learning
• Remote Sensing
• Hydrology
• +7 more

Atul Rai is an Associate Professor at Wichita State University, specializing in interdisciplinary research spanning machine learning, remote sensing, and optimization algorithms. His work integrates computational methods with real-world applications in healthcare, environmental science, and distributed computing systems. Key areas of focus include medical imaging analysis, satellite data-driven hydrological modeling, and task scheduling in fog-cloud environments. Research emphasizes innovations such as fuzzy logic-based medical image segmentation, deep learning for emotion classification in music, and genetic algorithm optimizations. Rai's contributions extend to ecological assessments using satellite technology, particularly in monitoring endangered species like the Ganga River dolphin. His publications reflect a blend of technical advancements and methodological innovations, addressing challenges in transdisciplinary collaboration frameworks and corporate financial disclosure practices. While no specific awards are documented, his extensive academic output highlights sustained contributions to multiple fields.

• Operations Research
• Combinatorial Optimization
• Network Design
• +3 more

Ulrich Pferschy is a Professor affiliated with the Department of Algorithms and Complexity at Technische Universität Wien (TU Wien). His research focuses on Operations Research, Combinatorial Optimization, and Network Design, with particular expertise in algorithms for knapsack problems, Steiner tree problems, and network optimization. He has supervised numerous PhD students, including M. Ruthmair, A. M. Chwatal, and M. Leitner, among others. His work combines theoretical insights with practical applications in telecommunications infrastructure and algorithm design. Pferschy has contributed to leading journals and conferences, publishing influential papers on topics such as multidimensional knapsack problems and survivable network design. Despite his extensive contributions, no scientific awards are explicitly mentioned in the provided text.

ZIDANI HasnaaView profile

Professor

• Optimal Control
• Mathematical Modeling
• Numerical Simulation
• +3 more

Hasnaa ZIDANI is a Professor in applied mathematics at INSA Rouen Normandie , holding the COPTI Chair . Her research focuses on optimal control , mathematical modeling , and numerical simulation , with applications to transportation systems (e.g., autonomous vehicles, traffic management) and environmental modeling (e.g., resource management, marine ecology). She leads the COPTI project, funded by the ANR , Région Normandie , and EU’s ERDF , aiming to advance international-level research in optimal control methods. Research priorities include Optimal control of large-scale and stratified systems, Trajectory planning and crowd movement optimization, Image segmentation and optimal transport, Applications in aerospace (e.g., launcher trajectory optimization) and energy (e.g., demand response systems). ZIDANI actively contributes to academic events, such as the 2024 conference on Control Theory (co-chair) and the 2023 workshop on Optimal Control in Italy . She collaborates with institutions like Thales Alenia Space and develops tools like the ROC-HJ solver for reachability analysis and optimal control. Affiliations : Laboratoire de Mathématiques de l’INSA Rouen (LMI), CNRS EA-3226. Contact via Hasnaa.Zidani@insa-rouen.fr .

Juraj HromkovičView profile

Professor

• Theoretical Computer Science
• Algorithms
• Complexity Theory
• +6 more

Juraj Hromkovič is a Full Professor of Computer Science at the Swiss Federal Institute of Technology (ETH Zurich) , holding this position since 2004. His academic career spans multiple institutions, including Professorships at Christian Albrechts University in Kiel (1994-1997), RWTH Aachen (1997-2003), and earlier roles at Comenius University and the University of Paderborn. Education : 1977–1982: Studied Computer Science at Comenius University, Bratislava 1982: Dr. rer. nat. (PhD equivalent) from Comenius University 1986: CSc (Ph.D.) in Theoretical Cybernetics 1990: Dr. Sc. in Mathematics and Physics Research Interests focus on Theoretical Computer Science , particularly Algorithms , Complexity Theory , and Communication Protocols . His work explores Randomized Algorithms , Approximation Techniques , and Automata Theory , with notable contributions to understanding exponential gaps in computational models and optimizing information dissemination in networks. His publications span books, journal articles, and conference papers addressing foundational and applied aspects of computing. Scientific Awards include membership in the Slovak Academy of Sciences (2001) and two awards from the Slovak Literature Foundation for Scientific Literature (2002, 2004). He has supervised 11 PhD dissertations and one habilitation, demonstrating his commitment to academic mentorship.

• Behavioural economics
• Experimental economics

Dr. Michael Thaler is a Lecturer in Economics at the Department of Economics, University College London (UCL). He holds a PhD in Business Economics from Harvard University (2020) and served as a Postdoctoral Research Associate at Princeton University's Department of Economics (2020–2022). His research focuses on behavioural economics and experimental economics , addressing topics such as motivated reasoning, gender bias in AI, and polarization in public health contexts. His work aligns with UN Sustainable Development Goals 3 (Good Health and Well-Being) and 10 (Reduced Inequalities). Key research contributions include studies on overinference in decision-making, the impact of fake news on trust, and gender differences in motivated reasoning. He developed the 'Jobfair' framework to benchmark gender bias in hiring algorithms. His earlier work also includes combinatorial geometry research, such as tribone tilings of triangular regions. Dr. Thaler has been affiliated with UCL since 2022 and maintains active research collaborations in behavioral science and experimental methodologies. No scientific awards are listed in the provided text.

• Online Information Processing
• Health Literacy
• Effective Communication
• +3 more

Dr. Corine Meppelink is an Assistant Professor of Persuasive Communication at the University of Amsterdam's Faculty of Social and Behavioural Sciences. Her research focuses on online information processing, health literacy, and digital inequalities, with a particular emphasis on how individuals interact with health and political information in digital environments. She holds a position at the Department of Communication Science and is affiliated with the Persuasive Communication Area. Her work bridges communication theory, computational methods, and applied health communication, addressing challenges in misinformation, algorithmic persuasion, and data donation ethics. Research Interests: Dr. Meppelink examines how literacy levels, digital skills, and cognitive processes influence online information seeking and processing. Key themes include the impact of health literacy on medical decision-making, the role of political attitudes in search behavior, and the design of effective digital health communication strategies. Her studies often employ mixed methodologies, including eye-tracking, computational social science, and experimental designs. Her recent work explores algorithmic personalization effects on political searches, the mental health implications of health communication, and the efficacy of warning tools against vaccination misinformation. She collaborates with interdisciplinary teams to address societal challenges in digital health literacy and algorithmic transparency. No scientific awards are explicitly listed, but her contributions are recognized through active peer-reviewed publications and academic engagements. Advising and Grants: While specific grant details are not provided, her publications suggest involvement in funded research projects on health communication and digital media. No formal advisee names are listed here, but her role as an Assistant Professor likely involves graduate supervision.

Nguyen TruongView profile

Lecturer

• Data Privacy
• Security
• Trust
• +4 more

Dr. Nguyen Truong is a Lecturer in Cybersecurity at the School of Computing Science, University of Glasgow, UK. Previously, he held a Research Associate position at the Data Science Institute, Imperial College London (2018–2022). He earned his PhD, MSc, and BSc from Liverpool John Moores University (2018), Pohang University of Science and Technology (2013), and Hanoi University of Science and Technology (2008), respectively. Before academia, he worked as a Software Engineer at DASAN Networks (2012–2015). His research focuses on Data Privacy, Security, Trust, Personal Data Management, Distributed Systems, Blockchain, and Privacy in Federated Learning. Notable contributions include GDPR-compliance frameworks using blockchain and defeasible logic reasoning, as well as surveys on Ethereum pseudonymity and federated learning privacy. Teaching responsibilities include COMPSCI5079 Cryptography and Secure Development, COMPSCI4062/5063 Cyber Security Fundamentals, and COMPSCI5110 Emerging Topics in Cyber Security. He advises PhD student Omodolapo Victor Babalola on Robust Privacy-Preserving Federated Learning for securing IoT. His work spans over 25 peer-reviewed publications, including articles in IEEE Transactions and Elsevier journals. Key themes include blockchain-based trust systems, privacy preservation in distributed environments, and trust evaluation mechanisms in IoT and smart city applications.

Baoze WeiView profile

Associate Professor

• Microgrid Control
• Power Electronics
• Renewable Energy Integration
• +5 more

Baoze Wei is an Associate Professor at Aalborg University's Department of Electric Power Systems and Microgrids, part of the Faculty of Engineering and Science. His research focuses on advanced control strategies for power electronics, microgrid stability, and energy management systems. He leads and collaborates on projects such as the Digital Twin-based Reliability Framework for Aviation Systems and Holistic Optimization of Green Fuel-Powered Microgrids. Key contributions include work on distributed energy systems, fault-tolerant architectures, and predictive maintenance for power electronics. His research emphasizes practical applications in renewable integration, smart grids, and industrial electrification. Wei has supervised one PhD student, Q. He, and contributed to projects funded by entities like Horizon JU and Huawei. Notable collaborations include work on hybrid-electric aircraft systems (HECATE) and advanced control algorithms for distributed converters. His research spans technical areas such as voltage source inverters, uninterruptible power systems (UPS), and DC shipboard microgrids. His publications reflect expertise in model predictive control, energy trading strategies, and condition monitoring. Current research trends include data-driven lifetime prediction for power electronics components and optimization of multi-energy systems. He actively participates in international conferences, contributing to both theoretical advancements and real-world system implementations.

Jörg-Martin RiesView profile

Associate Professor

• Supply Chain Management
• Operations Management
• Technology Management
• +4 more

Jörg-Martin Ries is an Associate Professor (Reader) in Operations Management at Bayes Business School, part of City, University of London. He is affiliated with the Digital Leadership Research Centre at Bayes and the Data Science Institute at City, University of London. His research focuses on applying business analytics to study supply chain performance, digital technologies, and sustainable inventory management. He holds a PhD from the Technical University of Darmstadt (Germany) and has industry experience as a supply chain consultant in automotive, chemical, and industrial construction sectors. Education : Dr. rer. pol. (PhD) in Operations Management, Technical University of Darmstadt, Germany Research Interests : Structural and organizational conditions for innovation in supply networks Role of Industry 4.0 technologies in smart supply chains Process optimization via supply chain finance mechanisms Sustainable inventory management and environmental impact analysis His work bridges theoretical research with practical applications, collaborating with industry partners on projects like digital supply chain governance and financial collaboration models. Professional Contributions : 2 nd supervisor to research student Fabienne Chedid Lead researcher on industry projects involving business analytics applications Advisory work for companies in process manufacturing and transportation sectors Labs/Teams : Active member of the Digital Leadership Research Centre and Data Science Institute at City, University of London.