جست‌وجوی استاد و پژوهشگر

• Operations Research
• Supply Chain Management
• Humanitarian Logistics
• +۳ مورد دیگر

Prof. Dick den Hertog is a Full Professor at Tilburg University's Department of Econometrics and Operations Research, part of the Tilburg School of Economics and Management (TiSEM). His research focuses on operations research methodologies with applications in humanitarian logistics, supply chain optimization, and robust decision-making under uncertainty. He collaborates with organizations like the UN World Food Programme to enhance operational efficiency in complex environments. Key research areas include robust optimization techniques, supply chain management in developing regions, and the integration of satellite data with machine learning for infrastructure analysis. His work addresses challenges such as food aid distribution, disaster response logistics, and predictive modeling for transportation systems in data-scarce areas. Notable projects include developing analytical tools for the WFP's supply chain planning and creating algorithms for weather-informed road speed prediction. He is affiliated with the Tilburg Sustainability Center and the Operations Research research group, contributing to both academic advancements and real-world impact through optimization solutions.

Frank Willemsمشاهده پروفایل

استاد

• Control Systems
• Automotive Engineering
• Powertrain Control
• +۵ مورد دیگر

Frank Willems is a Full Professor of Systems and Control Technology and Chair of Integrated Powertrain Control at Eindhoven University of Technology (TU/e), holding a part-time position realized with support from TNO. He is affiliated with the Control Systems Technology group within the Department of Mechanical Engineering, and also contributes to EIRES and EAISI research initiatives. Dr. Willems obtained his MSc (1995) and PhD (2000) in Mechanical Engineering from Eindhoven University of Technology (TU/e). His academic journey continued with a position at TNO Automotive, where he currently serves as a principal scientist in powertrain control. Professor Willems' research focuses on developing optimal and robust control methods for automotive powertrain systems. His work addresses the critical challenge of integrating energy and emission management strategies at the powertrain system level, which is essential as traditional methods become infeasible due to increasingly strict environmental regulations. Key research areas include control-oriented modeling of internal combustion engines, cylinder pressure-based combustion control, and integrated energy and emission management. His research aims to minimize development time and costs through model-based control methods, with the ultimate goal of achieving auto-calibration where powertrain energy efficiency is optimized online using smart sensors and route information. Dr. Willems serves as an Associate Editor for Control Engineering Practice and is an active member of the IFAC Technical Committee Automotive Control. He has participated in numerous international program committees for conferences including the IFAC Conference on 'Engine and Powertrain Control, Simulation and Modeling (E-CoSM)', IFAC Symposium 'Advances in Automotive Control (AAC)', and 'Symposium for Combustion Control (SCC)'. His research has been supported by organizations including the Dutch Technology Foundation (STW) and DENSO Japan. At TU/e, Professor Willems teaches courses on 'Optimal control and reinforcement learning' and 'Advanced control for future heavy-duty powertrains.' His research group, part of the Control Systems Technology group, focuses on developing self-learning powertrain control systems to address the complexity and diversity of future ultra-clean and efficient vehicles.

Sofie Haesaertمشاهده پروفایل

استادیار

• Cyber-Physical Systems
• Control Theory
• Formal Verification
• +۳ مورد دیگر

Sofie Haesaert is an Assistant Professor in the Control Systems group at the Department of Electrical Engineering, Eindhoven University of Technology. Her work focuses on formal verification and control synthesis methods for cyber-physical systems, particularly through stochastic simulation relations and temporal logic specifications. Education: BSc (cum laude) and MSc (cum laude) in Mechanical Engineering and Systems & Control from Delft University of Technology; PhD from Eindhoven University of Technology (2017) Experience: Postdoctoral researcher at Caltech (2017-2018), then returned to TU/e as Assistant Professor Her research interests include: Cyber-physical systems verification Stochastic control methods Temporal logic specification Markov decision processes Formal methods in control engineering Model abstractions and simulation relations Recent publications show strong focus on: Stochastic temporal logic control Robust and risk-aware control Multi-agent system verification Formal synthesis via simulation relations AI integration in control systems Software tools for formal control Scientific achievements: Veni Grant recipient (2020) Co-developer of the SySCoRe toolset for stochastic control synthesis Contributor to formal verification benchmarks through ARCH-COMP reports She contributes to education through courses on: Control principles for engineered systems Control challenges in autonomous racing Supervisory control of cyber-physical systems Haesaert collaborates across disciplines including computer science, applied mathematics, and robotics, with over 750 citations and significant contributions to formal control theory for stochastic systems. Her work bridges theoretical developments with practical applications in autonomous systems and complex control architectures.

Tom Bootمشاهده پروفایل

دانشیار

• Macroeconomic Forecasting
• High-Dimensional Data Analysis
• Econometric Theory
• +۴ مورد دیگر

Dr. Tom Boot is an Associate Professor at the Department of Economics, Econometrics & Finance at the University of Groningen. He holds a PhD in Econometrics from Erasmus University Rotterdam (2017) and an MSc in Econometrics from the same institution (2012), along with an MSc in Physics from the University of Groningen (2010). His research focuses on econometric theory applied to macroeconomic forecasting, high-dimensional data analysis, and causal inference. He has been recognized with the Veni grant (2021–2024) for his work on forecasting methodologies. Boot’s research interests include improving forecast accuracy through methods like subspace projections, structural break modeling, and privacy-aware marketing analytics. His recent work explores privacy-utility trade-offs in data-driven marketing and unbiased estimation techniques for clustered errors. He has supervised PhD students including Jhordano Aguilar Loyo and Gilian Ponte, whose theses addressed panel data heterogeneity and differential privacy applications. Boot is also a program director for the MSc Econometrics, Operations Research, and Actuarial Studies (since 2024). His contributions to econometrics span over a dozen peer-reviewed publications, with a focus on advanced statistical techniques for economic forecasting and policy analysis. Collaborations include work with institutions like Harvard/MIT and the organization of workshops on causal inference and machine learning.

Ralf Peetersمشاهده پروفایل

استاد

• Signal and Image Processing
• Systems and Control Theory
• Mathematical Modelling
• +۷ مورد دیگر

Ralf Peeters is a Full Professor in Mathematics of Knowledge Engineering at Maastricht University's Faculty of Science and Engineering , Department of Advanced Computing Sciences. He serves as Vice-Dean of Research and Director of the STEM Graduate School, while leading the university's team at the inter-university research school DISC and co-chairing the Mathematics Centre Maastricht. Education: PhD in Mathematics (Free University, Amsterdam, 1994) Technical Mathematics (Delft University of Technology, 1988) Research Interests span applied mathematics, systems and control theory, signal/image processing, artificial intelligence, and biomedical engineering applications. His work bridges mathematical techniques with real-world challenges in healthcare and industrial systems. Recent Publications highlight advancements in deep learning for cardiac signal reconstruction, tensor-based signal decomposition, and recurrence plot analysis. These works integrate machine learning with clinical diagnostics, particularly in electrocardiographic imaging and arrhythmia characterization. Key Collaborations: Mathematics Centre Maastricht Dutch Mathematics Platform Dutch Institute of Systems and Control Leadership Roles: Vice-Dean of Research (FSE), Director of STEM Graduate School, Head of DISC-affiliated team, and Co-Chair of Mathematics Centre Maastricht. He has supervised over 25 PhD projects, emphasizing applied research across health and industrial domains.

Anuj Pathaniaمشاهده پروفایل

استادیار

• Low Power Design
• Sustainable Systems
• Electronic Design Automation
• +۴ مورد دیگر

Anuj Pathania serves as an Assistant Professor in the Parallel Computing Systems (PCS) group within the Informatics Institute at the University of Amsterdam's Faculty of Science. His research pioneers sustainable computing systems operating under severe power, thermal, and reliability constraints, with significant contributions to energy-efficient hardware design and embedded systems. Education: PhD in Computer Science (2018), Karlsruhe Institute of Technology MSc in Computer Science (2012), National University of Singapore B.Tech in Computer Science (2009), Maharaja Agrasen Institute of Technology Pathania's research centers on low-power design and sustainable systems for constrained environments, with particular expertise in thermal management of 3D-stacked architectures and energy-efficient machine learning inference . His work bridges electronic design automation with real-world reliability challenges, developing novel power budgeting techniques like T-TSP that incorporate transient temperature effects ignored by conventional methods. Current projects include EU-funded initiatives on energy labeling for digital services, addressing ecological impacts through technological, behavioral, and legal frameworks. His publication trajectory reveals a strategic evolution toward zero-waste computing , with recent work (2023-2025) focusing on hardware-software co-design for edge AI, energy modeling across computing continua, and parameter-efficient neural adaptation. Key themes include thermal-aware scheduling for S-NUCA many-cores, cooperative processor utilization in heterogeneous systems, and sustainability metrics for digital services. Scientific Recognition: Best Paper Award Nomination at IEEE Computer Society Annual Symposium on VLSI 2023 for 3D-TTP power budgeting technique Pathania actively mentors 4 PhD students (Ehsan Aghapour, Saeedeh Baneshi, Sudam Wasala, Yixian Shen) and has successfully supervised 5 Master's theses (including Cum Laude defenses by Joris op ten Berg and Jurre Wolff). His research is supported by major grants including Energy Labels for Ecologically Sustainable Digital Services (2023-2024) and Towards Zero-Waste Computing (2021-2025), developing simulation frameworks like HotSniper and CoMeT for thermal analysis. The PCS group maintains strong industry collaborations with ARM and NVIDIA, particularly through tools like ARM-CO-UP for heterogeneous processor utilization.

• Artificial Intelligence
• Mobility and Transport
• Traffic (road)
• +۱۳ مورد دیگر

Eric C. van Berkum is a Full Professor at the Digital Society Institute and Transport Engineering and Management. His research spans Artificial Intelligence, Mobility and Transport, and Intelligent Transport Systems, with a focus on optimizing traffic networks, public transport efficiency, and railway maintenance scheduling. He contributes to UN Sustainable Development Goals (SDGs) related to environmental resilience and social safety in transport systems. Expertise in Equilibrium Traffic Models and Stochastic Modelling Active in Data Mining, Machine Learning, and Network Analysis Key themes: Dynamic Traffic Management, Infrastructure Optimization, and Passenger Behavior His recent work addresses railway maintenance scheduling, shared demand-responsive transit, and passenger rerouting in capacitated systems. He has received a Best Paper Award (2017) and served on editorial boards, including Tijdschrift vervoerswetenschap (2014–2017). He organized the E-COST Summer School on Autonomous Road Transport Systems (2014) and contributed to IEEE conferences as a program committee member.

• Operations Management
• Retail Operations
• Marketing-Operations Interface
• +۹ مورد دیگر

Robert Rooderkerk is Associate Professor of Operations Management at the Rotterdam School of Management, Erasmus University Rotterdam, where he is affiliated with the Department of Technology and Operations Management. His research sits at the intersection of marketing and operations, focusing on omnichannel retail, assortment optimization, and fulfillment strategies. He teaches courses on retail operations, empirical research methods, and consumer decision making across undergraduate, MBA, and PhD programs. Research Interests: His research combines empirical and conceptual approaches to understand how data analytics, consumer behavior, and new technologies are transforming retail. He investigates topics such as product line design, dynamic assortment personalization, and the impact of fulfillment failures on customer loyalty. His work integrates methods from econometrics, operations research, and psychology. Publication Trends: His recent publications span journals in marketing, operations, and management, reflecting the interdisciplinary nature of his work. Key themes include the adoption of retail analytics, omnichannel integration, and behavioral aspects of retail operations. There is a strong emphasis on practical relevance and industry applicability. Dutch Marketing Science Award Paul Green Award Finalist, Journal of Marketing Research Advising and Grants: While no direct list of students is provided, he supervises bachelor theses and contributes to PhD training through the ERIM Master of Philosophy program. He has served as coordinator of the Research Training and Bachelor Thesis course. His research has been supported through academic collaborations and has had significant media coverage, indicating public and industry impact. Labs and Teams: He is actively involved in the Marketing-Operations Interface research group at RSM and collaborates with scholars globally. His work contributes to the UN Sustainable Development Goals, particularly through innovations in sustainable retail practices and responsible consumption.

Ashish Cherukuriمشاهده پروفایل

دانشیار

• Optimization
• Control Systems
• Multi-agent Systems
• +۷ مورد دیگر

Ashish Cherukuri is an Associate Professor at the University of Groningen's Faculty of Science and Engineering, affiliated with the Optimization and Decision Systems group. His research focuses on optimization-based control, game theory, and multi-agent systems applied to energy, transportation, and robotics. He holds a Ph.D. from UC San Diego and postdoctoral experience at ETH Zurich. Education: Ph.D., University of California, San Diego (2012–2017) M.Sc., ETH Zurich (2008–2010) B.Tech, Indian Institute of Technology Delhi (2004–2008) Research Interests: Data-driven optimization, distributed algorithms, networked cyber-physical systems, and uncertainty handling in energy and transportation systems. Recent work emphasizes stochastic optimization, game-theoretic routing, and risk-aware control. Awards: Robert E. Skelton Dissertation Award (2017) Outstanding Graduate Student Award (2016) Focht-Powell Fellowship (2012–2015) Grants & Service: Editor for the IEEE Control Systems Society, organizer of Energy-Open 2019, and member of professional societies (IEEE, INFORMS, SIAM). Active in conference organization and academic leadership roles. Labs/Teams: Part of the Jan C. Willems Center for Systems and Control and the Engineering and Technology Institute Groningen (ENTEG). Research integrates theoretical advancements with practical applications in energy networks and smart systems.

• machine learning
• robotics
• machine vision
• +۹ مورد دیگر

Dr. Hamidreza Mohades Kasaei is an Associate Professor in the Department of Artificial Intelligence at the University of Groningen, Netherlands. He holds positions in both the Faculty of Science and Engineering and the Faculty of Medical Sciences/UMCG, focusing on Robotics and image-guided minimally-invasive surgery. His work bridges theoretical advances in machine learning with practical robotic applications. Dr. Kasaei's research focuses on developing algorithms for adaptive perception systems through interactive environment exploration and open-ended learning. His specific interests include 3D object perception, grasp affordance detection, object manipulation, and active perception. He has evaluated his research on various robotic platforms including PR2, UR5e, Kinova, Franka robotic arms, and humanoid robots. His work enables robots to learn from past experiences and intelligently interact with non-expert human users using data-efficient techniques. Analysis of his recent publications reveals strong trends toward increasingly sophisticated manipulation capabilities, particularly in dual-arm coordination and handling dense clutter. There's a clear progression toward integrating language models with robotic control systems, as seen in works like 'Lifelong Robot Library Learning' and 'Towards Open-World Grasping with Large Vision-Language Models.' His research consistently addresses real-world challenges in agricultural robotics, assistive technologies, and service robotics applications. Gratama Science Award (2022) Google Research Scholar Award in Machine Learning (2023) Outstanding Associate Editor for IEEE Robotics and Automation Letters (2023) Dr. Kasaei has successfully supervised multiple PhD students including Zhenxing Zhang (thesis on 'Generative Adversarial Networks for Diverse and Explainable Text-to-Image Generation') and Hamed Ayoobi (thesis on 'Explain What You See: Argumentation-Based Learning and Robotic Vision'). His research is supported by significant grants including the Google Research Scholar Award for 'Continual Robot Learning in Human-centered Environments' and various conference organization roles including workshops at RSS 2023 and NeurIPS 2022. He leads the Lifelong Interactive Robot Learning Lab (IRL-Lab), which focuses on six key research directions: Perception and Perceptual Learning, Object Grasping and Manipulation, Lifelong Interactive Robot Learning, Dual-Arm Manipulation, Dynamic Robot Motion Planning, and Exploiting Multimodality. The lab develops cutting-edge approaches for robots to learn in open-ended fashion through interaction with non-expert human users, with applications in assistive robotics for people with disabilities.

Adriana Iamnitchiمشاهده پروفایل

استاد

• Computational Social Science
• Social Media Analysis
• Misinformation Detection
• +۳ مورد دیگر

Adriana Iamnitchi is a Full Professor and Key Domain Chair for Computational Science at Maastricht University's Faculty of Science and Engineering, affiliated with the Department of Advanced Computing Sciences. Her research focuses on computational social science, social media dynamics, and misinformation detection. Her primary research interests include: Analysis of coordinated information campaigns across social platforms Development of LLM-based synthetic data generation for social media research Polarization quantification in multi-community networks Policy compliance frameworks for digital regulation (e.g., EU's Digital Services Act) Ethical AI applications for content moderation and transparency Her recent publications (2023-2025) demonstrate strong focus on: Cross-platform disinformation detection using multimodal embeddings Generative AI for synthetic social media datasets Quantitative analysis of toxicity monetization in creator economies Regulatory compliance automation for content transparency

Anna Wilbikمشاهده پروفایل

استاد

• Data Fusion
• Intelligent Interaction
• Fuzzy Logic
• +۴ مورد دیگر

Anna Wilbik is a Professor in Data Fusion and Intelligent Interaction at the Department of Advanced Computing Sciences, Faculty of Science and Engineering, Maastricht University (The Netherlands). Her research bridges data understanding and human-machine synergy in complex systems, focusing on multi-criteria decision making, explainable AI, and data fusion techniques. PhD in Computer Science (with honors), Systems Research Institute, Polish Academy of Science (2010) Postdoctoral Fellow, University of Missouri (2011) Stanford University TOP500 Innovators Program Alumnus Research Pillars: Intelligent human-machine interaction for joint decision making Data fusion methods for heterogeneous data integration Contextualized multi-criteria decision frameworks Fuzzy logic and linguistic summaries for explainability Federated learning systems Article Trends: Recent work focuses on intuitionistic fuzzy sets for knowledge-intensive processes, federated learning with uncertainty handling, and linguistic summarization techniques for interpretable AI. She actively explores explainability , collaborative business models , and driver behavior analysis through attention-based models. Professional Leadership: Vice-chair of IEEE Fuzzy Systems Technical Committee Organizer of IEEE World Congress on Computational Intelligence (2024)

• Agricultural Engineering
• Robotics
• Computer Science
• +۱۲ مورد دیگر

Ard Nieuwenhuizen is a Researcher at Wageningen University & Research in the Agro Field Technology Innovations department. His expertise spans Agricultural Engineering , Robotics , and Machine Learning , focusing on AI-driven solutions for crop management and harvesting automation. Agro Field Technology Innovations, Wageningen University & Research Research Interests Robotics and intelligent systems for agricultural operations Digital twin technology and precision agriculture Computer vision for weed and crop detection Human-robot collaboration in farming Machine learning for agricultural automation Publication Trends : His recent work emphasizes agricultural robotics , digital twins , and AI-driven crop monitoring , with applications in apple/pear harvesting, soybean weed detection, and spray optimization. Articles highlight collaborations with European institutions and contributions to journals like Smart Agricultural Technology . Projects : He leads initiatives such as Smart Autonomy for Precision Agriculture (SMP25029) and Redesigning future food production systems through AI and robotics (KB-53-000-010), focusing on integrating robotics and data science into sustainable farming practices.

Raymond H. Cuijpersمشاهده پروفایل

دانشیار

• Cognitive Robotics
• Human-Robot Interaction
• Socially Assistive Robotics
• +۵ مورد دیگر

Raymond H. Cuijpers is an Associate Professor at Eindhoven University of Technology in the Human Technology Interaction group. His research focuses on Cognitive Robotics , Human-Robot Interaction , and Artificial Intelligence for cognitive agents, with applications in healthcare robotics and aging population support. PhD in Physics of Man from Utrecht University (2000) Postdoctoral research at Erasmus MC Rotterdam and Radboud University Nijmegen Key research areas include: Developing socially intelligent robots with proper social cue interpretation Hybrid AI approaches for real-world complexity handling Visual-haptic perception integration in human motor control Service robots for COPD patient assistance (KSERA project) Rescue robotics and tele-operation applications Recent research output (2025) includes studies on: Personalization in human-robot communication Optimal lighting for elderly visual perception Human-robot bonding mechanisms Interactive sensorized platforms for homecare (GUARDIAN) Audiovisual temporal integration in virtual environments He coordinates large-scale European projects like GUARDIAN and previously KSERA, contributes to sustainable development goals through healthcare robotics, and serves on editorial boards of leading journals including International Journal of Social Robotics . His work spans both technical robotics development and human-centric interaction studies.

• Agent-Based Modelling
• Computational Social Science
• Natural Language Processing (NLP)
• +۳ مورد دیگر

Dr. Sjoukje Osinga is an Assistant Professor in the Information Technology group at Wageningen University's Department of Social Sciences. Her research focuses on computational social science, natural language processing (NLP), and big data applications in agriculture. She holds a PhD from Wageningen University on agent-based modelling of knowledge management in the pig sector, with fieldwork in China. She contributed to EU H2020 projects like Cybele (big data in agriculture) and Dragon (knowledge transfer of ABM tools). She is a member of the SiLiCo Centre, specializing in simulating complex systems through agent-based simulations. Education: Artificial Intelligence and Cognitive Science (Groningen and Leuven, 1991) Research interests include agent-based modelling, big data analytics for agriculture, machine learning, and knowledge management. She explores topics like digital twins in health and agriculture, and sentiment analysis in policy-making. Her work bridges technical innovation with societal challenges, such as sustainable farming practices and compliance strategies in regulatory environments. Publications span agent-based models for pork supply chains, machine learning applications in crop forecasting, and digital twin frameworks for agriculture. She actively engages in interdisciplinary projects addressing data integration and policy implications of emerging technologies.