جستجوی استاد راهنمای دانشگاهی

Bert de Vries is a Professor at the Signal Processing Systems Group at Eindhoven University of Technology (TU/e), where he has been employed since January 2012. He maintains a dual career, also working at GN Hearing in the hearing aids industry since April 1999, where he holds both research and managerial roles. His academic journey began at TU/e, where he earned his MSc in Electrical Engineering in 1986, followed by a PhD from the University of Florida in 1991. Between 1992 and 1999, he worked at Sarnoff Research Center in Princeton, NJ, contributing to diverse signal and image processing projects. Professor de Vries's research centers on Bayesian Machine Learning, with particular focus on the Free Energy Principle and its applications to engineering problems. His work bridges theoretical neuroscience with practical signal processing systems, especially in biomedical applications. He directs the BIASlab research team at TU/e, which develops probabilistic programming tools including RxInfer.jl, ForneyLab.jl, GraphPPL.jl, ReactiveMP.jl, and Rocket.jl. His research spans active inference, variational message passing, probabilistic programming, and Bayesian neural networks, with applications ranging from hearing aids to multi-agent systems. Analysis of his recent publications reveals a strong trend toward practical implementations of Bayesian inference frameworks, particularly through Julia-based probabilistic programming tools. His work shows increasing focus on active inference applications, message passing algorithms, and the intersection of Riemannian geometry with probabilistic modeling. The research demonstrates consistent progression from theoretical foundations toward real-world engineering applications, particularly in biomedical signal processing and autonomous systems. Professor de Vries teaches a graduate-level course on Bayesian Machine Learning at TU/e and actively contributes to open-source software development through his GitHub profile (bertdv), with recent activity as recent as August 2025. His research team has developed several influential probabilistic programming libraries that have gained significant attention in the machine learning community. The BIASlab research group continues to advance the state of the art in Bayesian inference methods with applications in hearing technology, robotics, and signal processing.

• Bayesian Machine Learning
• Signal Processing
• Biomedical Applications
• +۳ مورد دیگر

Jeroen van den Hoven is a Professor at the Faculty of Technology, Policy and Management at Delft University of Technology . He serves as Editor in Chief of Ethics and Information Technology (Springer) and Founding Chair of the CEPE conference . His affiliations include advisory roles in the EU Commissioner Reding's ICT group , grants from the Dutch Research Council , and collaborations with industry leaders like SUN, IBM, and Getronics . Research Interests Van den Hoven's work bridges ethics, artificial intelligence, and public policy . He focuses on value-sensitive design , responsible innovation , and moral philosophy applied to emerging technologies. His research addresses AI governance , privacy , and ethical frameworks for autonomous systems , with applications in healthcare, military technology, and smart cities . Scientific Contributions His recent publications explore trust in foundation models , transparency in AI , and human control over autonomous systems . Themes include epistemic dependence in healthcare AI , democratic integrity in digital eras , and ethical guidelines for military applications . Awards & Grants Recipient of multiple Dutch Research Council grants , he advocates for ethical design principles and chairs international conferences on computer ethics . His advisory roles span Dutch government commissions and EU ICT policies .

• Ethics of AI
• Responsible Innovation
• Value-Sensitive Design
• +۱۱ مورد دیگر

Maria Birna van Riemsdijk is an Associate Professor in Intimate Computing at the University of Twente, Netherlands. Her research focuses on developing technologies that address human vulnerability in daily life through intimate computing , blending ethics with AI and robotics. She leads the Human-Media Interaction group and contributes to the Digital Society Institute. Awards: Vidi personal grant Dutch Prize for Research in ICT 2014 2020 IEEE Computer best paper award Leadership Roles: Editorial board member, Journal of Autonomous Agents and Multiagent Systems Board member, 4TU.NIRICT (ICT research consortium) Former board member, IFAAMAS (2012-2018) Her research bridges Artificial Intelligence , Human-AI Interaction , and Healthcare , emphasizing responsible design. Recent work explores conversational agents for behavior support, ethical frameworks, and AI in healthcare contexts. Key article themes include responsible computing , conversational strategies , and adaptable AI frameworks . She has contributed to 26 total research outputs and datasets in human-agent alignment and social situation modeling.

• Artificial Intelligence
• Autonomous Agent Systems
• Human-AI Interaction
• +۷ مورد دیگر

Viola Schiaffonati serves as Associate Professor of Logic and Philosophy of Science at Politecnico di Milano's Department of Electronics, Information and Bioengineering. She holds pivotal leadership roles including Director of the CINI National Laboratory on Informatics & Society (IeS) and founding member of Polimi META, the university's social sciences and humanities unit for science and technology. Additionally, she acts as Associate Editor for Science and Engineering Ethics and represented Informatics Europe in the European Commission Expert Group on AI and data in education. Education: PhD in Philosophy of Science, Università di Genova Visiting Scholar, Department of Philosophy, University of California, Berkeley Visiting Researcher, Suppes Center for Science and Technology Studies, Stanford University Her research critically examines the philosophical foundations of artificial intelligence and robotics, with specialized focus on experimental epistemology in computer engineering and ethical frameworks for autonomous systems. This interdisciplinary work bridges philosophy, engineering, and social sciences to address societal impacts of emerging technologies, emphasizing methodological rigor in robotics experimentation and ethical governance of intelligent systems. Scientific Awards: No awards explicitly mentioned in source text. While specific advisees aren't documented, her laboratory directorship and editorial role indicate active research mentorship. Her European Commission involvement demonstrates policy-level contributions to AI ethics in educational contexts, though grant details remain unspecified in available materials. She spearheads the CINI National Laboratory on Informatics & Society (IeS), analyzing technology-society interactions, and co-founded Polimi META to integrate humanities perspectives into technical research. These initiatives position her at the forefront of interdisciplinary studies examining how AI and robotics reshape social structures and ethical norms.

• Philosophy of Artificial Intelligence
• Ethics of Artificial Intelligence
• Philosophy of Robotics
• +۳ مورد دیگر

Prof. dr. Lambert Schomaker is a Full Professor of Artificial Intelligence at the University of Groningen, leading the Artificial Intelligence and Cognitive Engineering (ALICE) institute within the Faculty of Science and Engineering. His work spans perceptual intelligence, machine learning, and neuromorphic computing, with significant contributions to handwriting recognition, robotics, and historical document analysis. Affiliations: Bernoulli Institute, CogniGron (Cognitive Systems & Materials), and Data Science & Systems Complexity (DSSC) centers. Education: M.Sc. (1983) and Ph.D. (1991) in Psychophysiology/Psychology from Nijmegen University. Research Interests: AI, pattern recognition, neural networks, autonomous systems, and applications in cultural heritage (e.g., the MONK system for handwritten archive indexing). He has pioneered handwriting recognition methods used in modern devices like tablets and led the 30MEuro Target project for large-scale data mining. Grants & Projects: Includes NWO-funded initiatives (e.g., Catch, TriGraph) and EU projects (MANTIS, MANIC). Current focus areas include neuromorphic computing with electronic materials and AI-driven analysis of the Dead Sea Scrolls. Awards: IBM Faculty Awards (2011, 2012), IAPR Best Paper Award (2012), Ching Yee Suen Special Award (2012). Advising: Supervised over 20 PhD students in AI, robotics, and document analysis. Active in industry collaborations (e.g., HP, Microsoft). Labs/Teams: Director of ALICE, contributor to CogniGron, and leader of the MONK system team. Current research includes neuromorphic hardware development and AI applications in maintenance systems.

• Artificial Intelligence
• Pattern Recognition
• Machine Learning
• +۶ مورد دیگر

Kerstin Bunte is a Professor of Machine Learning for interdisciplinary data analysis at the University of Groningen, affiliated with the Faculty of Science and Engineering and the Bernoulli Institute's Intelligent Systems Group. She holds an Honorary Fellowship at the University of Birmingham and leads the Intelligent Systems Group. Her research focuses on interpretable machine learning, interdisciplinary applications (e.g., astrophysics and biomedical data), and visualization techniques. Research Interests: - Machine Learning - Artificial Intelligence - Explainable AI (XAI) - Interpretable Models - Dimensionality Reduction - Data Visualization - Astrophysical Data Analysis - Medical Imaging Awards & Grants: - DSSC XS funding (2023) - NWO VIDI grant (2020) - Rosalind Franklin Fellowship (2016–present) Advising & Students: Supervised PhD students include Elisa Oostwal, Janis Norden, Matteo Marcantoni, and Petra Awad. Research spans topics like tumor segmentation in medical imaging, astrophysical structure detection, and autonomous navigation systems. Labs & Collaborations: Leads the Intelligent Systems Group, collaborating with institutions like the University of Birmingham and the University of Warwick. Work involves interdisciplinary projects combining machine learning with astronomy, biomedical sciences, and robotics.

• Machine Learning
• Artificial Intelligence
• XAI (Explainable Artificial Intelligence)
• +۷ مورد دیگر

Dr. Matias Valdenegro Toro is an Assistant Professor of Machine Learning at the University of Groningen within the Faculty of Science and Engineering and the Artificial Intelligence department of the Bernoulli Institute. He holds a PhD from Heriot-Watt University (2019) and a Master's in Autonomous Systems from Bonn-Rhein-Sieg University of Applied Sciences (2014). His research focuses on trustworthy machine learning models , particularly in uncertainty quantification , medical AI , and robotics , with applications in computer vision and explainable AI. He teaches courses like Introduction to Machine Learning and Deep Learning at the Bachelor and Master levels. His work emphasizes robustness in AI systems, including uncertainty estimation for medical applications, super-resolution techniques, and neuromorphic robotics. He has published widely on topics like Bayesian neural networks, prompt tuning, and sanity checks for explanations. Notable awards include Best Reviewer at ICML (2024) and Highlighted Reviewer at ICLR (2022). He collaborates with institutions like the German Research Center for Artificial Intelligence and actively contributes to open-source datasets (e.g., the Japanese Uncertain Scenes Dataset ). Key grants and activities include organizing the ENLIGHT BIP Course on Deep Learning for Forestry and teaching at the European Summer School on AI . His research also addresses regulatory challenges like the EU AI Act's implications for uncertainty quantification in general-purpose AI.

• Machine Learning
• Neural Networks
• Uncertainty Quantification
• +۴ مورد دیگر

Prof. D. (David) Lentink is a Full Professor of Biomimetics at the University of Groningen, Faculty of Science and Engineering. His research focuses on understanding biological flight mechanics, particularly in birds, to inspire advanced robotics and aerospace innovations. He holds a PhD in Experimental Zoology (cum laude, Wageningen University, 2008) and dual MS/BS degrees in Aerospace Engineering (Delft University of Technology, 2003). Lentink leads the Biomimetics Group, pioneering projects like rudderless flight and morphing-wing drones. His work bridges biomechanics, robotics, and aerodynamics, with notable contributions to aerial grasping systems and biomimetic materials. Education: PhD cum laude, Experimental Zoology, Wageningen University (2008) MS/BS, Aerospace Engineering, Delft University of Technology (2003) Research Interests: Biomimetics, bio-inspired design, animal flight biomechanics, aerodynamics of flight, and aerial robotics. His lab develops cutting-edge tools like the Aerodynamic Force Platform to measure in vivo forces and advanced wind tunnels for precise flight studies. Awards: 2018 Steven Vogel Young Investigator Award 2017 National Academy of Engineering Gilbreth Lecturer 2013 World Economic Forum Top 40 Scientists Under 40 Grants & Labs: Lentink oversees grants from NSF, Human Frontiers Science Program, and Dutch Academic Year Prize. His lab collaborates globally and maintains ties with Stanford University’s former projects. Current focus includes biomimetic drones for complex environments and understanding turbulence adaptation in birds.

• Biomimetics
• Bio-inspired Design
• Animal Flight
• +۳ مورد دیگر

Javid Jooshesh serves as a Lecturer and Researcher at Amsterdam University of Applied Sciences, affiliated with the Digital Product Research Group and Robot Lab - Digital Production Research Group. His work bridges academic research with industrial applications in sustainable manufacturing. Research focuses on Circular Design, Robotic Fabrication, and Waste Wood Utilization through Industry 4.0 technologies. Key interests include Digital Twins for material optimization, robotic 3D printing protocols, and circular workflows for residual wood in interior design. His fingerprint analysis shows strong specialization in Quality Material Engineering and Robotic Fabrication. Publications (2022-2025) demonstrate consistent innovation in circular wood systems, particularly through API development for design-to-production workflows and robotic stool fabrication using waste wood. Research increasingly integrates Digital Twins with physical production systems. No scientific awards were documented in source materials. Jooshesh contributes to education through the Minor Robotic Production & Circular Materials program and co-organizes industry workshops like the Circular Wood Digital Design Workshop. He actively participates in the Circular Wood 4.0 Consortium, facilitating knowledge transfer between academia and wood industry stakeholders. As core member of HvA's Robot Lab, he develops infrastructure for digital production research. Current initiatives focus on scaling circular wood solutions through the Consortium's industry partnerships and advancing Digital Twin applications in material testing.

• Circular Design
• Robotic Fabrication
• 3D Printing
• +۴ مورد دیگر

Ruisheng Su is an Assistant Professor in the Department of Biomedical Engineering at Eindhoven University of Technology (TU/e), part of the Medical Image Analysis group (IMAG/e). He leads the SWITCH stroke workshop at MICCAI and collaborates with institutions like Erasmus MC, University of Bern, and Philips. His research focuses on deep learning for neurovascular image/video analysis, including applications in stroke, aneurysms, and image-guided interventions. He aims to develop trustworthy AI methodologies for medical professionals. Academic Background: Joined TU/e's IMAG/e group in 2024. Previously, he was a post-doctoral researcher at Erasmus MC’s Biomedical Imaging Group Rotterdam, specializing in AI for endovascular stroke interventions. Before 2020, he worked as a software engineer at ASML and a research scientist at Philips Research. Holds a Master’s in Electrical Engineering from Technical University of Munich (TUM), with thesis work at Philips on patient activity monitoring. Research Highlights: Active in developing AI-based techniques for image registration, segmentation, and quantification in neurovascular diseases. Key projects include CAVE (artery/vein segmentation), AngioMoCo (motion correction), and autoTICI (automatic reperfusion scoring). His work contributes to UN Sustainable Development Goals in health and well-being. Awards: Van Leersum Grant (2022) for visiting Harvard Medical School and DAAD AiNet Fellowship (2023) for collaborations in Berlin/Munich. Teaching: Courses include 'Medical Image Analysis' spanning from 2013 to present and ongoing courses starting 2024.

• Deep Learning
• Medical Image Analysis
• Neurovascular Imaging
• +۴ مورد دیگر

Bahar Haghighat is a Tenure Track Assistant Professor in Robotics and Automation at the Faculty of Science and Engineering, University of Groningen. She leads the Distributed Autonomous Intelligent Systems (DAISY) Lab as Principal Investigator and contributes to academic governance as a Member of the Faculty Council. Her professional affiliations include the Royal Netherlands Institute of Engineers (KIVI), the Institute of Electrical and Electronics Engineers (IEEE), and editorial roles with Nature Portfolio Journal Robotics and Springer Nature Journal Autonomous Robots. Her educational background includes: PhD in Robotics, Control, and Intelligent Systems from the Swiss Federal Institute of Technology in Lausanne (EPFL), Switzerland (2018) Master's degree in Electrical Engineering/Digital Electronics from Sharif University of Technology (SUT), Tehran, Iran Bachelor's degree in Electrical Engineering/Physics (double major) from Sharif University of Technology (SUT), Tehran, Iran Dr. Haghighat's research focuses on building novel miniaturized robotic swarms and algorithmic frameworks for sensing, surveying, and inspection applications. Her work spans mechatronics, electronics, embedded systems, embedded artificial intelligence and machine learning, and distributed systems. She envisions developing surface, aquatic, and aerial miniaturized robot swarms and small-scale intelligent devices for basic research and commercial applications including inspection of complex structures, environmental monitoring, space exploration, and search-and-rescue operations. Her recent publications demonstrate a strong focus on swarm robotics, particularly using particle swarm optimization techniques for multi-robot coordination, surface inspection tasks, and spacecraft hull inspection. Her research shows an interdisciplinary approach combining mechatronic design with advanced algorithms for self-assembly and collective decision-making in resource-constrained robotic systems. Her notable scientific achievements include: EPFL's PhD research award of Gilbert Hausmann for the best PhD thesis in mechanical engineering, electricity, and physics (2019) EPFL distinction of excellence for a PhD thesis in Robotics, Control, and Intelligent Systems (2018) Swiss National Science Foundation Postdoc Mobility Fellowship (2019) Swiss National Science Foundation Early Postdoc Mobility Fellowship (2017) Third place in EPFL's "My Thesis in 180 Seconds" competition (2017) EECS Rising Star recognition (2021 at MIT and 2019 at UIUC) Dr. Haghighat has served as Program Co-Chair for The International Symposium on Distributed Autonomous Robotic Systems (DARS) and has held visiting scholar positions at MIT and Harvard University. Her research has received media attention for applications in Mars rover technology and drone swarms for defect detection. She leads the DAISY Lab, which focuses on distributed autonomous intelligent systems for various inspection and monitoring applications.

• Robotics
• Control Systems
• Artificial Intelligence
• +۱۱ مورد دیگر

Eliseo Ferrante is an Assistant Professor at the Faculty of Science, Department of Artificial Intelligence, Vrije Universiteit Amsterdam. He is also affiliated with the Network Institute. His research focuses on swarm robotics, collective decision-making, and autonomous systems, contributing to UN Sustainable Development Goals. He teaches courses such as 'Learning Machines' and 'Collective Intelligence.' His research explores topics including robot swarms in challenging environments, evolutionary algorithms for adaptive robotics, and morphological evolution in robots. Key contributions include methods for robust swarming in GNSS-denied areas and optimized control strategies for evolvable morphologies. Dr. Ferrante has supervised 2 PhD theses and contributed to datasets on collective motion models and modular robotics. His work emphasizes practical applications of AI in robotics, with a focus on resilience and adaptability in complex systems.

• Robotics
• Swarm Robotics
• Collective Decision Making
• +۳ مورد دیگر

Cock Heemskerk serves as a Lecturer in Robotics at Inholland University of Applied Sciences, Alkmaar campus since May 2016, operating under the Research and Innovation Centre for Technology, Design and Computer Science (RIC-TOI). He collaborates across Mechanical Engineering, Electrical Engineering, and Computer Science programs to integrate robotics into technical curricula through applied research. His educational foundation includes a PhD in Mechanical Engineering from Delft University of Technology (1990) on industrial robot assembly, an MSc from the same institution (1985), and a visiting scientist role at Carnegie Mellon University (1985-1986). Delft University of Technology: MSc Mechanical Engineering (1985) Delft University of Technology: PhD Robotics (1990) Carnegie Mellon University: Visiting Scientist (1985-1986) Dr. Heemskerk's research centers on practical robotics implementation with dual emphases: healthcare applications (including a care robot developed since 2014 through his consultancy HIT) and agricultural robotics for sustainable farming. His work uniquely bridges Technology, Design and Computer Science (TOI) with Health, Sport and Welfare (GSW), Agri, Food & Life Sciences (AFL), and Business domains through projects like HiPerGreen. Key cross-cutting themes include sustainability, human-robot collaboration, and field-deployable solutions for real-world problems. Analysis of his 2017-2019 publications reveals a concentrated focus on agricultural robotics , particularly Unmanned Aerial Systems (UAS) for greenhouse crop monitoring. These works demonstrate a strategic shift toward practice-oriented validation of robotics in horticulture, with strong emphasis on data transmission, storage, and UAS navigation in confined environments. Concurrently, his educational contributions explore robotics' role in developing 21st-century technical skills. Students engage through internships, graduation projects, and design assignments within his Robotics knowledge circle, while industry partnerships drive innovation in healthcare and agricultural robotics applications. Government collaboration is exemplified by the Ministry of Agriculture's working visit regarding his input on the "Robots to Farming Practice" innovation program. The Robotics lectureship operates within RIC-TOI as a multidisciplinary hub connecting Terra Technica and other platforms, with current projects including HiPerGreen, KIEM 21st Century Skills, and SCOUT focusing on field validation of robotic systems.

• Robotics
• Agricultural Robotics
• Healthcare Robotics
• +۴ مورد دیگر

Kim Baraka is an Assistant Professor at the Faculty of Science, Vrije Universiteit Amsterdam, affiliated with the Artificial Intelligence department, Network Institute, and Social AI division. His research focuses on Human-Robot Interaction, Reinforcement Learning, and socially intelligent systems. He co-developed frameworks like SHARPIE for Human-AI collaboration and explores ethical aspects of AI teamwork. Baraka teaches courses on Human-interactive Agent Learning, Robotics, and Socially Intelligent Robotics. He actively contributes to conferences like HRI and ROMAN, publishing on topics ranging from robot curriculum learning to empathetic AI design. Ancillary roles include director of Bara-kadance and board member of Stichting Triplets. Research interests include: Human-AI co-creativity and collaboration Robot learning through human demonstrations Emotional expression in embodied AI Ethical frameworks for human-agent teams Recent work highlights multimodal interaction (e.g., audio-visual speech recognition), prosody-based teaching signals, and proxemics-aware navigation. His 2025 publications emphasize iterative algorithm design for fairness in human-agent teams and systematic reviews of collaborative AI creativity. This research bridges technical advancements with socially responsible AI deployment.

• Artificial Intelligence
• Human-Robot Interaction
• Reinforcement Learning
• +۳ مورد دیگر

Prof. Jenny van Doorn is a Professor of Service Marketing at the University of Groningen, affiliated with the Faculty of Economics and Business. Her research focuses on service technology, robotics, customer engagement, sustainability, and food waste. She collaborates with organizations such as Welbo, Tangenborgh, and Landal Green Parks to explore societal transitions through technology adoption. Key projects include investigating human-robot collaboration in healthcare and developing speech technology for robots using regional dialects. She holds editorial roles at top journals like the Journal of the Academy of Marketing Science and Journal of Service Research. Awards include the D&IN Insight Scientist Award and SAGE’s 10-Year Impact Award. Her teaching includes courses on Marketing & Consumer Well-being and Managing Customer Experience. Research interests emphasize the ethical and practical integration of AI and robotics in services, with a focus on healthcare and sustainability. Notable contributions address consumer responses to service robots, food waste drivers, and policy impacts. She frequently engages with practitioners and policymakers, advocating for socially responsible technology adoption. Her interdisciplinary work bridges marketing, technology, and public health, addressing challenges like aging populations and environmental conservation. Education: PhD in Marketing (implied by position). Labs/Teams: Collaborations with the Centre of Computational Linguistics (Faculty of Arts) and the UMCG (University Medical Center Groningen). Grants: NWA-IDG Grant on dialect-speaking robots for elderly acceptance. Awards: Includes editorial excellence and impact recognition in marketing research.

• Service Marketing
• Robotics in Service
• Customer Engagement
• +۵ مورد دیگر