جستجوی استاد راهنمای دانشگاهی

Sebastian Risi is a Professor at the IT University of Copenhagen , where he directs the Creative AI Lab and co-directs the Robotics, Evolution and Art Lab (REAL) . His work bridges computational evolution, deep learning, and collective intelligence for applications in robotics, art, and video game design. His research focuses on self-organizing AI systems that grow or assemble through local interactions, inspired by biological development. Key areas include neuroevolution , neural cellular automata , and generative modeling , with applications in adaptive robotics, game content creation, and damage-resilient AI. Recent publications highlight trends in self-assembling neural architectures (NDPs) and 3D functional machine generation (Minecraft experiments). Awards include ERC Consolidator Grant (2022), Best Paper at FDG’21 , and Google Faculty Award (2019). Scientific Awards : ERC Consolidator Grant (GROW-AI), Best Paper FDG’21, Runner-Up IEEE Games’20, GECCO 2017 Competition Winner, Sapere Aude Grant, Amazon/Google Faculty Awards He advises on projects like GROW-AI (EU-funded), AI-TESTER (game testing), and C2SIM (military systems). Media coverage includes Science , Wired , and Popular Science .

• Neuroevolution
• Evolutionary Robotics
• Self-Organizing AI
• +۹ مورد دیگر

Yvonne Dittrich is a Professor at the IT University of Copenhagen (ITU), affiliated with the Software Development Group. She holds an adjunct professorship at IIT Mandi, India, and has held roles at institutions in Sweden, Canada, and the U.S. Her research focuses on cooperative and human aspects of software engineering, including Continuous Software Engineering (CSE), use-oriented design, and end-user development (EUD). She has led projects like SAIA-Farm (sustainable irrigation via satellite analytics) and contributed to frameworks like 'Cooperative Method Development.' **Education**: PhD in Computer Science (Hamburg University, 1997), M.Sc. from TU Darmstadt. **Research Interests**: She pioneers methods bridging software engineering with human-centric practices, emphasizing sustainability and participatory design. Her work addresses challenges in global software development, agile methodologies, and software ecosystems. **Awards**: TAT-Förderpreis (1989), Best Paper Award (2018), Distinguished Reviewer recognition (2018). **Grants & Leadership**: Led projects funded by the Danish Innovation Fund, EU, and others. Served on editorial boards for IEEE Transactions on Software Engineering and Journal of Systems and Software. **Labs/Teams**: Collaborates with labs in Denmark, India, and Canada on interdisciplinary projects, including smart irrigation systems and fintech ESG data commons.

• Cooperative and Human Aspects of Software Engineering
• Continuous Software Engineering (CSE)
• Use Orientation in Software Engineering
• +۷ مورد دیگر

Silvia Tolu is an Associate Professor at the Technical University of Denmark's Department of Electrical and Photonics Engineering, specializing in Neurorobotics. She leads the NeuroRobotics Technology Lab (NRT-LAB), focusing on bio-mimetic control architectures for compliant robotic systems. Her research integrates neuroscience, computer science, and biology to develop solutions for assistive robotics and neurodegenerative disease diagnosis. Her research interests span: Neuro-robotics and neuromorphic engineering Bio-inspired control systems and adaptive motor control Machine learning for robotic applications Human-robot compliant interaction Cerebellar control models Publications primarily focus on neurorobotics, bio-inspired control, and human-robot interaction, with recent advances in learning-based control systems for soft robots and aerial manipulation. Awards include the AEG Elektrofonden Research Grant and funding for human-robot interaction safety research. Current projects include LOCOPD (Lundbeck Foundation), AEROTRAIN (EU Marie Curie ITN), and compliant human-robot interaction systems. She supervises multiple PhD students in neurorobotics and maintains international collaborations across Europe and Asia. Laboratory resources include advanced robotic platforms for musculoskeletal and soft robot control.

• Neurorobotics
• Bio-inspired Control Systems
• Neuromorphic Engineering
• +۳ مورد دیگر

Andres Faina is a Lecturer at the IT University of Copenhagen , specializing in Robotics, Evolution, and Artificial Life Lab . He serves as Academic Director at The Maritime Hub and co-leads the Robotics, Evolution, and Art Lab . Research Focus: Robotics, Morphological Development, Bipedal Walking Key Collaborations: European Commission-funded projects (EVOBLISS, BIG-MAP, MOZART), Novo Nordisk Foundation His work explores growth-based morphological development for robotics, focusing on: Bipedal and quadrupedal locomotion Artificial Neural Network control systems Evolutionary algorithms for fitness landscape shaping Modular and reconfigurable robot design Scientific Awards : Best Paper Award at RIE 2017 Winner of Virtual Creatures Competition at GECCO 2017 Honorable Mention for Technical Achievement at GECCO 2017 Active in project leadership (e.g., Teaming up a quadruped robot with a drone ) and media engagement (14 mentions in press/media), including commentary on robotics entrepreneurship and industry challenges.

• Robotics
• Evolutionary Robotics
• Morphological Development
• +۶ مورد دیگر

Ameer Tamoor Khan serves as a Postdoctoral Researcher (Research Fellow) in the Section for Crop Sciences within the Department of Plant and Environmental Sciences at the University of Copenhagen's Faculty of Science. Based at the Taastrup campus (Højbakkegård Allé 13, 2630 Taastrup), his work bridges agricultural science and computational intelligence with direct contact via atk@plen.ku.dk and +4535327865. His research centers on AI-driven solutions for agricultural challenges, specializing in computer vision applications for precision farming. Key focus areas include pest and weed detection using YOLO architectures (v8/v11), leaf phenotyping analysis, neural network-based supply chain optimization, and evolutionary computation for model-free systems. This interdisciplinary work integrates deep learning, operational research, and agricultural engineering to enhance food security and farming efficiency through real-time computational approaches. Analysis of his 2025 publications reveals a dominant trend in applying computer vision to agricultural robotics, particularly in multi-crop monitoring systems. His work consistently connects neural dynamics with practical farming applications, spanning from cotton weed management to portfolio risk optimization, demonstrating cross-domain versatility in computational intelligence. No scientific awards were documented in the source material. Information regarding student supervision or research grant acquisition was not provided in the available records. While specific laboratory affiliations weren't detailed, his research output indicates active collaboration within computational agriculture networks, particularly with co-authors Jensen and Mirjalili across multiple institutions.

• Precision Agriculture
• Computer Vision
• Neural Networks
• +۳ مورد دیگر

Simon Shaw is a Researcher at the Novo Nordisk Foundation Center for Biosustainability , Technical University of Denmark. His work focuses on genome mining and bioinformatics tool development for microbial genetics. Research Interests : Computational analysis of gene clusters , antiSMASH database expansion, phylogenetic tree generation , and robotic automation in Streptomyces conjugation. Key Contributions : Co-author on 11 peer-reviewed publications including major updates to the antiSMASH database (versions 6.0–7.0), ActinoMation automation framework, and getphylo phylogenetic tool. Collaborative Activities : Organized the 2018 antiSMASH Hackathon and participated in the 4th antiSMASH Hackathon (2017) .

• Bioinformatics
• Genome Mining
• Microbial Genetics
• +۵ مورد دیگر

Rodrigo Moreno Garcia is an Assistant Professor at the IT University of Copenhagen, specializing in Robotics, Evolutionary Computation, and Systems Engineering. He actively contributes to research in modular robots, human-robot interaction, and automated chemical processes, with affiliations to the Robotics, Evolution, and Art Lab and Robotics, Evolution and Artificial Life Lab. Academic Rank: Assistant Professor Institution: IT University of Copenhagen (ITU) Research Focus: His work spans evolutionary robotics, sensor design for liquid-liquid extraction, AI-driven morphological optimization, and materials acceleration platforms for battery research. Key areas include modular robotics , human-machine interfaces , and self-reconfigurable systems . Recent Publications explore neural cellular automata for classification, constraints in hardware evolution, and sensor innovations for industrial processes. Trends highlight interdisciplinary integration of AI, robotics, and chemical engineering. Awards: Recipient of the Honorable Mention for Technical Achievement at GECCO 2017 for virtual creatures research.

• Robotics
• Evolutionary Robotics
• Modular Robots
• +۵ مورد دیگر

Djordje Grbic is a Lecturer at the IT University of Copenhagen, actively contributing to research in artificial intelligence, robotics, and maritime logistics. He is affiliated with the Creative AI Lab, Robotics, Evolution, and Art Lab, and The Maritime Hub Robotics, Evolution and Artificial Life Lab. His research focuses on: Deep reinforcement learning for complex planning tasks Evolutionary computation in artificial life systems AI optimization of maritime container stowage Procedural content generation for games Sequence evolution simulations for biological systems Recent publications (2023-2024) demonstrate expertise in applying deep reinforcement learning to maritime logistics problems and developing systems for sequence evolution simulation. Collaborations span computational logistics, bioinformatics, and game design domains. Current affiliations include: Creative AI Lab (ITU Copenhagen) Robotics, Evolution, and Art Lab The Maritime Hub for logistics research

• Deep Reinforcement Learning
• Evolutionary Robotics
• Computational Logistics
• +۳ مورد دیگر

Efthymios Altsitsiadis is an Associate Professor at the Department of Management, Society and Communication, Copenhagen Business School. His research focuses on sustainability, renewable energy transition, wildfire management, stakeholder engagement, and social network analysis. He has contributed to interdisciplinary projects such as TREEADS, addressing holistic fire management ecosystems and organizational structural factors in disaster response. His work intersects environmental science, public policy, and information systems innovation. Key areas include developing frameworks for social acceptance of renewable energy and analyzing drivers of wildfire evacuation stakeholder collaboration. Recent studies also explore virtual agents' trustworthiness in human-agent interactions. Altsitsiadis collaborates with institutions like ACCELIGENCE Ltd and Marin Energi Testsenter AS. His research spans both academic and applied domains, including pandemic-related food systems resilience and optimization algorithms in manufacturing. He has supervised 2 academic works and contributed to EU-funded deliverables and policy reports. Notable projects include the Thessaloniki Metro Study on public transport innovations and analyses of market trends in collaborative production. His diverse portfolio reflects expertise in bridging organizational behavior with environmental and technological challenges.

• Sustainability
• Renewable Energy Transition
• Disaster Management
• +۷ مورد دیگر

Inkyung Sung is an Associate Professor at the Department of Materials and Production, Aalborg University, Denmark. Her research focuses on Artificial Intelligence for Operations Research, particularly in optimization algorithms, UAV operations, and scheduling systems. She leads projects on maritime search and rescue planning, autonomous vehicle path-finding, and cloud computing resource management. Her work integrates AI-driven solutions with real-world applications in emergency services, manufacturing, and logistics. Key research areas include UAV-based service delivery optimization, dynamic environment adaptation for autonomous systems, and scheduling algorithms for robotic and cloud environments. She has collaborated on datasets for generalized assignment problems and developed methodologies for zone partitioning in UAV operations. Sung’s contributions span 33 peer-reviewed publications and three datasets, emphasizing practical applications of operations research in safety-critical and efficiency-driven domains.

• Artificial Intelligence
• Operations Research
• Optimization Algorithms
• +۵ مورد دیگر

Daniel Ortiz Arroyo is an Associate Professor at Aalborg University's Faculty of Engineering and Science, affiliated with the Intelligent Energy Systems and Flexible Markets department. His research focuses on AI-driven solutions for energy systems, wastewater treatment optimization, robotics, and deep learning applications in industrial systems. He leads and collaborates on projects such as AITEKS (AI for Tech Support), OPTIMIZE (Deep Reinforcement Learning in Fermentation), and amphibious drone development for infrastructure inspection. Key research areas include reinforcement learning for environmental control systems, synthetic data generation for defect detection, and predictive modeling in wastewater treatment. His work integrates machine learning with physical systems to enhance efficiency and sustainability. Notable contributions include grey-box models for N₂O dynamics and amphibious quad-rotor designs for pipeline inspection. Dr. Arroyo has contributed to over 97 publications, including peer-reviewed journal articles and conference proceedings, focusing on AI applications in energy, environment, and robotics. He actively participates in editorial peer review for journals like Evolutionary Intelligence and CRC Press . His projects involve collaborations with industry partners like Novo Nordisk Foundation and Innovation Fund Denmark, addressing challenges in microbial fermentation, fiber rope inspection, and wind turbine maintenance. He maintains a strong emphasis on data-driven innovation and interdisciplinary research.

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +۹ مورد دیگر

Joshua Skewes is an Associate Professor in the Department of Communication and Culture – Cognitive Science at Aarhus University, Denmark. He is actively involved in interdisciplinary research bridging cognitive science, psychology, neuroscience, and social robotics. His work is supported by institutions such as the Carlsbergfondet and Forskningsråd for Kultur og Kommunikation, and he collaborates with key research groups including BICLabs and projects like INTERACT-LLM and INSOR. Research Interests: Joshua's research spans cognitive psychology, philosophy of science, psychophysiology, decision-making, and social interaction. He investigates how cognitive processes are shaped by early life experiences, how humans respond emotionally and behaviorally to infant crying, and how social robots can be ethically and effectively integrated into society. His work combines experimental methods, neuroimaging, and behavioral tracking to explore fundamental questions in human cognition and social behavior. The recent trends in his publications reveal a strong focus on interdisciplinary theory evaluation, decision dynamics using movement tracking, and the psychological impact of infant crying. His articles frequently appear in high-impact journals such as Behavioral and Brain Sciences , Experimental Brain Research , and Current Research in Ecological and Social Psychology , reflecting a deep engagement with both theoretical and empirical dimensions of cognitive science. Scientific Contributions: Active contributor to major research projects including INSOR and BICLabs. Regular participant in academic discourse through lectures and media engagement. Involved in public communication of science, addressing criticisms and promoting scientific literacy. Advising and Grants: While specific advisees are not listed, Joshua has contributed to PhD theses and research training. He has secured funding from national and private research councils, including the Carlsberg Foundation, indicating successful grant acquisition. His role as a project manager and co-PI demonstrates leadership in collaborative research. Labs and Teams: He is affiliated with BICLabs (Behaviour, Interaction and Cognition Labs), a multidisciplinary research environment focused on human interaction, automated data collection, and cognitive modeling. He also participates in social robotics initiatives exploring the ethical, legal, and psychological dimensions of human-robot interaction.

• Cognitive Psychology
• Philosophy of Psychology
• Neuroscience
• +۷ مورد دیگر

Rodrigo Moreno is an Assistant Professor at the IT University of Copenhagen, where he joined in 2020. His research focuses on applying AI and machine learning to robotics, with special emphasis on evolutionary robotics, modular robots, and lab automation, particularly for battery chemistry synthesis processes in the BIG-MAP project. His educational background includes a PhD in Systems and Computer Engineering (2019), an MEng in Industrial Automation (2010), and a BSc in Mechatronics Engineering (2008), all from Universidad Nacional de Colombia. His research interests span Artificial Intelligence, Machine Learning, Robotics, Evolutionary Robotics, Modular Robots, Lab Automation, Battery Chemistry Synthesis, and Emergence. His recent publications demonstrate significant work in modular robot evolution, with experiments varying base lengths and analyzing fitness, number of modules, and structural properties. His research employs evolutionary algorithms to optimize robot morphology and control, with applications extending to laboratory automation for battery chemistry. The BIG-MAP and EMERGE projects represent his current major research directions, bridging robotics with chemical synthesis automation. Evolution of modular robots with variable morphologies CPG parameter optimization for robot locomotion Statistical analysis of evolutionary outcomes Lab automation for battery chemistry synthesis His GitHub repositories show active development of research code for evolutionary robotics experiments, with a focus on quantitative analysis and visualization of evolutionary processes. His work demonstrates a strong integration of theoretical evolutionary computation with practical robotics applications.

• Artificial Intelligence
• Machine Learning
• Robotics
• +۵ مورد دیگر

Ying Qu is a Research Assistant at the Institute of Mechanical and Electrical Engineering , University of Southern Denmark , affiliated with the Faculty of Engineering . Their work bridges robotics, control systems, and multi-objective optimization (MOO) in industrial and marine contexts. Research Focus: Multi-objective optimization, underwater robotics, digital twin frameworks, and sustainable agricultural technology. Key Projects: Development of an innovative propeller polishing robot for the shipping industry, focusing on fuel savings and emission reductions. Ying Qu's publications emphasize MOO applications in robotics (e.g., underwater end-effector control), industrial systems (greenhouse climate management), and power electronics. Their work integrates machine learning, evolutionary algorithms, and simulation techniques to address complex engineering challenges.

• Multi-Objective Optimization
• Control Systems
• Robotics
• +۵ مورد دیگر

Milton Llera Montero is a Research Fellow at the IT University of Copenhagen, affiliated with the Creative AI Lab and Robotics, Evolution and Artificial Life Lab. He serves as Co-Investigator on the European Commission-funded GROW-AI project (2023-2027) focused on developing machines capable of rapid learning in unknown environments. His research spans Artificial Intelligence, Robotics, and Evolutionary Computation with emphasis on biological inspiration for adaptive systems. He investigates how principles from biological intelligence can enable artificial systems to rapidly learn and adapt in novel, unstructured scenarios through creative AI methodologies and evolutionary algorithms. Current research centers on the GROW-AI project where he collaborates with Principal Investigator Sebastian Risi and Co-Investigators Eleni Nisioti, Emilie Plantec, and Jakob Winther Pedersen. The project integrates mobile platforms with biological intelligence models to achieve rapid learning capabilities in unpredictable environments.

• Artificial Intelligence
• Robotics
• Machine Learning
• +۳ مورد دیگر