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Elina RönnbergView profile

Professor

• Discrete Optimisation
• Mathematical Optimisation
• Scheduling
• +18 more

Elina Rönnberg is a Professor and Deputy Head of Department at the Department of Mathematics, Linköping University, where she leads research in discrete optimisation and intelligent decision-making. Her work bridges theoretical method development and real-world applications in sectors such as healthcare, aviation, mining, and transportation. She is actively involved in the Wallenberg AI, Autonomous Systems and Software Program (WASP) and has collaborated with industry leaders like Saab and Scania. Her research focuses on advanced optimisation techniques including Dantzig-Wolfe decomposition, Lagrangian relaxation, column generation, branch-and-price, and logic-based Benders decomposition. She also explores hybrid methods combining mathematical programming with constraint programming and machine learning. Applications span nurse rostering, electric vehicle routing, aircraft arrival scheduling, and underground mine planning. Recent publications highlight a strong trend toward integrating AI and machine learning—particularly graph neural networks—with classical optimisation frameworks to accelerate solution methods. Her work emphasizes practical impact, robustness, and scalability in solving complex scheduling and resource allocation problems. Nurse Rostering with Strategic Planning of Skills for Sick-Leave Robustness (2024) Pricing for the EVRPTW with Piecewise Linear Charging (2024) Speeding Up Logic-Based Benders Decomposition with Graph Neural Networks (2024) Elina supervises several PhD students and has co-supervised doctoral research at international institutions including Makarere University (Uganda) and the University of Exeter (UK). She has contributed to applied projects through student theses in collaboration with Scania and Saab, focusing on electric vehicle routing and search-and-rescue optimisation. She previously served as a Specialist in Optimisation at Saab Aeronautics (2014–2020) and co-founded Schemagi, a scheduling tool aimed at improving quality in healthcare. She teaches courses such as Introduction to Optimization (TAOP07) and Project - Applied Mathematics (TATA62). Her research group, 'Mathematics and algorithms for intelligent decision-making,' operates within the Division of Applied Mathematics (TIMA) at the Department of Mathematics. The team develops decision support tools that enhance efficiency and sustainability in complex systems, particularly under the growing demands of electrification and digitalisation in transport and logistics.

Michael WeyrichView profile

Professor

• Industrial Automation
• Digital Twins
• Large Language Models (LLMs)
• +7 more

Prof. Michael Weyrich is a faculty member at the Institute of Industrial Automation and Software Engineering (IAS) within the University of Stuttgart , leading the Cluster of Excellence IntCDC . His academic rank is Professor, and he focuses on Industrial Automation , Digital Twins , and Large Language Models (LLMs) for manufacturing and automotive systems. His research explores integrating LLMs into industrial automation for adaptive control, cloud offloading of vehicle functions, and semantic interoperability via Asset Administration Shells . He investigates modular production architectures , connected vehicle systems , and synthetic data generation for autonomous machinery. Recent publications highlight LLM-driven production planning , dynamic sensor calibration , and machine learning for fault detection in electric vehicle powertrains. His work emphasizes real-time data modeling and flexible microservice orchestration .

Samuel LederView profile

Researcher

• Robotics
• Architectural Design
• Computational Design
• +5 more

Samuel Leder is a doctoral researcher at the Institute of Computational Design and Construction (ICD) under the Cluster of Excellence IntCDC at the University of Stuttgart. His work focuses on the integration of robotics and architectural design, particularly in developing distributed robotic systems for timber construction. He has been actively involved in research projects such as RP 19-1 – Robotic Kinematic System for Parallel Construction and RP 19-2 – Co-Design for Distributed Cooperative Multi-Robot Systems . Additionally, he serves on the Equal Opportunity Commission at ICD. Bachelor of Design in Architecture (summa cum laude), Washington University in St. Louis Bachelor of Applied Science in Systems Science and Engineering (magna cum laude), Washington University in St. Louis MSc in Architecture via the Integrative Technologies and Architectural Design Research (ITECH) program, University of Stuttgart Samuel’s research explores the synergies between agent-based modeling , robotic systems , and architectural design . His work aims to create minimal robotic machines capable of constructing complex spatial assemblies, particularly with timber structures . He investigates the co-design of robots and the structures they build, emphasizing modular systems and kinematic behaviors . Recent publications highlight advancements in digital twins , adaptive assembly , and human-robot collaboration for timber construction. The 15 most recent articles reveal trends in collective robotic construction , agent-based modeling , and material-robot interaction . These works emphasize timber fabrication , modular systems , and interactive simulation for large-scale construction tasks. Key sub-fields include adaptive assembly , cyber-physical systems , kinematic control , and human-guided robotics . Scientific Awards: German Academic Exchange Service (DAAD) Award for Outstanding Achievement Deutschlandstipendium Samuel’s research is conducted within the ICD at University of Stuttgart , where he collaborates on the Wood Building Systems for Distributed Robotics associated project. His work bridges architecture , robotics , and computational design , aiming to redefine on-site construction methodologies through innovative robotic systems.

• Photonics
• Laser Technology
• Machine Learning
• +5 more

Professor Robert Eason is a leading academic at the University of Southampton, specializing in photonics and laser technology. His research spans interdisciplinary areas combining Machine Learning , Medical Diagnostics , and Microfluidics . Research Interests : Eason focuses on AI-driven laser applications, including deep learning for phototherapy , autonomous laser machining , and low-cost paper-based diagnostic devices . His work bridges photonics with biomedicine and advanced manufacturing. Recent Publications : His 2025 article in Scientific Reports explores AI simulations for psoriasis treatment, while 2024-2022 works address laser-controlled microfluidics, deep learning in microscopy, and reinforcement learning for laser machining. Supervision : He supervises PhD student Georgia Mourkioti in laser-based research projects. External Roles : Eason has served as a speaker at international conferences including the International Symposium on Laser Precision Microfabrication (2018), LAISER (2019), and Deep Learning for Control of Light-Matter Interactions (2022).

• Biomaterials
• Regenerative Medicine
• Tissue Engineering
• +4 more

Prof. Elisabeth Engel López leads the Biomaterials for Regenerative Therapies group at the Institute for Bioengineering of Catalonia (IBEC) and serves as a Professor at the Technical University of Catalonia. With over 80 publications in JCR journals, her work focuses on designing biomaterials and scaffolds for in vitro/in vivo regenerative medicine, emphasizing cellular response mechanisms and translational applications. Developing lactate-releasing systems for metabolic modulation Advancing 3D bioprinting for tissue-specific models Engineering angiogenic and osteogenic biomaterials Her research bridges fundamental studies with industrial partnerships, including pharmaceutical and biomedical device companies, and contributes to European collaborative projects. She received the Barcelona City Award for technological research and has delivered numerous invited lectures. Her group explores substrate stiffness, ion release, and microenvironmental cues to control cell behavior in cardiac, neural, and bone regeneration contexts.

• Embedded Systems
• Artificial Neural Networks
• Signal Processing
• +3 more

Magdalena Szymczyk is a Lecturer in the Department of Biocybernetics and Biomedical Engineering at AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering. Her work bridges embedded systems, biomedical signal processing, and geophysical data analysis. Research focuses on energy-efficient sensor networks, neural networks for GPR data classification, and mathematical transforms in signal analysis Expertise in parallel computing, real-time systems, and biomedical engineering applications Her publications (2015–2025) demonstrate a trajectory from parallel neural networks and S-transform/GPR methodologies to recent work on MicroPython in embedded systems. Key themes include energy optimization in distributed architectures and AI-driven signal processing across biomedical and geophysical domains. She has authored works on deterministic chaos in simulations, GPU image processing, and cybersecurity in microcontroller systems. Her current research emphasizes embedded systems security, medical signal diagnostics, and computational methods for geological analysis. She utilizes tools like OpenCL for GPU acceleration and MATLAB for parallel computing implementations.

Sara BernardiniView profile

Professor

• Artificial Intelligence
• Automated Planning
• Robotics
• +4 more

Professor Sara Bernardini is a leading academic in Artificial Intelligence at the University of Oxford's Department of Computer Science, where she holds a joint appointment as a Tutorial Fellow at Mansfield College. Her research specializes in decision-making for autonomous systems, automated planning, and robotics, with applications in extreme environments like space missions, nuclear decommissioning, and offshore energy. She bridges theoretical AI with real-world challenges through projects funded by Innovate UK, EPSRC, NERC, and the Alan Turing Institute. Her research interests span: Autonomous Systems : Developing agents that support humans in complex cognitive tasks. Automated Planning : Algorithms for goal recognition, pathfinding, and multi-agent coordination. Robotics : Solutions for subterranean exploration, offshore wind farms, and UAV operations. AI Safety : Risk-aware autonomous systems and interpretable decision-making. Bernardini's publications emphasize algorithmic robustness in path planning, multi-agent coordination , and real-world AI deployments . Recent work explores goal legibility in uncertain environments, energy-efficient robotics, and AI education tools. Her 65+ papers in top venues (e.g., AIJ, JAIR, ICAPS) show a trend toward safety-critical applications and human-AI collaboration. Awards & Leadership: ICAPS-2020 Best Paper Honorable Mention Executive Council Member, Association for the Advancement of Artificial Intelligence (AAAI) Program Chair, International Conference on Automated Planning and Scheduling (ICAPS 2024) Associate Editor, Artificial Intelligence Journal She leads interdisciplinary teams for projects like autonomous offshore wind farm maintenance and modular robots for extreme environments. As Principal Scientist at the UK National Oceanography Centre, she advanced marine robotics. She mentors PhD candidates and collaborates globally (e.g., NASA Ames, MIT).

Gaël KermarrecView profile

Researcher

• Boundary Layer Meteorology
• Atmospheric Turbulence
• GNSS Applications
• +3 more

Dr. Gaël Kermarrec is a researcher at the Boundary Layer Meteorology Group , part of the Institute of Meteorology and Climatology within the Faculty of Mathematics and Physics at Leibniz University Hannover . His work focuses on atmospheric turbulence, GNSS applications, and remote sensing for environmental monitoring. Boundary layer meteorology Turbulence theory GNSS signal processing Terrestrial laser scanning Climate change impacts Geodetic time series analysis His research integrates advanced mathematical models like LR B-splines and Matérn covariance with large eddy simulations to study: Atmospheric turbulence effects on optical/GNSS signals Hydrospheric mass loading Deformation analysis of terrain/port infrastructure Climatic sea-level changes Machine learning for remote sensing The 15 most recent articles (2025-2023) demonstrate his focus on: GNSS-based turbulence detection AI-enhanced climate mapping Advanced surface approximation techniques Multi-sensor data fusion Stochastic modeling of geodetic observations Environmental impacts on optical measurements He has developed tools like the Klimascanner QGIS plugin for urban climate resilience and contributes to: Understanding atmospheric scale lengths Improving TLS/GNSS deformation monitoring Analyzing hydrospheric changes Wavefront modeling Ionospheric corrections

Sara MagliacaneView profile

Assistant Professor

• Causality
• Causal Representation Learning
• Causality-inspired Machine Learning
• +4 more

Sara Magliacane is an Assistant Professor at the University of Amsterdam , affiliated with the Amsterdam Machine Learning Lab (AMLab) and the Informatics Institute . She also holds a Research Scientist position at the MIT-IBM Watson AI Lab and has been an ELLIS Scholar since 2022. Education PhD in Artificial Intelligence (2017), VU Amsterdam MSc in Computer Engineering (2011), Politecnico di Milano BSc in Computer Engineering (2008), Università degli Studi di Trieste Research Focus : At the intersection of Causality and Machine Learning , her work addresses Causal Representation Learning from high-dimensional data (images, sequences) Causal Discovery in latent confounder scenarios Causality-inspired Reinforcement Learning for robustness and adaptability Neurosymbolic AI for theoretical guarantees Publication Trends : Her recent work explores Factored adaptation in non-stationary environments (NeurIPS 2022) Temporal causal identifiability (ICML 2022) Binary interaction-based causal discovery (UAI 2023) Safe exploration in visual RL (HSCC 2021) Structure learning lower bounds (NeurIPS 2020) Scientific Recognition : ELLIS Scholar (2022–present) Spotlight presentations at ICML 2022 and ICLR 2022 Advising & Collaborations : Currently supervising 6 PhD students at the University of Amsterdam and AUMC, with 12 alumni advisees. Collaborates with researchers at MIT-IBM Watson AI Lab, Simons Institute, and TUM.

Cathy YeView profile

Associate Professor

• Tissue Engineering
• Biomaterials
• Biomechanics
• +5 more

Professor Cathy Ye is an Associate Professor of Engineering Science at the University of Oxford and Director of the Oxford Centre for Tissue Engineering and Bioprocessing (OCTEB) . She is also a Fellow of Linacre College , with research focusing on Tissue Engineering , Biomaterials , and Bioreactor Design for regenerative applications. Her research spans in vitro cancer modeling , bone-cartilage interface development , and smart bioreactor systems for cell therapy. Current projects include SimCells for Cultured Meat under the Tissue Engineering group, supported by grants like the BBSRC award and EPSRC First Grant (EP/H021442/1). She teaches C10 Biosystem Modelling , C23/BME2 Tissue Engineering , and B17/BME1 Biomechanics while leading lab modules for the MSc in Biomedical Engineering. Her publications cover extracellular vesicle purification , antimicrobial biomaterials , and 3D tumor models , reflecting her interdisciplinary approach to biomedical engineering challenges.

Rhiannon FirthView profile

Lecturer

• Sociology of Education
• Gender, sexuality and education
• Utopian studies
• +5 more

Dr. Rhiannon Firth is a Lecturer in Sociology of Education in the Department of Education, Practice and Society at the Institute of Education, University College London (UCL). She also serves as the Programme Leader for the MA in Sociology of Education. Her academic career spans interdisciplinary research at the intersection of Sociology, Education, and Politics, with a focus on utopian ideals and pedagogical practices of social and ecological movements. Dr. Firth's educational background includes: First Class BA (Hons) in Combined Studies (Politics, English Literature and Economic and Social History) from the University of Leicester ESRC-funded MA in Political Science (Distinction) from the University of Nottingham PhD in Political Sociology from the University of Nottingham Her research focuses on how grassroots social movements create knowledge and mobilize social change around global "wicked" problems including inequality, climate change, technological developments, and pandemics. She has conducted funded research with self-managed sustainable communities in the UK and USA, grassroots disaster relief movements including Occupy Sandy New York and COVID-19 Mutual Aid London, and organizations using automation technology in experimental ways. Dr. Firth's recent publications reflect her ongoing exploration of utopian and dystopian themes across multiple domains. Her work spans analyses of pandemic responses, ecological breakdown, industrial technology, and community organizing. A strong thread throughout her scholarship examines how prefigurative politics and mutual aid practices offer alternatives to mainstream approaches to social organization, particularly in times of crisis. Her research increasingly focuses on the intersection of technology, labor, and utopian thinking, particularly examining how automation and cybernetics might be reimagined through radical social movements. Among her significant recognitions: Senior Fellow of the Higher Education Academy (SFHEA), earned in 2017 ESRC funding for her MA studies Dr. Firth has secured research funding from multiple sources including ESRC, ISRF, EPSRC, HEFCE, local councils, and UCL Grand Challenges. She supervises MA dissertations annually and currently mentors one PhD student. Her professional activities include media engagement (such as appearing on BBC Radio 4's The Moral Maze), conference presentations, and serving as ECR Representative for the Utopian Studies Society of Europe. She is actively involved with research groups and networks focused on utopian studies, social movements, and critical pedagogy, contributing to the vibrant intellectual community around alternative futures and radical educational practices.

• Textile Engineering
• Smart Textiles
• Textile Sensors
• +4 more

Helder Carvalho is an Associate Professor at the University of Minho's School of Engineering, Campus de Azurém, where he also serves as Director of the Department of Textile Engineering and Director of the Master's program in Textile and Accessories Product Design and Innovation. His academic career spans over three decades, with a focus on textile engineering and its intersection with electronics and automation systems. His educational background includes: PhD in Textile Engineering (2004) from University of Minho, School of Engineering MSc in Textile Engineering (1998) from University of Minho, School of Engineering BSc in Electrotechnical and Computer Engineering (1992) from University of Porto, Faculty of Engineering Professor Carvalho's research primarily focuses on smart textiles, textile sensors, and instrumentation systems for industrial sewing machines. His work bridges the gap between traditional textile manufacturing and modern electronics, creating innovative solutions for interactive textiles and wearable technology. He has particular expertise in developing flexible sensors that can be integrated into fabrics for applications ranging from sports performance monitoring to healthcare. His recent publications demonstrate a strong trend toward sports applications of smart textiles, with numerous papers on fencing apparel, karate body protectors, and general athletic performance monitoring. The research spans material science, sensor development, and user experience design, showing a comprehensive approach to creating functional and attractive smart textile products. Professor Carvalho has received recognition through research funding from major institutions: BE@T Bioeconomy Textile and Clothing (current) Greenauto - Green Innovation for the Automotive Industry (current) Factor ST+ (2021-2023) FAMEST (2017-2020) TSSIPRO (2016-2019) He has directed multiple academic programs including the Master's in Textile and Accessories Product Design and Innovation, and coordinated educational initiatives like the CET 'Fashion Commerce' program. His work at the Textile Science and Technology Centre demonstrates a commitment to translating research into practical applications across sports, healthcare, and industrial manufacturing sectors.

• Creative Cognition
• Psychology of Creativity
• Metacognition
• +3 more

Mathias Benedek is an Associate Professor at the Institute of Psychology, Faculty of Natural Sciences, University of Graz, Austria. He directs the Creative Cognition Lab and is actively involved in several research networks, including the "Complexity of Life" profile area, the "Brain and Behavior" research network, and the "FUTURE EDUCATION" research network at the University of Graz. His research focuses on the cognitive and neural mechanisms underlying creative thinking, with particular emphasis on the role of memory processes, metacognition, and eye movement patterns during creative ideation. Dr. Benedek's work bridges psychological theory with empirical research methods including eye tracking, neuroimaging, and computational modeling of creative processes. His research has important implications for understanding how creative potential develops and how it can be assessed and nurtured in educational and professional contexts. Dr. Benedek's publication record demonstrates a consistent focus on creative cognition across multiple dimensions. His recent work has expanded into emerging areas such as human-AI collaboration for creative tasks, automated assessment of creativity using large language models, and the relationship between physical activity and creative performance. His research shows a strong trajectory toward more ecologically valid methods for studying creativity in real-world contexts, moving beyond traditional laboratory paradigms. Seraphine Puchleitner Anerkennungspreis (PhD Supervision Award), University of Graz, 2021 William-Stern-Preis, German Psychological Society, 2019 Research Prize, University of Graz, 2017 Research Prize (Publication Category), Initiative Gehirnforschung, 2016 Berlyne Award, Division 10, American Psychological Association, 2015 Dr. Benedek has demonstrated strong commitment to mentoring the next generation of researchers, as evidenced by his 2021 PhD Supervision Award. His research has been supported by multiple grants from national and international funding bodies, though specific grant details are not provided in the available information. His professional service includes leadership roles in the Initiative Gehirnforschung Steiermark since 2010 and active membership in several psychological societies across Europe and North America. Dr. Benedek leads the Creative Cognition Lab at the University of Graz, which employs a multidisciplinary approach to studying creative processes. The lab integrates methods from cognitive psychology, neuroscience, and computational modeling to investigate the mechanisms underlying creative thought. Current research projects examine the relationship between eye movements and internal cognitive processes, the development of automated assessment tools for creativity, and the application of creativity research to educational contexts.

• Robotics
• Human-Robot Interaction
• Machine Learning
• +7 more

Christian Smith is an Associate Professor and Lecturer at the Department of Robotics, Perception and Learning at Kungliga Tekniska Högskolan (KTH Royal Institute of Technology). His research focuses on robotics and applications in human-centered environments like home environments, small workshops, and healthcare facilities, including the development of new robotic systems for research. Teaching Roles: Course Coordinator/Teacher/Examiner for courses such as Introduction to Robotics (DD2410), Research Project in Robotics (DD2411), and Java Programming for Python Programmers (DD1380) Research Themes: Human-Robot Interaction, Behavior Trees, Exoskeletons, Intent Recognition, and Multimodal Perception Awards: No specific scientific awards mentioned in the provided text His KTH profile highlights work on adaptive robotics systems and formalized control strategies. The research portfolio spans from theoretical studies on behavior tree programming to applied work in assistive technologies and teleoperation systems.

Clinton FookesView profile

Professor

• Computer Vision
• Artificial Intelligence
• Human Behavior Analysis
• +7 more

Professor Clinton Fookes is a faculty member at the Queensland University of Technology (QUT) within the School of Electrical Engineering & Robotics . His research focuses on leveraging computer vision and artificial intelligence to develop automated systems that understand, anticipate, and interact with human behaviors, with applications in medical diagnostics, autonomous vehicles, defense, and industrial efficiency . Research areas include AI adaptability, multimodal biosignal analysis, and human-machine interaction Collaborates with CSIRO Data61, Defence Science and Technology Group, Orica, Airbus, and Sentient Vision Systems Develops systems for human action detection, infrastructure monitoring, and stress response prediction His work addresses critical challenges in AI deployment, such as environmental adaptability and reducing diagnostic errors in medical and autonomous systems. Recent publications highlight trends in self-supervised learning, zero-shot knowledge transfer, multimodal integration , and 3D reconstruction for healthcare , while exploring ethical AI use in sectors like mining and defense . Professor Fookes emphasizes interdisciplinary collaboration, bridging engineering, medicine, and social sciences to advance AI systems capable of real-world impact. His research agenda includes improving AI memory capabilities and explainability for safer, more reliable automation.