جست‌وجوی استاد و پژوهشگر

Valerie Simonمشاهده پروفایل

استاد

• Developmental Psychopathology
• Interpersonal Violence
• Adolescent Development
• +۳ مورد دیگر

Valerie Simon is a full professor and Clinical Area Chair in the Department of Psychology at Wayne State University , with a joint appointment at the Merrill Palmer Skillman Institute for Child & Family Development . She specializes in developmental psychopathology, interpersonal violence exposure, and adolescent romantic/sexual development. Postdoctoral Training: Brown University School of Medicine (T32 Grant) Clinical Internship: University of North Carolina at Chapel Hill Ph.D.: University of Denver (Clinical & Developmental Psychology) M.A.: American University (General Psychology) B.A.: Loyola University (Music Therapy) Her research examines how interpersonal violence exposure undermines adolescent psychosocial development through multi-method approaches including virtual reality, questionnaires, and physiological measures. She also investigates the interplay between romantic/sexual development and risk factors like revictimization. Selected trends from her publications include: Longitudinal impacts of childhood sexual abuse on adolescent adjustment Attentional bias in trauma survivors Role of social norms in early romantic/sexual experiences Intergenerational trauma and postpartum mental health Honors include grants from the Tiny Blue Dot Foundation , NIH , and Blue Cross Blue Shield of Michigan Foundation .

• AI and Robotics
• Human-Robot Interaction (HRI)
• Autonomous Agents
• +۷ مورد دیگر

Dr. Abolfazl Zaraki is a Senior Lecturer in AI and Robotics at the University of Hertfordshire's Department of Computer Science, part of the School of Physics, Engineering & Computer Science. He leads the Robotics Research Group and previously held roles at Cardiff University's School of Engineering and the IROHMS Research Centre. His academic journey includes a Master's in Mechatronics from University Technology Malaysia (2010) and a PhD in Automatic Robotic and Bioengineering from the University of Pisa (2014). He has held Research Fellow positions in Italy and the UK until 2019. Dr. Zaraki's research focuses on AI-driven autonomous systems, social robotics, and assistive technologies. Key projects include the EASEL, BabyRobot, and JAMES EU initiatives, alongside the Innovate UK-funded InSight project. His work emphasizes Human-Robot Interaction (HRI), trusted autonomy, and applications in healthcare and industrial contexts. Notable contributions include the development of the Kaspar humanoid robot for autism therapy and advancements in reinforcement learning for robotic control. His recent publications (2021–2025) explore agentic AI, memory-driven systems, and personalized LLMs for HRI, alongside technical advancements in robotic control, communication systems, and bio-inspired robotics. His research bridges theoretical AI innovation with practical applications in healthcare, education, and industrial automation. Zaraki has collaborated internationally across institutions and industry partners, contributing to 35+ research outputs. His work aligns with global trends in ethical AI, explainable systems, and human-centric robotics design.

Alberto Sanfeliu Cortésمشاهده پروفایل

استاد

• Artificial Intelligence
• Robotics
• Computer Vision
• +۱۲ مورد دیگر

Alberto Sanfeliu Cortés is a Full Professor of Computational Sciences and Artificial Intelligence at the Universitat Politècnica de Catalunya (UPC), where he has been a faculty member since 1981. He is affiliated with the Institut de Robòtica i Informàtica Industrial (IRI), a joint center of UPC and CSIC, and serves as the Scientific Director of the Unit of Excellence Maria Maeztu at IRI. He leads the Mobile Robotics research line and coordinates the Artificial Vision and Intelligent Systems Group (VIS). He previously served as director of IRI and the UPC Department of Automatic Control. Research interests: His work spans Artificial Intelligence, Robotics, Computer Vision, Pattern Recognition, SLAM, Human-Robot Interaction, Autonomous Systems, and Networked Robotics . He focuses on both theoretical and applied aspects, including urban robotics, autonomous navigation, and the integration of large language models in robotic systems. His research is deeply interdisciplinary, bridging engineering, AI, and societal applications. The recent publications highlight a strong trend toward human-centered robotics , particularly in urban environments, last-mile delivery, and cybernetic avatars. There is growing emphasis on large language models for explainability and personalization, collaborative robotics , and context-aware navigation using vision transformers. His work increasingly addresses societal integration of robots in smart cities and sustainable systems. Scientific Awards: Technology Prize from Generalitat de Catalunya Fellow of the International Association for Pattern Recognition (IAPR) Advising and Grants: He has supervised multiple PhD students, with current advisees working on topics like human intention learning and LLM-enhanced interaction. He has led 45 R&D projects, including 16 EU-funded ones, and was coordinator of the URUS project. Current projects include TORNADO (foundation models for robots handling deformable objects) and SOCIAL PIA (cybernetic avatars). He has also collaborated with Volkswagen Research on autonomous driving initiatives. Labs and Teams: He leads the Artificial Vision and Intelligent Systems (VIS) group and the Mobile Robotics research line at IRI, a premier robotics institute in Spain. His team is actively involved in EU and national projects, focusing on real-world deployment of intelligent robotic systems.

Yuexin Maمشاهده پروفایل

استادیار

• Computer Vision
• Artificial Intelligence
• Scene Understanding
• +۳ مورد دیگر

Yuexin Ma is an Assistant Professor at the School of Information Science and Technology (SIST), ShanghaiTech University, specializing in computer vision and artificial intelligence. Her research focuses on scene understanding, multi-modal learning, autonomous driving, and embodied AI, with over 80 publications in top-tier venues including CVPR, ICCV, TPAMI, and Science Robotics. Education: PhD in Computer Science, University of Hong Kong, 2019 Bachelor of Science, Shandong University (inferred from undergraduate awards) Her work bridges theoretical advances and real-world applications, particularly in 3D perception for autonomous systems. Notable achievements include the Cylinder3D framework (1st place on SemanticKITTI leaderboards) and a MICCAI 2024 Best Paper Award for medical computer vision research. Honors and Awards: Outstanding Teaching Award, ShanghaiTech University, 2024 Outstanding Research Award, ShanghaiTech University, 2023 Best Paper Award, MICCAI 2024 Hong Kong PhD Fellowship Award, 2015 National Scholarship of China (2013, 2014) Professor Ma actively mentors PhD/MPhil students and leads a research group at ShanghaiTech, supported by competitive grants and industry collaborations. Her team released a large-scale 3D crowd perception dataset in 2022 and maintains consistent publication output at premier AI conferences.

• Computer Vision
• Medical Image Analysis
• Pattern Recognition
• +۵ مورد دیگر

Jaime S. Cardoso is a prominent researcher at the University of Porto and Institute for Systems and Computer Engineering, Technology and Science (INESC TEC) in Portugal. His extensive publication record spanning two decades demonstrates his leadership in computer vision, medical image analysis, and pattern recognition. His research primarily focuses on applying artificial intelligence to healthcare challenges, particularly in medical imaging and diagnostics. Cardoso's research interests center on explainable AI for medical applications, biometrics, and computer vision. His work bridges the gap between theoretical machine learning and practical medical solutions, with significant contributions to breast cancer diagnosis, medical image segmentation, and biometric security systems. He has developed innovative approaches to medical image analysis, including virtual staining techniques and privacy-preserving explanation methods for medical AI systems. His recent publications (2023-2025) reveal a strong emphasis on explainable AI in medical contexts, with multiple papers addressing how to make deep learning models more transparent and trustworthy for healthcare applications. He has also made significant contributions to face recognition technology, video anomaly detection, and specialized medical imaging techniques for breast cancer and neonatal EEG analysis. Among his scientific contributions are numerous collaborations with researchers across Portugal and internationally. His work has appeared in top-tier journals including IEEE Access, Medical Image Analysis, and Neurocomputing, reflecting the high impact of his research. Cardoso has supervised numerous students who have become established researchers in their own right, including Ricardo P. M. Cruz, Kelwin Fernandes, and Ana Filipa Sequeira. His research group appears to focus on the intersection of deep learning, medical imaging, and biometrics, with strong connections to clinical applications.

• Energy Security
• Heat Poverty
• Geothermal Energy
• +۳ مورد دیگر

Dr. Katarzyna Świerszcz is an Assistant Professor at the Military University of Technology, specializing in energy security, heat poverty, and non-military security strategies. Her research focuses on integrating geothermal energy resources, analyzing energy poverty indicators, and developing sustainable energy policies. She has published extensively on topics including energy system decarbonization, local governance of energy security, and the socio-economic impacts of energy access. With 50 publications and 5 promoted theses, her work bridges environmental science, policy analysis, and strategic planning. Key research interests include geothermal energy utilization, heat poverty measurement, and cross-sectoral energy security strategies. She has conducted case studies in Poland and Europe, emphasizing regional comparisons and policy implementation. Her projects address infrastructure sustainability, climate resilience, and community-level energy challenges. Dr. Świerszcz contributes to both academic and applied fields through collaborative research on low-emission systems, smart infrastructure, and energy equity. She advises students on projects combining technical and socio-economic dimensions of energy security, reflecting her interdisciplinary approach to solving contemporary energy challenges.

• 3D Reconstruction
• Scene Understanding
• Autonomous Driving
• +۷ مورد دیگر

Stefano Gasperini is a PostDoc Researcher (part-time) at the Technical University of Munich (TUM), affiliated with the Chair of Computer Science Applications in Medicine (CAMP) under Prof. Nassir Navab. He also serves as Co-Founder & CEO of Visualais, a startup focusing on 3D rendering from smartphone images. His primary roles include advancing reliable 3D scene understanding for autonomous driving and medical applications. He holds a PhD (submitted 2023) in Reliable 3D Scene Understanding from TUM, supervised by PD Dr. Federico Tombari, with prior industry experience at BMW and Airbus. Education : PhD in Informatics (2019-2025), TUM Master in Informatics (2017-2019), TUM Bachelor in Computer Engineering (2013-2016), University of Bologna Exchange at UC Santa Cruz (2015-2016) Research Interests : 3D reconstruction, scene understanding, autonomous driving, robustness in computer vision, domain generalization, and medical image analysis. His work bridges theoretical advancements with practical applications in automotive and medical fields, emphasizing reliability under challenging conditions. Publications : Gasperini’s research focuses on robust 3D perception, adversarial augmentation techniques, and domain generalization. Recent work includes pioneering methods like 3D adversarial augmentations for domain adaptation and novel view synthesis using NeRF extensions. Awards : Outstanding Reviewer awards at CVPR 2025, ECCV 2024, ICCV 2023 Deutschlandstipendium scholarships (2017–2019) Summa Cum Laude (2016) and Provost’s Commendations (2015) Advising & Collaboration : Supervises PhD candidates across TUM and industry partners (BMW, Huawei, Mercedes-Benz). Coordinates the reconstruction research group at CAMP and collaborates on projects with AIT, BMW, and academic institutions. Labs & Teams : Active in TUM’s DHM, IFL, and NARVIS labs, focusing on medical imaging, autonomous systems, and surgical data science. Leads the Visualais startup to commercialize 3D reconstruction technologies.

Avideh Zakhorمشاهده پروفایل

استاد

• Signal Processing
• Artificial Intelligence
• 3D Computer Vision
• +۶ مورد دیگر

Dr. Avideh Zakhor is a Professor and Qualcomm Chair at the Department of Electrical Engineering and Computer Sciences (EECS) at the University of California, Berkeley. She is affiliated with several research centers including the Berkeley Artificial Intelligence Research Lab (BAIR), Berkeley Deep Drive Initiative, Video and Image Processing Lab, and Berkeley Center for New Media (BCNM). Her career spans over three decades with significant contributions to signal processing, 3D computer vision, robotics, and deep learning. 1983 B.Sc. in Electrical Engineering from Caltech 1985 S.M. in Electrical Engineering and Computer Science from MIT 1987 Ph.D. in Electrical Engineering and Computer Science from MIT Dr. Zakhor's research interests focus on 3D computer vision, autonomous systems and robotics, deep learning, and signal/image processing. Her work spans diverse areas including drone navigation, medical imaging analysis, indoor positioning, and building energy audits. She has led projects on drone-based 3D building reconstruction, legged robot locomotion, and melanoma detection using AI. The 15 most recent publications highlight her work in several key areas: person search pre-training techniques, drone-based indoor navigation and 3D modeling, medical image segmentation for melanoma detection, hexapod robot locomotion, and proximity detection for public health. These publications demonstrate her expertise at the intersection of computer vision, robotics, and AI applications. Dr. Zakhor has received numerous prestigious awards throughout her career: 2022 Winner of Phases 1 and 2, Department of Energy E-Robot Competition 2018 Electronic Imaging Scientist of the Year by SPIE 2004 Okawa Research Grant 2002 IEEE Fellow 1992 Office of Naval Research Young Investigator Award 1990 Presidential Young Investigator (PYI) Award from President George H.W. Bush 1990 Junior Faculty Development Award 1984-1988 Hertz Fellowship 1983 Henry Ford Engineering Award 1982-1983 General Motors Scholarship Dr. Zakhor has advised numerous research projects and has been involved in significant research grants. She has founded successful companies including Indoor Reality, which develops technologies for rapid 3D mapping and visualization of buildings and assets. She leads research initiatives in various cutting-edge technologies: Unmanned Aerial Vehicles (UAV) with focus on autonomy and obstacle avoidance, perception, path planning and control Deep learning applications in legged locomotion, unsupervised learning for multimodal sensors, misinformation detection, and learning-based image compression Wi-Fi proximity detection methods for contact tracing of diseases Temporal graphical neural networks for disease prediction Detection of small objects in ultra-high resolution images 3D reconstruction and recognition

• Robot Cooperation
• Human-Robot Interaction
• People Motion Behavior
• +۵ مورد دیگر

Anaís Garrell Zulueta is an Associate Professor at the Polytechnic University of Catalonia (UPC) and a Robotics Researcher at the Institut de Robòtica i Informàtica Industrial (CSIC-UPC) . She serves as Vice-Director of the Mobile Robotics and Intelligent Systems subline and supervises the RAIG - Mobile Robotics and Artificial Intelligence Group . PhD (2013): European Doctorate with highest honors from UPC B.S. in Mathematics (2006) from University of Barcelona Diploma d'Estudis Avançats (DEA) in Control, Vision, and Robotics from UPC Her research focuses on Human-Robot Interaction (HRI) and robot cooperation , particularly in urban environments . Key themes include: Explainable AI for robot transparency Human motion behavior prediction Socially aware navigation systems Collaborative transport robotics Autonomous last-mile delivery systems Cybernetic avatars and societal implications Recent projects (2023-2025) include: TORNADO: Foundation models for robots handling deformable objects HandIA: AI-based rehabilitation tools LENA: Lifelong navigation learning TRIFFID: First responder assistance robotics SOCIAL PIA: Cybernetic avatar modeling Scientific recognition includes: Second Prize for Best Spanish Robotics Thesis Best Paper Award Nomination (IEEE/RSJ IROS, 2009) As an advisor, she supervises: PhD students: Ferran Gebelli Guinjoan, Lavinia Hriscu, Edison Bejarano Final year projects: 8 students on topics like LLM-enhanced interaction and LiDAR SLAM systems She operates within the Institut de Robòtica i Informàtica Industrial (IRI) and collaborates with Carnegie Mellon University.

Markus Strohmaierمشاهده پروفایل

استاد

• Computational Social Science
• Data Science
• Machine Learning
• +۷ مورد دیگر

Markus Strohmaier is Professor and Chair of Data Science in the Economic and Social Sciences at the University of Mannheim, with affiliations as Scientific Coordinator at GESIS – Leibniz Institute for the Social Sciences and External Faculty Member at the Complexity Science Hub Vienna. His interdisciplinary work bridges computer science, economics, and the social sciences. University of Mannheim – Chair for Data Science in the Economic and Social Sciences GESIS – Scientific Coordinator for Digital Behavioral Data Complexity Science Hub Vienna – External Faculty Former Professor at RWTH Aachen University and University of Koblenz-Landau Previous Post-Doc and Visiting Roles at Stanford University, Xerox PARC, University of Toronto, and Graz University of Technology His research focuses on computational social science , algorithmic fairness , network science , and the modeling of human behavior using machine learning and large-scale data. He develops methods to analyze textual, relational, and emerging data types to understand socioeconomic systems and digital societies. The recent articles reflect a strong trend in studying inequality in algorithmic systems , governance in decentralized organizations (DAOs) , and psychological profiling of AI . His work spans high-impact journals like Nature and Scientific Reports , emphasizing fairness, transparency, and societal impact of data-driven technologies. Notable scientific contributions include: Editor-in-Chief of EPJ Data Science (2018–2022) Founding co-chair of the Computational Social Science section of the German Informatics Society He advises students and leads research projects on algorithmic fairness, digital governance, and behavioral modeling. His team engages in both fundamental methodological development and applied studies in real-world digital platforms. He has been involved in significant grants and collaborative initiatives around digital behavioral data and computational social science infrastructure. His lab and projects include the Algorithmic Fairness initiative and the interactive visualization tool Planets of Disparity , which explores how algorithms behave on different network structures. These efforts aim to enhance public understanding and technical scrutiny of algorithmic systems.

Chang-Hee Wonمشاهده پروفایل

استاد

• Tactile Sensing
• Optimal Control Theory
• Spectral Imaging
• +۷ مورد دیگر

Chang-Hee Won is a Professor in the Department of Electrical and Computer Engineering at the College of Engineering, Temple University. He leads the Control, Sensor, Network, and Perception (CSNAP) Laboratory and is actively engaged in research funded by the National Science Foundation, Pennsylvania Department of Health, and the Department of Defense. His research interests span tactile sensing , optimal control theory , spectral imaging , and dynamic sensing systems . His work integrates sensor technologies with machine learning for biomedical applications, particularly in cancer detection and tissue characterization. He has published over 120 peer-reviewed articles and secured multi-million dollar grants as principal investigator. The recent publications highlight a strong trend in applying tactile and imaging sensors with deep learning for medical diagnostics , especially in breast cancer and malignant melanoma classification. His research bridges control theory, sensor design, and AI-driven health technologies. He serves as a frequent reviewer for the National Science Foundation and sits on the National Institute of Health Biomedical Imaging Study Section. Reviewer, National Science Foundation panels Member, NIH Biomedical Imaging Study Section He has advised multiple graduate students including N. Rahman, V. Oleksyuk, and H. Ahn, who have co-authored recent journal publications. His research is supported by significant grants from federal and state agencies, as well as industry partnerships. He directs the Control, Sensor, Network, and Perception (CSNAP) Laboratory , which focuses on developing advanced sensor systems, control algorithms, and perception technologies for biomedical and engineering applications.

Joseph Welchمشاهده پروفایل

استادیار

• Respiratory Physiology
• Neural Control of Breathing
• Respiratory Muscle Fatigue
• +۷ مورد دیگر

Dr. Joseph Welch is an Assistant Professor in Respiratory Physiology at the School of Sport, Exercise and Rehabilitation Sciences, University of Birmingham , UK, a position he assumed in September 2022. His research focuses on the neural control of breathing, respiratory mechanics, diaphragm fatigue, and exercise physiology. Education: PhD in Kinesiology, University of British Columbia, Canada MRes in Sport and Exercise, University of Derby, UK BSc (Hons) in Sport and Exercise Science, University of Derby, UK Dr. Welch's research investigates how breathing adapts to physiological stressors such as exercise, disease, and hypoxia; how it interacts with other body systems; and its impact on human health and performance. His work spans both healthy individuals and clinical populations, including spinal cord injury. He is particularly known for his studies on respiratory motor plasticity induced by acute intermittent hypoxia and its therapeutic applications. His research aligns with the Rehabilitation and Motor Control theme and the Integrative Physiology of Exercise and Neuroscience and Brain Health groups. The recent publications indicate a strong focus on respiratory neuroplasticity, ventilatory control, and the therapeutic potential of hypoxia. His work integrates human and animal models, clinical populations, and advanced physiological assessments, reflecting a multidisciplinary approach to understanding breathing regulation and rehabilitation. Scientific Awards: Inaugural Review Prize 2023: The exercise hyperpnoea dilemma: A 21st-century perspective Dr. Welch actively supervises postgraduate research at both master’s and doctoral levels and teaches courses including Human Physiology & Exercise, Control of Human Movement, and Applied Exercise Physiology. He has collaborated extensively with leading researchers such as Professor Gordon Mitchell and Professor Bill Sheel. His laboratory work includes neurophysiological assessments and respiratory function testing, contributing to translational research in rehabilitation.

Daniel N Jacksonمشاهده پروفایل

استاد

• Software Design and Specification
• Design Methods
• Tools and Analysis
• +۹ مورد دیگر

Prof. Daniel N. Jackson is a Professor of Electrical Engineering and Computer Science at MIT, serving as Associate Director of the Computer Science and Artificial Intelligence Laboratory (CSAIL) and Director of the Middle East Education Through Technology (MISTI MIT-MEET) initiative. His research focuses on software dependability, formal methods, and design analysis, particularly through the Alloy framework. Jackson emphasizes lightweight formal methods to reduce development costs and enhance software safety, with applications in cybersecurity, autonomous systems, and safety-critical software. His work includes developing tools like Bluefish for declarative diagram composition and Riffle for reactive systems. He explores ethical software design frameworks to address dark patterns and advocates for concept-centric development. Jackson's contributions span academic publications, educational initiatives, and industrial collaborations, aiming to bridge formal methods with practical software engineering challenges. Recent projects involve certified control systems for autonomous vehicles, end-to-end dependability cases, and model checking for security flaws. His research integrates interdisciplinary approaches, combining programming languages, static analysis, and human-centered design principles.

Beau Schelbleمشاهده پروفایل

استادیار

• Human-AI Teaming
• Responsible AI
• Trust in Human-AI Systems
• +۱۲ مورد دیگر

Beau Schelble is an Assistant Professor in the Department of Industrial and Systems Engineering at the University of Tennessee, Knoxville, within the Tickle College of Engineering. He is the founding director of the AI and Robotics for Collaborative Systems (ARCS) Lab, where he leads interdisciplinary research on human-AI teaming, responsible AI, and team cognition. His work bridges human factors, systems engineering, and artificial intelligence, with applications in advanced manufacturing, healthcare, emergency response, and defense. Education: PhD in Human-Centered Computing, Clemson University, 2023 BS in Psychology, Clemson University, 2018 Dr. Schelble's research focuses on optimizing collaborative systems involving humans and AI. Key interests include trust development, situational awareness, shared knowledge, and ethical AI integration. He employs mixed-methods approaches—qualitative, quantitative, and computational—to study human-AI interaction in complex environments. His work has resulted in over 30 peer-reviewed publications in top-tier venues across human factors, HCI, and systems engineering. The 15 most recent articles reflect a strong trend toward ethical AI, explainability, autonomy adaptation, and team cognition in human-AI systems. Topics span healthcare applications, collaborative technologies, training methods, and emotional expression in AI teammates, demonstrating a broad yet cohesive research agenda centered on responsible and effective human-AI collaboration. Scientific Awards and Recognitions: NSF Research Traineeship (THINKER) Scholarship, August 2019 Multiple best paper awards and nominations (5 total) in human factors and systems engineering conferences Dr. Schelble actively mentors students and leads a dynamic research lab. He has secured research support through academic collaborations and professional engagement with IEEE, HFES, ACM, and IISE. His lab, ARCS, fosters innovation in AI-driven collaborative systems. Future work includes expanding frameworks for outpatient care, adaptive autonomy in healthcare, and deeper integration of human teaming principles into AI design. He continues to publish extensively and contribute to shaping the future of human-AI teaming.

Carme Torrasمشاهده پروفایل

استاد پژوهشی

• Robotics
• Artificial Intelligence
• Neurocomputing
• +۴ مورد دیگر

Carme Torras is a Research Professor at the Institute of Robotics and Industrial Informatics (IRI), a joint center of the Polytechnic University of Catalonia (UPC) and the Spanish National Research Council (CSIC), affiliated with the Faculty of Informatics of Barcelona (FIB). She leads the research group in assistive robotics, focusing on ethical, human-centered robotic systems. With over 400 scientific publications, she has made pioneering contributions in robotics, neurocomputing, and artificial intelligence. PhD in Computer Science – Universitat Politècnica de Catalunya Master in Computer Science – University of Massachusetts Bachelor in Mathematics – University of Barcelona Her research interests span robotics , artificial intelligence , neurocomputing , and ethics in digital technologies . She emphasizes the societal impact of AI, promoting ethical principles and public engagement. Her recent articles and literary works explore human-robot interaction, assistive systems, and the emotional dimensions of technology. The analysis of her recent publications reveals a strong trend toward interdisciplinary research combining technical innovation with ethical reflection. Her work integrates robotics with cognitive science, literature, and social responsibility, emphasizing open science and inclusive design. She advocates for an open laboratory model in assistive robotics to foster collaborative innovation. Nit de la Robòtica Award (2022) Pedrolo Prize for 'La mutación sentimental' Ictineu Prize for 'La mutación sentimental' and 'Enxarxats' Carme Torras has supervised 20 doctoral theses and led 17 European research projects, demonstrating significant leadership in both academic mentoring and large-scale collaborative research. She is deeply involved in science communication, using fiction to explore ethical dilemmas in AI. Her vision includes expanding open-access research infrastructure in robotics. She leads the assistive robotics research group at IRI, which focuses on developing intelligent robotic systems for healthcare and personal assistance. The team emphasizes ethical design, human-robot collaboration, and accessibility, contributing to both technological advancement and societal dialogue.