Matthieu Perrin is an Associate Professor at the University of Nantes, affiliated with the GDD team at LS2N (Laboratoire des Sciences du Numérique de Nantes). He holds a PhD from the University of Nantes (2016), advised by Claude Jard and Achour Mostéfaoui. His research focuses on distributed computing, particularly message-passing systems, weak consistency models, and distributed algorithms. He has co-advised PhD students including Grégoire Bonin and supervised undergraduate projects like Damien Maussion's work on weak consistency enforcement. Key contributions include seminal work on differentiated consistency for gossip protocols, causal broadcast algorithms, and extensions of the Herlihy wait-free hierarchy to multi-threaded systems. His publications span journals like IEEE TPDS and conferences such as EuroSys and PODC. Perrin's work bridges theoretical foundations (e.g., consistency models) with practical implementations (e.g., state-machine replication for large-scale systems). He collaborates widely, including postdoctoral work at Technion and IMDEA Software Institute.
Mariella Dimiccoli is a Científica Titular (equivalent to Professor) at the Institute for Robotics and Industrial Informatics (IRI), a joint research center of the Spanish National Research Council (CSIC) and Universitat Politècnica de Catalunya (UPC). She is actively involved in cutting-edge research in computer vision, robotics, and multimodal AI, with a focus on egocentric vision, action recognition, and temporal video understanding. Position: Científica Titular (Professor) Institution: IRI, UPC-CSIC Research Subline: Perception and Manipulation Email: mdimiccoli@iri.upc.edu Her research interests center on enabling machines to understand human actions and interactions through visual and auditory signals. She works extensively on unsupervised and weakly supervised learning methods for video analysis, particularly in untrimmed and egocentric videos. Her work integrates insights from robotics, machine learning, and cognitive science to build systems capable of perceiving and predicting human behavior in dynamic environments. The recent publications highlight a strong trend in temporal modeling of video data, multimodal fusion (especially audio-visual), and explainable AI. Her work spans from fundamental representation learning to applied robotics, with a consistent focus on grounding AI models in real-world sensor data and human behavior. She actively supervises graduate students and leads significant research projects such as AWESOME and SAFEDYP025, which aim to model temporal structures in videos and enable safe autonomous planning through episodic memory. These projects reflect her leadership in integrating prior knowledge into AI systems for long-term autonomy. PhD Student: Elena Belén Bueno Benito Master's Student: Xabier Blázquez González Her research is supported by national and European funding, including participation in the RAMON LLULL: AIRA Postdoctoral Programme and leadership in projects like AWESOME and GreenVAR. These grants underscore her role in advancing AI and robotics in Spain and Europe. Mariella Dimiccoli leads research within the Perception and Manipulation subline at IRI, contributing to the development of intelligent robotic systems that can perceive, interpret, and interact with humans and environments through multimodal sensing and learning.
Dr. Carla Ferreira is a Researcher at NOVA University Lisbon, Portugal. She actively contributes to academic communities as a committee member and session chair in conferences like POPL, ECOOP, and SPLASH. Her work bridges distributed systems, low-code development, and program verification. Researcher at NOVA University Lisbon Conference committee roles: POPL, ECOOP, SPLASH, MODELS, PLDI Research interests: distributed systems, low-code development, invariant verification Carla’s work focuses on ensuring correctness in distributed systems through coordination-free designs and replicated data types. She has explored low-code templates for safe application composition and automated scaling of sequential systems. Her recent contributions include consistency models for weakly consistent databases and educational approaches for teaching distributed verification with TLA+. She has authored key works on ECROs, OSTRICH, and VeriFx frameworks. Her publications span from 2016 to 2025, reflecting ongoing contributions to system design and verification. Carla Ferreira can be reached via her personal website at http://ctp.di.fct.unl.pt/~cf/ , though no direct email addresses are publicly listed in the scraped data.
Miguel Ángel Cazorla Quevedo is a Professor in the Department of Computer Science and Artificial Intelligence at the University of Alicante's Higher Polytechnic School. He has served as a professor since 1995, progressing through all academic ranks to become a full professor in 2017. His administrative roles include being Director of the University Institute of Computer Research, Coordinator of the Robotics Engineering degree program, and Director of the Artificial Intelligence Master's program. Dr. Cazorla holds a PhD in Computer Engineering (2000) and a Computer Engineering degree (1995), both from the University of Alicante. His research has consistently focused on computer vision with applications to robotics. Over his career, he has expanded into 3D data processing, deep learning applications across multiple domains including medical imaging and traffic analysis, and more recently, Large Language Models. His current research emphasizes social robotics, applying these technologies to assist dependent individuals. His publication record includes over 70 JCR-indexed articles (more than 30 in Q1 journals) and over 100 conference papers. Recent publications show a strong focus on holographic classroom integration, depth estimation, adversarial attacks in neural networks, medical image analysis, and educational applications of AI. His work bridges computer vision, robotics, deep learning, and practical applications in healthcare, education, and transportation. Senior Member of IEEE Dr. Cazorla has supervised 22 doctoral theses and 198 undergraduate/master's theses in the last five years. He serves as Principal Investigator on multiple national research projects including 'Asistente para Personas con TEA y fobias mediante Realidad Virtual y Aumentada' (2023-2026) and 'MEEBAI: A Methodology for Emotion-Aware Education Based on Artificial Intelligence' (2022-2025). He also leads several technology transfer projects with companies like CYPE SOFT and EMBENTION. He leads the Robotics, Vision and Intelligent Technologies (RoViT) research group within the University Institute of Computer Research, which focuses on applying computer vision and AI to real-world problems in social robotics, healthcare, education, and industry.
