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Rozenn DahyotView profile

Professor

• Computer Vision
• Machine Learning
• Digital Signal Processing
• +4 more

Rozenn Dahyot is a Professor of Computer Science at Maynooth University within the Faculty of Science & Engineering. She previously held roles as Assistant and Associate Professor in Statistics at Trinity College Dublin (2008-2021) and Lecturer in Computer Science (2005-2008). Her research interests bridge Digital Signal Processing, Computer Vision, Machine Learning, and Statistical Analysis. She organized the European Signal Processing Conference (EUSIPCO2021) in Dublin and served as President of the Irish Pattern Recognition and Classification Society (IPRCS) from 2014-2020. Her work spans topics like semantic scene understanding, CNN compression, and medical image segmentation. Key contributions include advancements in graph-based image analysis, reinforcement learning optimization, and AI-driven systems for disaster management. Dahyot is a member of IEEE, ACM, and EURASIP, contributing to both academic and industrial collaborations.

• Perceptually guided graphics
• Virtual characters and crowds
• Virtual reality
• +4 more

Cathy Ennis is an Assistant Professor in the Department of Computer Science at Maynooth University, Ireland, specializing in perceptually guided graphics and virtual reality. She is actively involved in research and teaching, with affiliations to the ADAPT Centre and D-REAL SFI Centre for Research Training. Education: BEng in Electronic Engineering, Maynooth University MSc in Cognitive Science, University College Dublin PhD in Computer Graphics, Trinity College Dublin PG Dip in Higher Education Teaching and Learning, DIT Research Interests: Dr. Ennis's research centers on creating realistic virtual humans and crowds, exploring multisensory perception in VR, and applying these technologies in serious games and interactive systems. Her work integrates AI, HCI, and immersive technologies to enhance user engagement and learning. Her recent publications reflect a strong focus on virtual character realism, VR-based education, and machine learning applications in animation and interaction. Notable themes include speech-animation realism, cultural VR experiences, and reinforcement learning for character control. Scientific Awards: Best Paper Award, IEEE VR 2022 Teaching and Supervision: Dr. Ennis currently teaches CS401 (Machine Learning and Neural Networks) and CS261 (Multimedia Technology). She is actively seeking PhD students and collaborators interested in VR, games, and virtual characters, particularly using machine learning for gesture generation and engagement. Labs and Teams: She is a Funded Investigator with the ADAPT Centre and D-REAL SFI Centre for Research Training, contributing to interdisciplinary research in AI, HCI, and immersive technologies.

Cathy EnnisView profile

Lecturer

• Plausible Animation
• Virtual Games
• Perceptually-driven Computer Graphics
• +2 more

Dr. Cathy Ennis is a Lecturer in the School of Computer Science at Technological University Dublin (TU Dublin), where she has taught for 5 years. She delivers modules at undergraduate and postgraduate levels and supervises student research projects across all academic levels. Education: PhD in Computer Science, University of Dublin, Trinity College (2010) – Thesis: Plausible Crowd and Group Formations MSc in Cognitive Science, University College Dublin (2007) – First Class Honors BEng in Electronic Engineering, NUI Maynooth (2005) – Second Class Honors, Grade One Her research explores perceptually-driven techniques for virtual character animation, focusing on behavioral plausibility in game environments. Key interests include computational models for crowd simulations, graphics optimization for human perception, and applied gaming solutions for educational/training contexts. She integrates principles from computer graphics, cognitive science, and electronic engineering in her work. Dr. Ennis currently supervises or co-supervises multiple PhD candidates and guides MSc dissertation students. She leads research within the Applied Social Computing Research Group, concentrating on interactive virtual environments.