James Peters is Professor in Electrical and Computer Engineering at the University of Manitoba's Price Faculty of Engineering. His research explores computational proximity, digital topology, and computer vision, developing frameworks for signal analysis and shape detection. Key innovations include near set theory for perceptual similarity, optical vortex nerve analysis, and quaternion-based fMRI interpretation. He leads the Computational Intelligence Laboratory, focusing on topological data analysis for video tracking, neuroimaging, and pattern recognition. His 700+ publications span proximal Voronoï tessellations, fuzzy topology, and geometric realizations of cell complexes. Collaborations extend to Turkey, Italy, and India through visiting professorships.
William Penny is a Professor in Psychology at the University of East Anglia (UEA), School of Psychology. He joined UEA in 2017 after serving as a Professor at University College London (UCL). His research focuses on brain imaging methodologies, particularly analyzing fMRI and EEG data using Bayesian Inference, Dynamical Systems, and Probabilistic Machine Learning. He holds a BEng in Electrical Engineering (Nottingham University, 1988), MSc in Communication Engineering (Imperial College, 1989), and PhD in Artificial Neural Networks (Brunel University, 1993). He has led projects including a Wellcome Trust-funded initiative on brain imaging (2019–2024) and a study on brain function during perimenopause with Braincare Limited (2025–2026). His work spans collaborations in neuroimaging analysis, cognitive modeling, and translational neuroscience. His research outputs emphasize Bayesian methods, dynamic causal models, and computational neuroscience, with 84+ peer-reviewed articles. Key areas include cortical degeneration in Huntington’s disease, diet-cognition links, and neural mechanisms of decision-making. His lab, the UEA Brain Imaging Centre (UBIC), advances multimodal neuroimaging techniques. Professional affiliations include the Wellcome Trust Centre for Human Neuroimaging at UCL and international collaborations. No specific awards are listed, but his contributions to neuroimaging methodology are widely recognized.
Dr. Sarah Foley is a Lecturer in Developmental Psychology at the Moray House School of Education and Sport, University of Edinburgh, and a Fellow of Advance HE. She specializes in family dynamics, child wellbeing, and parenting arrangements in diverse family structures. Her research is funded by the Economic and Social Research Council (ESRC), including a current New Investigators Grant exploring shared parenting post-divorce and a prior Post-Doctoral Fellowship examining co-parenting experiences. Dr. Foley’s work bridges observational and quantitative methods to inform evidence-based family support strategies. Education : BA (Hons) Social and Political Sciences, University of Cambridge PhD in Developmental Psychology, University of Cambridge Research Focus : Her research examines parent-child relationships, family functioning, and child outcomes in non-traditional family forms (e.g., elective co-parenting, assisted reproduction). Key areas include post-separation family adjustment, parent mind-mindedness, and shared care arrangements. She collaborates with stakeholders like mediators and charities to translate findings into practical interventions. Awards : ESRC Post-Doctoral Fellowship ESRC New Investigators Grant Fellow of Advance HE Teaching & Supervision : Dr. Foley teaches courses on child development in education, including Child and Adolescent Mental Health and Wellbeing . She welcomes PhD students exploring family dynamics or developmental psychology. Labs/Teams : She leads the Parenting After Divorce or Separation Study , a multi-method project funded by ESRC to understand family life and children’s experiences in shared parenting arrangements post-separation. The team includes researchers like Rawan Abdelaal and collaborators across UK institutions.
Peter C.-H. Cheng is a Professor in the Department of Informatics at the University of Sussex, with a distinguished career spanning over three decades in the fields of diagrammatic reasoning, cognitive science, and visual representation systems. His research has significantly contributed to our understanding of how humans interpret and utilize visual representations for problem-solving and knowledge acquisition. Cheng's research interests focus on the cognitive aspects of visual representations, diagrammatic reasoning, representation systems theory, and mathematical knowledge representation. His work bridges cognitive science, computer science, and educational technology, exploring how different representational formats impact human cognition and problem-solving abilities. He has developed theoretical frameworks such as Representational Systems Theory (RST) and has investigated the cognitive properties of various diagrammatic notations including Feynman diagrams, truth diagrams, and algebra diagrams. His recent publications demonstrate a continued focus on the intersection of human cognition and machine intelligence, particularly in how humans and AI systems can collaboratively select and use appropriate representations for problem-solving. His work on Oruga, a system implementing Representational Systems Theory, shows his commitment to translating theoretical insights into practical applications. Expertise in diagrammatic reasoning and visual representation systems Development of theoretical frameworks like Representational Systems Theory Research on mathematical knowledge representation Investigations into cognitive aspects of visualization Applications in educational technology and AI systems Professor Cheng has maintained an active research program with consistent publications in top venues including CHI, CogSci, and Diagrams conferences. His work continues to influence both theoretical understanding of human cognition and practical applications in human-computer interaction and AI systems.
Christos Doulkeridis is a Professor at the Department of Digital Systems, University of Piraeus. Specializing in big data management, distributed systems, and mobility analytics, he has led projects such as CHOROLOGOS (ELIDEK-funded) and contributed to EU initiatives like datAcron and Track&Know. He holds Marie-Curie and ERCIM fellowships, and his work emphasizes energy-efficient data architectures and semantic trajectory analysis. Education: PhD in Informatics, Athens University of Economics and Business (2007) MSc in Informatics, Athens University of Economics and Business (2003) Diploma in Electrical & Computer Engineering, National Technical University of Athens (2001) Research Interests: Big data analytics, cloud computing, spatiotemporal query processing, mobility forecasting (e.g., traffic patterns, maritime monitoring), and semantic trajectory modeling. His work bridges theory with practical applications in smart cities and environmental sustainability. Awards: Winner of SemEval’17 Task4 (sentiment analysis) Best Paper Award at EuroVA’19 Michalis Dertouzos Award (2004) for Human Face of Computing Grants & Projects: Principal Investigator for CHOROLOGOS (semantic spatiotemporal data) Core contributor to datAcron (maritime data ontology) European projects: BigDataStack, RoadRunner (ARISTEIA II) Labs & Teams: Leads research teams developing frameworks like SPARTAN (semantic integration) and ARGO (trajectory prediction). Collaborates on open-source tools like ST_VISIONS (spatiotemporal visualization) and NoDA (unified NoSQL access).
Monica Castelhano is a Professor and Chair of the Cognitive Neuroscience Program in the Department of Psychology at Queen's University. She holds a B.Sc. from the University of Toronto (2000), M.A. (2002), and Ph.D. (2005) from Michigan State University. Her research focuses on visual attention and memory in real-world scenes, examining how perception, attention, and long-term memory interact. Using behavioral and eye-tracking methods, her work investigates how scene context influences attentional guidance and memory encoding. Research Interests: Her primary areas of investigation include the hierarchical structure of scene representations, the role of object-function in guiding attention, and the impact of spatial associations on visual search. She explores depth-based biases in scene processing and the integration of contextual and object-based cues during scene perception. Lab and Collaborations: Dr. Castelhano's lab employs eye-tracking technology to study gaze behavior in naturalistic environments. Her work bridges cognitive psychology and neuroscience, contributing to theories of scene perception and attentional mechanisms. Recent trends in her publications highlight interdisciplinary approaches, incorporating computational models and machine learning frameworks to analyze scene analysis processes. Advising and Grants: While specific grant details are not listed, her active research program indicates sustained funding support. No awards are explicitly mentioned in the provided materials. She supervises graduate students in experimental psychology and cognitive neuroscience.
Dr. Kirsten Pamperien is a Lecturer in the Department of Didactics of Social Sciences and Mathematics and Natural Sciences within the Faculty of Education at the University of Hamburg. She coordinates the university project of the PriMa measure, a program supporting mathematically gifted primary school children. Her research focuses on talent identification systems, progressive problem-solving tasks, inclusion strategies for migrant students, and classroom observation frameworks. Key areas include developing diagnostic tools for mathematical giftedness and evaluating enrichment program effectiveness. With a doctorate completed in 2021 on fostering mathematically gifted children, Pamperien received the Waxmann Poster Prize (2015) and was named Mathemacherin des Monats (2014) by the German Mathematical Society. Her publications demonstrate consistent focus on improving identification and support systems for gifted learners. Since 1999, she has coordinated the PriMa project, overseeing university math circles for grades 5-8 and conducting regular teacher trainings. Previously, she taught at Grundschule Turmweg (1999-2001) and GTS Osterbrook (1991-1999), developing mathematics workshops and serving as literacy consultant. Educational background includes mathematics and biology teaching qualifications (First State Examination, 1988) and psychological research on girls' mathematical development (1988-1989).
Kate Larson is a Professor at the David R. Cheriton School of Computer Science, University of Waterloo. Her research explores artificial intelligence with emphasis on multiagent systems, reinforcement learning, and AI applications for sustainability and climate challenges. She employs game-theoretic approaches to address coordination and cooperation in complex systems. Education Ph.D. in Computer Science from Carnegie Mellon University (2004), M.Sc. from Washington University in St. Louis (1999), and B.Sc. from Memorial University of Newfoundland (1997). Research Focus Professor Larson's work bridges theoretical AI and practical societal impacts. Key areas include: Designing cooperative AI frameworks for multiagent environments Developing value-alignment mechanisms for ethical AI Applying reinforcement learning to climate change mitigation Creating robust AI systems through game-theoretic guarantees Publication Trends Her recent publications (2024-2025) demonstrate strong focus on AI safety, game-theoretic foundations, and multimodal learning systems. Dominant themes include: algorithmic alignment techniques, multi-agent risk management, and interpretable AI architectures, with increasing emphasis on real-world climate and sustainability applications. Awards & Recognition No major scientific awards mentioned in source materials. Research Infrastructure No specific labs or teams detailed in available information.
Stefan Bruckner is Professor of Visualization at the University of Bergen, specializing in biomedical visualization, volume rendering, and visual data exploration. His work develops novel techniques for analyzing complex scientific datasets across meteorology, medicine, and materials science. Dr. Bruckner's research group develops interactive visual analytics tools for weather forecasting, medical diagnostics, and ensemble data analysis. His methodological innovations include GPU-accelerated rendering, visual parameter exploration, and uncertainty visualization. He received the 2011 Eurographics Young Researcher Award for contributions to illustrative visualization. Professional service includes program committee roles for IEEE VIS, Eurographics, and ECRTS conferences. His pedagogical contributions span visualization, computer graphics, and programming languages at institutions including École normale supérieure and École polytechnique.
Professor Lars Chittka holds the position of Professor of Sensory and Behavioural Ecology at Queen Mary University of London, within the School of Biological and Behavioural Sciences. His research focuses on animal cognition, sensory systems, pollination ecology, and social insect behavior, with a particular emphasis on bees as model organisms. Chittka’s work bridges sensory physiology, learning psychology, and evolutionary ecology, exploring how sensory systems and cognitive processes function in natural foraging environments. His lab investigates topics such as insect color vision, navigation, and the welfare implications of insect consciousness. Key areas of research include the cognitive abilities of bees, including their capacity for social learning, tool use, and decision-making. Chittka has pioneered studies on how bees perceive and interact with their environment, including the role of floral signals and the impact of environmental factors like nectar quality and nociception. His team uses field studies, computer-controlled behavioral tests, and phylogenetic analyses to address these questions. Chittka supervises a range of PhD and postdoctoral researchers, including current students such as Joanna Brebner and Yonghe Zhou. His work has been featured in high-impact journals and media outlets like Science and Nature , and he has contributed to public engagement through articles and commentary on topics like insect welfare and conservation. Chittka’s research also extends to collaborations with engineering and computer science groups, such as the NimbleAI project exploring neuromorphic computing inspired by insect vision. His lab is affiliated with the Centre for Brain and Behaviour and the Centre for Biodiversity and Sustainability, emphasizing interdisciplinary approaches to understanding animal behavior and cognition.
Christian Dorner is a Professor of Mathematics Education and Head of Studies at the Department of Mathematics Education, Pädagogische Hochschule Steiermark. His work focuses on procedural knowledge development, financial mathematics in education, and student perspectives in mathematics teaching. He leads curriculum design initiatives and assessment frameworks for secondary mathematics education. Research interests include: Procedural knowledge measurement and deficiencies Integration of technology in mathematics classrooms Financial literacy education Student-centered lesson analysis Recent work emphasizes cross-national comparisons of financial education systems and the role of technology in procedural skill development. His research often involves collaborative projects with Austrian secondary schools and teacher communities. Notable contributions include the AmadEUs project analyzing classroom dynamics from student perspectives, and curriculum materials like 'Mathematik verstehen' series integrating GeoGebra tools. His work bridges theoretical educational research with practical classroom implementation.
Benjamin Ralston is an Assistant Professor at the University of Saskatchewan College of Law, where he teaches Environmental Law, Administrative Law, and courses on Indigenous peoples and Canadian law. He also instructs a graduate-level Environmental Law and Policy course for the School of Environment and Sustainability. His educational background includes: LLM (Otago, 2014) with distinction, focusing on marine spatial planning and Indigenous rights Juris Doctor (UBC, 2010) Bachelor of Arts (UBC, 2007) Ralston's research centers on the intersection of environmental assessment practices and Indigenous rights in Canada, with particular emphasis on constitutional law, Aboriginal title, and reconciliation frameworks. His work critically examines consultation policies, UNDRIP implementation, and the application of Gladue principles in sentencing. Through extensive publications, he analyzes how legal systems can better accommodate Indigenous governance structures and rights recognition. His scholarly output demonstrates consistent focus on Indigenous environmental governance, constitutional interpretation of Aboriginal rights, and systemic reforms in criminal justice. Recent publications increasingly address practical implementation challenges of reconciliation frameworks in provincial policy contexts. Ralston maintains active legal practice credentials through the Law Society of Saskatchewan and previously the British Columbia bar. His professional experience includes significant work on major Indigenous rights cases such as the Fraser River Sockeye Salmon Inquiry, Northern Gateway Pipeline reviews, and Coastal GasLink Pipeline injunctions. He currently serves in a tenure-track position at the College of Law after holding various academic roles at the University of Saskatchewan since 2014, including term appointments as Assistant Professor, research positions at the Indigenous Law Centre, and teaching in the Nunavut Law Program and Kanawayihetaytan Askiy Program.
Alexei Efros is a Professor of Electrical Engineering and Computer Science at UC Berkeley , affiliated with the Berkeley Artificial Intelligence Research Lab (BAIR) . Previously, he was a faculty member at the Robotics Institute, Carnegie Mellon University , and a postdoc at Oxford University with Andrew Zisserman. His work spans data-driven computer vision , self-supervised learning , and applications to computer graphics , computational photography , and human-AI interaction . Research Themes : Self-supervised visual learning 3D scene understanding Vision-language multimodal systems Teaching : CS 180/280A: Intro to Computer Vision CS 280: Graduate Computer Vision CS 294-192: Visual Scene Understanding Recent Publication Trends : Focus on diffusion models and self-guidance 3D perception and rendering Interpretability of vision-language models Temporal and sequential learning Scientific Collaborations : Extensive partnerships with institutions like MIT, CMU, Stanford, and NVIDIA Mentorship of PhD students now at TTIC, OpenAI, Anthropic, and academia Labs & Teams : BAIR Lab (UC Berkeley) Collaborations with Adobe Research, Google, and NVIDIA
Natan Rubin is a faculty member in the Computer Science Department at Ben-Gurion University of the Negev, Beer-Sheba, Israel, where he has been conducting research in combinatorial and computational geometry since 2014. He is the principal investigator of a 5-year ERC Starting Grant project titled 'Combinatorial Aspects of Computational Geometry' (CombiCompGeom), which supports graduate students and postdocs in geometric algorithms and structures. Ph.D., Tel Aviv University, 2012 Advisor: Prof. Haim Kaplan and Prof. Micha Sharir His research focuses on fundamental problems in computational geometry, including geometric transversals , epsilon-nets , Voronoi diagrams , Delaunay triangulations , and intersection patterns of geometric objects . He has made significant contributions to the understanding of combinatorial bounds in geometric settings, such as resolving the Richter-Thomassen conjecture for pairwise intersecting Jordan curves and improving long-standing bounds on weak epsilon-nets. The recent publications reveal a consistent trend toward improving asymptotic bounds in high-dimensional and planar geometric configurations, with a strong emphasis on combinatorial methods and topological reasoning. His work often intersects with extremal combinatorics and discrete geometry, particularly in analyzing crossing and touching structures in planar graphs and families of convex sets. His scientific recognition includes: Best Paper Award at FOCS 2013 Best Paper Award at SoCG 2012 Rubin actively contributes to the academic community through service, having organized major workshops such as SODA 2018 and SoCG 2022, and hosting international researchers. He collaborates widely with leading figures in the field, including Pankaj Agarwal, János Pach, Micha Sharir, and Haim Kaplan. Though no formal list of students is provided, his ERC-funded project explicitly advertises multiple graduate and postdoctoral positions, indicating active mentorship. He is also involved in organizing international workshops and fostering collaboration within Israel’s strong computational geometry community, including researchers at BGU, Tel Aviv, and Jerusalem. His research is supported by competitive grants and involves the development of robust kinetic data structures and stable geometric graphs, with applications in dynamic environments and algorithmic stability.
Dr Constantine Manolchev is a Senior Lecturer in the Business School at the University of Exeter and Programme Director for the BSc Business (Penryn) degree. He holds administrative roles including Widening Participation Lead and Equality, Diversity & Inclusion Lead for the Business School. His research focuses on ethical organizational structures, precarious work conditions, workplace bullying/harassment, and circular economic systems. He also explores pedagogical applications of generative AI in education. Education: PhD in Business & Management (Plymouth University, 2016), multiple postgraduate certificates in research methods, HRM, and academic practice (Open University/Plymouth University) Professional Qualifications: Senior Fellow of the HEA His research has included a Cornwall clean growth report (2022) commissioned by the UK Government and a follow-up study for Innovate UK (2023). He has published widely on workplace ethics, circular economy transitions, and AI in education, with notable contributions to understanding labor precarity and organizational learning in remote teams. Key Research Themes: Sustainability policy, organizational justice, and education innovation Dr Manolchev’s work bridges academic research and practical policy, with particular focus on regional economic development and socially responsible management practices.
