FOCUS   /   Research Areas.  TOPICS.

Research in Artificial and Human Intelligence aims to bring together and advance a novel & unique combination of research methodologies, academics and communities encompassing artificial intelligence, cognitive science, neuroscience, psychology & human development, human-computer interaction, and design science. In addition to pursuing its core scientific agenda, this line of inquiry also creates a discussion point for the development of interdisciplinary research, projects, collaborations, and other international people-exchange initiatives addressing the Confluence of Cognition, AI, Interaction, and Design.  Dribbble


INSTITUTE 2020 courses encompass:

Emerging research-driven themes of high interest to be addresses in the institute include:


The insititute emphasises:  (i). ``In-the-wild'' ecologically valid naturalistic (embodied multimodal interaction) settings;  (ii). Bottom-up interdisciplinarity, e.g., combining methods in AI and cognitive psychology; and  (iii) . Design-thinking as a human-centred perspective for engineering (``usable'') cognitive technologies aiming to assist, empower, and augment human capability.

The institute addresseses core topics of interest from formal, cognitive, computational, engineering, empirical, psychological, and philosophical perspectives. Indicative topics and applications in focus include:

  • knowledge representation - semantics
  • reasoning about space, actions, and change
  • commonsense reasoning
  • computational cognitive systems
  • embodied visuoauditory perception
  • declarative spatial reasoning
  • deep (visuo-spatial) semantics
  • integrated reasoning and learning
  • non-monotonic reasoning
  • visual computing computing
  • cognitive vision
  • commonsense scene understanding
  • semantic question-answering with image, video, point-clouds
  • concept learning and inference from visual stimuli
  • explainable visual interpretation
  • learning relational knowledge from dynamic visuo-spatial stimuli
  • knowledge-based vision systems
  • ontologically modelling for scene semantics
  • motion representation and reasoning (e.g., for embodied control)
  • attention, anticipation, action
  • declarative reasoning about space and motion
  • computational models of narrative
  • narrative models for storytelling (from stimuli)
  • vision and linguistic summarization (e.g., of social interaction, human behavior)
  • vision, AI, and eye-tracking
  • high-level visual perception and eye-tracking
  • egocentric vision, perception
  • visual perception and embodiment
  • biological and artificial vision
  • biological motion
  • visuoauditory perception
  • multimodal media annotation tools

  • Autonomous driving
  • Embodied cognitive vision for robotics
  • Social interaction in cognitive robotics
  • Architectural design cognition
  • Clinical diagnostic technologies
  • Social signal processing
  • Technology-assisted learning
  • Digital media design
  • Visual art design
  • Vision and social media
  • Cognitive moving image studies
  • Visual art, cultural heritage, fashion
  • Vision and VR, AR
  • Vision for psychology / behavioural studies
  • Vision for social sciences, humanities
  • Vision for industrial applications
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