Nouf Abukhodair
Nouf’s background is in Computer Science, she is interested in AI, Image Processing and Visual Perception. Her current research is looking at computational creativity, understand how Deep Learning AI systems can understand visual art. Her work uses modern AI machine learning systems to understand goals and processes, to dynamically adapt the system for best results for art, entertainment and health applications.
Contact: nouf_abukhodair_2@sfu.ca
Position: PhD Researcher
Research
Deep Learning AI Creativity For Visuals / Words
Using Cognitive Science as a basis for our work, we attempt to model aspects of human creativity in AI. Specially we are using Neural Networks (and evolutionary systems) in the form of Deep Learning, CNNs, RNNs and other modern techniques to model aspects of human expression and creativity.
Cognitive (AI) Based Abstraction
What is abstraction? Can you use AI techniques to model the semantics of an idea, object, or entity, where that understanding allows for abstraction of the meaning? We use several AI techniques including genetic programming, Neural Nets and Deep Learning to explore abstraction in its many forms. Mainly here in the visual and narrative arts.
We will combine our AI work in Empathy based modeling for AI Character Agents with our Deep Learning-based Creativity system (see papers and work in PDF) that realizes a fine art portrait from sitters.
Publications
Empathic AI Painter: A Computational Creativity System with Embodied Conversational Interaction
Conference Proceedings: Proceedings of Machine Learning Research (NeurIPS 2019 Competition and Demonstration Track), 2020
10 Pages