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Steve DiPaola, active as an artist and a scientist, is a professor/researcher at Simon Fraser University, Steve directs the I-Viz Lab ( ~10 computer-based PhDs, Postdocs, Grads – 72% women) which uses cognitive-based Artificial Intelligence and Virtual Reality techniques and computational modeling. He parallels a professional art career. He came to SFU from Stanford University and before that spent 10 years as a senior researcher at NYIT Computer Graphics Lab, an early pioneering lab in high-end 3D techniques. He has over 100 computer science-based publications patents and books and held senior positions at Electronic Arts and Saatchi & Saatchi Innovation and has consulted for HP, Microsoft, Adobe, and the Institute for the Future. His artwork has been exhibited internationally including the A.I.R. Tenderpixel, and Tibor de Nagy galleries in NYC/London as well as museums MoMA, Tate, Whitney Museum of Art, and the Smithsonian. He co-curated the first computer art show in a major NYC gallery in 1988 and had one of the first one-man travel shows of his AI art.
Publications :: News :: CV :: Media :: Art Exhibitions
See Art Site or Research Site for more information.
Teaching & research interests
- Artificial intelligence, computer graphics and interaction
- Computational systems for expression, movement, gesture and creativity
- Gaming, narrative and interaction systems
- Avatar, character and computer facial animation and AI
- Cognitive science approaches to computer modeling
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Contact: Steve DiPaola
Professor :: Simon Fraser University :: Vancouver, B.C., Canada
sdipaola [at] sfu.ca
Director, iVizLab :: iViz Laboratory Surrey Campus: 2945
Latest Research Projects
AI Affective Virtual Human
Our affective real-time 3D AI virtual human project with face emotion recognition, movement recognition and full AI talking, gesture and reasoning.
BioSensing 2D / 3D / VR Systems
Our lab has extensive experience in using different sensing technology including eye tracking and facial emotion recognition (DiPaola et al 2013), as well as gesture tracking and heart rate and EDA bio sensing (Song & DiPaola, 2015) to affect generative computer graphics systems.
Bringing together an interdisciplinary team, we created a wholly new AI technique to anonymize interview subjects and scenes in regular and 360 videos to create a technique that would be much better at conveying emotional and knowledge information than current anonymization techniques.
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.