Robert B. Lisek

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Most Recent Affiliation(s):

  • Institute of Advanced Study CEU and Institute for Research in Science and Art

Other Affiliation(s):

  • City University of New York
  • Fundamental Research Lab


  • Austria


  • SIGGRAPH Asia 2020

    I have an education in art as well as mathematics. I research at the truly cutting-edge vanguard of electronic arts, music and performance. The areas of my activity covering conceptual art, media arts, immersive art, storytelling and performance with a critical consideration of social problems. I am a pioneer of art based on Artificial Intelligence and Machine Learning. I’m using Deep Reinforcement Learning and Recurrent Neural Networks techniques. My projects deal with human-machine interaction and building of new interactive interfaces. It is a multi-agent AI development process. I research also new modes of interaction that integrate physiological human sensing, gesture and body language, and smart information analysis and adaptation. I deal also with spatial sound and video synthesis. My approach is based on meta-learning. Meta-learning goes by many different names: learning to learn, multi-task learning, transfer learning, etc. People easily transfer knowledge acquired in solving one task to another more general task. This means that we naturally recognise and apply previously acquired knowledge to new tasks. The more the new task is related to our previous experience, the easier we can master it. In contrast, popular machine learning algorithms deal with individual tasks and problems. Transfer learning attempts to change this by developing methods to transfer knowledge acquired in one or more source tasks and using them to improve learning in a related target task. The goal of transfer learning is to improve learning in the target task by using knowledge from the source task. When an artificial agent applies knowledge from one task to another, it is helpful to map and embedded the characteristics of one task to the characteristics of another. Techniques enabling knowledge transfer will constitute significant progress in AI and immersive art.

    SIGGRAPH 2005

    Robert B. Lisek is an artist, mathematician and a founder of FUNDAMENTAL RESEARCH LAB; he is involved in the number of projects focused on alternate art strategies and artificial intelligence. He is also a scientist at Department of Logic of Wroclaw University specialising in the theory of partially-ordered sets. His projects include among others: FLXTXT- Red Gate gallery & Panetary Collegium, Beijing, FLEXTEXT- CiberArt Bilbao Congres , Medi@terra – Byzantine Museum, Athens, RunMe-Moscow, FLEXTEXT – ACA Media festival,Tokyo {Jury Recomended Work/Interactive Art}; STACK – ISEA 02, Nagoya ; SSSPEAR -17th Meridian, WRO Center for Media Arts, Wroclaw; HAPPY NEW FEAR – FluxusOnline, New Horizonte; ODER- Medienturn – Graz, Kunstpalase – Dusseldorf, Fournose Center – Athens, and Graz, Paris, Tokyo, Palermo, Istambul.

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