Professor Alexey S. Potapov
Potapov, Ph.D., D.Sc. is Principal Investigator of the
AIDEUS project aimed at creation of (safe) AGI. He is also Head of
Lab of Learnable Image Analysis Systems at Vavilov State Optical
Institute (Russia) and Professor of Computer Photonics and Videomatics
NRU ITMO (Russia), where he gives lectures on
artificial intelligence, computer vision, and machine
Alex authored Extending Universal Intelligence Models with Formal Notion of Representation, Differences between Kolmogorov Complexity and Solomonoff Probability: Consequences for AGI, Cognitive Bias for Universal Algorithmic Intelligence, Principle of Representational Minimum Description Length in Image Analysis and Pattern Recognition, New Paradigm of Learnable Computer Vision Algorithms based on the Representational MDL Principle, Theoretic-Informational Approach to the Introduction of Feedback into Multilevel Machine-Vision Systems, Information-Theoretic Approach to Image Description and Interpretation among others. He also authored two books in Russian — Artificial Intelligence and Universal Reasoning and Pattern Recognition and Machine Perception: General Approach on the Base of the Minimum Description Length Principle.
He has participated in the creation of a number of such narrow AI systems as “Roboking Dual Eye” with the invention of several patents, but his main research interests are focused in the area of artificial general intelligence, algorithmic information theory, and strong machine learning.
Alex earned his diploma in astronomy and mathematics from Saint-Petersburg State University in 2002, his Ph.D. in optoelectronic systems from the Vavilov State Optical Institute in 2005, and his D.Sc. in computer science from the National Research University of Information Technology, Mechanics, and Optics in 2008.