Algorithmic Information Theory for Machine IntelligenceApply
We recently developed numerical and computational techniques to use algorithmic information theory (AIT) to the analysis of networks. For publications see google scholar(https://scholar.google.com/citations?hl=sv&user=_DUppAgAAAAJ&view_op=list_works&sortby=pubdate).Subprojects include to- Develop python packages for AIT analysis of large-scalenetworks- Develop new AIT network embedding algorithms- Analyze Convolutional Networks a representational learning usingAIT- Quantify and benchmark AIT network analysis with othertechniques- Large-scale computation of AIT networks using a supercomputer(Shaheen)Newand improved numerical approximation of algorithmic complexity using massive computations of Turing Machines on Shaheen(supercomputer)
Program - Computer Science
Division - Computer, Electrical and Mathematical Sciences and Engineering
Field of Study - Computer Science, Applied Mathematics
Desired Project Deliverables
Individual projects will be tailored and narrowly designed from the above palette according to interest of the student, technical proficiency, and level of study. We expect you (a) to bring enthusiasm, creativity, and hard work, (b) give lab seminars on your work, and (c) produce a final written report. In return this facilitates your critical thinking, presentations skills, and scientific writing. Your research, in collaboration and with support of team members, may lead to scientific publications. You will also get a good hands-on perspective at the frontier of machine intelligence and its applications in an interdisciplinary research group and environment.