Thus far, for years, I have been addressing mathematical aspects of computer sciences. The main fields are

• Universal data compression and Kolmogorov complexity
• Bayesian statistics and MDL principle
• Learning Bayesian network structure from data
• Markov chain analysis on GAs
• Algebraic curve cryptography

I have strong background on information theory, Bayesian statistics, Kolmogorov complexity, computation theory, Markov chain, algebraic geometry, number theory, etc. However, my interest is in their applications to computer sciences. Except data compression and cryptography, I have been engaged mostly in arificial intelligence. (I found that universal data compression is strongly connected to learning stochastic rules.)