Mathematics; Computer Science; Software Engineering; Artificial Intelligence; Neural and Cognitive Science.
I am trying to combine theoretical research and practical applications.
My theoretical interests concentrate in applications of continuous mathematics to computing - domains for denotational semantics give the prime example of such applications. Another important area of such applications is realistic neural networks.
My practical interests are in programming language design and implementation, in methods and tools for software engineering, and in audio-visual computer-based cognitive tools.
By the end of 2015, a degree of convergence between my theoretical interests and my practical interests have emerged. We finally have a model of computation which allows us to continuously deform programs and, moreover, to represent large classes of programs by matrices of real numbers.
It turns out that the resulting dataflow matrix machines are a fairly powerful generalization of recurrent neural networks. A one-page overview of dataflow matrix machines (November 25, 2016).
The reference paper on this subject is currently Dataflow Matrix Machines and V-values: a Bridge between Programs and Neural Nets (December 2017).
If you are interested in collaboration please let me know - I am always looking for people to work with.
An interdisciplinary and collaborative research agenda related to dataflow matrix machines: dmm-collaborative-research-agenda.pdf (8 pages, March 2021):
Gay mathematicians, queer stuff, eastern philosophy, Puschino - a Biological Center in Moscow Region, Jewish intellectual community in Russia, etc.