Mathematics; Computer Science; Software Engineering; Artificial Intelligence; Neural and Cognitive Science.

My resume.

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.

- My papers in computer science
- A contribution to quantum gravity research
- My papers in computational chemistry
- A Poor Man's Russificator
- Some open problems in domain theory (link disappeared, but a PDF file can be obtained here)

e-mail: bukatin@cs.brandeis.edu