Problem Solver
Igor Balaz
Areas Igor Balaz is Knowledgeable in:
My primary interest is modeling and development of systems that mimic real organisms in their ability to evolve and autonomously develop novel functional traits. In designing such systems I use combination of very abstract mathematical tools (like category theory) and more analytical approaches (like complex network analysis).
I am also very interested in both self-organization and agent-based systems.
I am also very interested in both self-organization and agent-based systems.
Techniques Igor Balaz Uses:
First phase is always information mining and survey of available literature. After that I write a short review of the field of interest in order to consolidate my understanding of the problem. Next phase is combination of planning, brainstorming and subject mapping, until I reach satisfactory outline of the solution. Practical realization depends on the problem and of course skills I am familiar with (listed above).
Igor Balaz's Problem Solving Skills:
- published papers in peer-reviewed journals
- Mathematical skills (abstract algebra, lattices, category theory, nonlinear dynamics)
- programming in Python
- analysis of complex networks
Igor Balaz's Problem Solving Experience:
- I developed Evolvable Strategy to Assimilate Unstructured Information; InnoCentive award - Challenge #9932821 “Strategy to Assimilate Unstructured Information” (February 2012)