I'm a computer scientist, software engineer and more broadly a "hacker" in its classical sense.I have passion for building absolutely minimal slim software designs that do the required task in 1/4th of time expected using a couple of times less resources then a typical "off the shelf" solution does. I love investigating the quality of code and digging down into libraries/systems where I usually find error-prone design/patterns, bugs and/or performance problems. Lints, disassemblers, profilers, stress tests and fuzzing are my usual guides. With that being said I drift away from being perfectionist and try to stay pragmatic. If say a program is going to be used once in a year and meets expected deadlines, there is typically no point in making it faster, fixing memory leaks, refactoring it to death or otherwise burning hours of work on it. Proportional response, hacking our way through to meet the deadline, carefully allocating time on the critical path are essential skills in my book.Other activities that I wholly enjoy is parsing, pattern-matching and extracting the knowledge out of a pile of mess also known as BigData these days. Aside from well-known stuff attributed to Machine Learning I posses knowledge of (sadly) relatively obscure algorithm called JSM that is actually superior in certain areas to _all_ of the popular models we have today. Though JSM implementations are far and few between, and most of them won't pass basic expectations in usability and quality.