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From Jonathan D. Lettvin

Professional Info	Samples of My Work	Preferred Languages	Preferred Platforms	Antivirus Patents	Neural Patents	Social Media	Contact Info
resumé LinkedIn	github repos Writing Samples	Python C++	Unix linux	5559960 5826012	7796173 7952626	google+ facebook	email wikipedia

Big Data Mathematics

I attack/solve "insoluble" Big Data problems and generate unexpected successes (see my resumé for examples). I have loved big data since before it was named. I use novel mathematical methods where databasing would obscure features. I think about it, visualize it, detect events in it, and discover monetizable value in it where others see only noise.

To achieve my results, I develop high-quality, high-performance code that is small, fast, correct, complete, and secure. My code is targeted for zero-bugs, unit-tests, edge-cases, 100% coverage, and orders of magnitude performance boosts. I comment and document heavily. I prefer to collaborate, but work very well autonomously.

Development Environment

I have experience with many languages, editors, platforms, etc... Learning new tools rarely improves my problem-solving abilities and usually takes time away from solving really interesting problems with the tools I already have. Learning Python was one of those rare exceptions because a strong scientific community has evolved excellent, optimized, and easily used libraries. In the spirit of avoiding premature optimizations, Python is my preferred prototyping language.

When performance issues arise, I switch to C++ and Intel assembly. I use Virtualbox to sandbox environments. My preferred development environment includes git, mediawiki, make, and gvim. I'm interested in gpu and map/reduce. I am experienced in architecting and implementing operating systems, editors, compilers, data ingesters, lattice math, and feature detection.

Clients

My clients/employers include Carbonite, Lotus, IBM, NASA, MIT, and many small high tech startups. I have patents, and publications, and have contributed to project success in many arenas. These include canonicalization, virus search, high speed lexing, discrete convolution/correlation, efficiency calculations, dimensional conversion, and automated generation of code and papers.

Personal Project

My personal goal is to answer Cajal's three questions about nervous systems (ISBN 0-19-507401-7 Histology of the Nervous System): "Practitioners will only be able to claim that a valid explanation of a histological observation has been provided if three questions can be answered satisfactorily: what is the functional role of the arrangement in the animal; what mechanisms underlie this function; and what sequence of chemical and mechanical events during evolution and development gave rise to these mechanisms." Santiago Ramón y Cajal

Principally, I work on the first two questions: I model observed groups of shaped neurons. I model observed signal propagation and expression. I replicate observed functional roles. As a personal Python OpenCV Big Data project I research and develop neuron-shaped mathematical transforms, as discrete 3D convolution/correlation kernels achieving far sub-pixel image feature detection, using methods learned during my MIT Physics training and early experience in a wet neuroscience lab. ignore old page

Philosophy

The unknown only becomes known by one who makes mistakes. For example, all advances in science are achieved by violating inviolable rules, whether intentionally or not. It is a common theme to be found in the nobel lectures by the prize winners (http://www.nobelprize.org). As I like to say "You know the value of your mistake by the size of the army mounted against you".