In June, July, and August I was almost daily engaged in the application of evolutionary computation to glitch classification at LIGO. I worked extensively with Marco Cavaglia and his students Hunter, Luciano, and Kentaro for this effort.

We wrestled with the data, trying to find new ways to extract features which provide stronger correlations. We made progress, got lucky a few times, but more often than not hit dead ends which forced us to circle back to the start.

The joy of this arduous process is complex, for it entails both a passion for success and failure, the two faces to discovery. My professor too often said, “Research is hard” as a badge of honour, a mark of the fearless and brave and dedicated. Yet he failed to say “Research is rewarding!” As a recent New Scientist article presented, it is the people we work with that make most jobs tolerable. I am fortunate to have the best of both–an incredibly engaging challenge conducted with incredibly engaging people.

I have the joy of working with some of the brightest and the best, the funniest, the most seasoned and the most juvenile. We laugh far more than we do argue, yet we celebrate only long enough to realise our mistake and then dive back into another seemingly endless, dark tunnel. The phone calls, the TeamSpeak meetings, the hundreds of emails that keep us going. For with each communication we are challenged to prove our findings, we are challenged to be better at our job than we were before. No one ever says, “That is good enough.” Always, the challenge is for more. Higher accuracy. A stronger correlation. An improved better dataset. Better writing, presentation, and publication.

This week I will officially engage as a “Visiting Scientist” at the Embry-Riddle Aeronautical University in Prescott, Arizona where I am working under Dr. Michele Zanolin and with Marek Szczepanczyk, PhD candidate and chair of the supernovae group at LIGO.

Together, we are applying evolutionary computation, genetic programming in particular, to the classification of Coherent Wave Bursts (CWB) in LIGO data. While we have just begun, only a few data runs in our shared experience, we know the work will be long, challenging, and more likely to fail than succeed. But it is the people with whom I am working which compels me, as much as the prospect of success. If I can play a small part in the team which may, some day, detect supernovae using gravitational wave astronomy, then that small part will be an honour indeed.

My revised MSc thesis was submitted today. More than 120 hours effort across six weeks. There is no end, for there is always room for improvement, always more content to generate. Ultimately, you just stop and turn it in. Challenging, educational, and rewarding. Now, I wait …

Six months ago I submitted my thesis.

I waited for six weeks, to learn of my fate.

I waited for six more weeks to learn the meaning of the feedback given.

I then busied myself with conferences, workshops, research, programming, and travel.

Now, with just a few weeks to go, my thesis waits for me.

An intense application of feature engineering, genetic programming, and proposed ensemble learning applied to LIGO glitch classification leads to an email exchange in which an imaginary beach harbors a pile of shells assembled by a greedy fitness function. The lines are drawn in the sand. The decision tree vies for position while the binary classifier stands its ground.

The conch? Well, it was an outlier whose incorrect classification initiated a war amongst otherwise solid researchers, upstanding men and boys. I fear Sam-n-Eric are endangered once more …

Nearly 18 months after I began working on my Python-based genetic programming platform Karoo GP, and 9 months since any real code development, I have returned to revise, update, and improve what served me well while conducting my research at the Square Kilometre Array (SKA) in Cape Town, South Africa.

The data sort and normalisation tools are fully revised, each with a simple yet effective text-based interface. The Quick Start Tutorial is fully rewritten and now available for download. And with 2-3 fairly substantial fixes and improvements, I hope to launch Karoo GP by GECCO 2016, Denver, Colorado.

Karoo GP has it’s own page and will soon be made available from github.

(2016 04/??)

Today I gathered my parents for a review of the code I produce for my MSc research, a Genetic Programming platform designed to work with any prepared .csv file, no matter the user’s level of experience in Python or Machine Learning.

Over the course of an hour I successfully explained how so much of the world, even the greater cosmos can be explained through mathematical functions. Some simple. Some extremely complicated. But all of them, that is, the ones that truly express the inner workings of the cosmos are elegant in form and function. They are beautiful.

When it came to my code, 3000+ lines of Object Oriented Python, there was a moment’s hesitation when I recall that very first line of code, the very first hesitant definition of a variable and function when I thought I’d have the basic code running in a few hundred lines, not thousands; over the course of six weeks, not six months.

In the telling of that story, in the explanation of what I had accomplished, there was very little ego or expression, rather a pure joy for the process of discovery. I was proud not of what may hands accomplished, for I did not invent Genetic Programming, but for the means by which I can now explore the world around me with the vehicle I had built.

I imagine the joy of a geologist is similar, seeing rock layers through the eyes of time and pressure. In the same way, on a much smaller scale, I was challenged to bring this code to life, to allow me to see patterns that tell their own story much as solidified layers of drifting sand, quartz, calcite, and igneous flows tell the story of what happened hundreds of millions of years ago.

I can say that six months of programming was the most mentally challenging thing I have ever done. While the mathematics were relatively simple, the implementation was often arduous. I discovered a new capacity for problem solving that goes beyond my former work in designing supercomputers or a 2000 package operating system, beyond the intrinsic risk / reward of running a for-profit enterprise when every large contract presents a do-or-die situation.

Now, I wonder, have I short-changed my own potential? Not in some kind of ego stroke, but in a very real, “What else am I capable of? What more can I do that I would have otherwise thought impossible?” How many of us truly engage our full potential? With concern for funding, bills, relationships, family, and physical well being, the times in our modern lives in which we are enabled to just think, brainstorm, and solve problems is truly but a minor fraction of our waking hours.

What a shame. What a waste of resources when so much of our world, so much of all our daily, living, breathing, working hours are spent on the day-to-day operations of just getting by. Who out there, who among the myriad humans on this planet has ever been given the challenge and reward of fully using his or her innate ability to solve problems … and indulge in the total bliss of discovery?

Toward the back of a recent issue of Scientific American, I was totally engrossed by a brief discussion of the “Circle of Life” from the point of view of biology. Every known species (2.3 million and growing) is included in the count (inner circle) with a projection for the balance of types of life, as we discover more, in the outer circle.

Perhaps what I love most is the understanding that we know so little, and are projecting our own lack of knowledge as a kind of map for what we desire, and will some day learn.

At long last, my draft thesis has been submitted.

Now, I wait for feedback …

I have since my return to the States five weeks ago been preparing my MSc thesis for submission to UCT. 114 pages. 40 citations. 20 images. Three weeks to go … and still so much to do. Nearly every day I engage. 2 hours, 4 hours … 14 hours. It is a process I enjoy far more than I thought possible, for the exacting attention to every detail is wonderfully consuming.

Running, hiking, yoga, bread baking, tending the fire at my aunt’s home in Tucson are what I do between the hours I am writing and editing. As when I was developing Karoo GP, I wake, breathe, and sleep my thesis.

This is the making of a scientist. No fact goes to print without evidence of its origin, either in previously published works, or my own, validated research. No statement is personal. This is not about me, but what was discovered about the arena in which I laboured to better understand.

I was twenty months in South Africa, twenty two months in this program. I attended a dozen workshops and conferences in South Africa, Namibia, and Spain in order to broaden my skills and deepen my knowledge, to learn how to begin to understand machine learning as it can be applied to radio astronomy. Countless thousands of pages of literature reviewed, thousands of lines of code written, and hundreds of hours spent in development, data runs, and analysis.

In the end, it comes down to just two numbers, Precision and Recall, to determine if my work was a success.

That is … incredible!