Featured Profile

Meet Simon Angus, our featured profile for spring 2015. Simon is a member of the Department of Economics, Monash University, Melbourne, Australia. He attended the SFI Graduate Workshop on Computational Social Science and Complexity (John Miller, Scott Page) in 2004 and is an alumnus of the Complex Systems Summer School (Santa Fe 2007).

We asked Simon the following questions about his experience at SFI and his research interests.

1. What do you know now that you wished you knew when you attended CSSS at SFI and/or what did you learn at CSSS that has helped you most in your career?

What I wish I knew before CSSS? Well, I wish I’d remembered that Michelle Girvan’s co-author was none other than Mark Newman when I put up my hand and tried to tell Mark that he should look at Michelle’s working-paper on community detection during Mark’s lectures to us on networks. Mark: “Yeah, I know about that one, I co-authored it.” .. ahem. (I can laugh about it now, and sorry Mark.)

More seriously, probably the biggest thing that the CSSS gave me was the confidence to pursue an unpopular, and apparently ill-advised line of research that I was pursuing during my PhD. Being in an economics department, and a major one at that, it was a great intellectual environment, but one which knew almost nothing of complexity science and what it could contribute to economics, or science for that matter. I’d already had contact with the SFI via John Miller and Scott Page’s grad workshop on computational social science and complexity, which had fuelled my fascination with complexity science and its application to my area of research in economic networks, but the CSSS was another level of encouragement and engagement. The combination of the lecture program, the projects, and the people I met gave me the confidence that complexity science was not a marginal concern, but of increasing prominence and explanatory power towards some of the most interesting scientific questions of our time. The month at the CSSS in New Mexico felt like the modern day Los Alamos (more of that below). Whilst we weren’t designing bombs, there was an overwhelming spirit of intellectual curiosity, generosity and excitement that I’ve experienced rarely since. I came back to my PhD research with great excitement for what the future held, and greatly encouraged by the network of SFI friends who shared a view of scientific endeavor that put the nature of the problem first, even if this would break taboos or norms of one or more fields.

The other major thing I took out of the CSSS was a group of friends. I’ve found that SFI CSSS relationships are remarkably persistent. Clearly in some cases these friendships spilled over quickly into academic activity (e.g. I met Monika Piotrowska at the CSSS and our fourth paper together came out in PLoS-One late last year), but others, whilst infrequent in contact these days, I’m sure will live on. I loved the work hard / play hard mentality of the CSSS: Monday to Friday were certainly intellectually demanding on many fronts, but come Friday night, a group of us were always thinking of the next road-trip, camping trip, or adventure to be had in the mountains and places around Santa Fe. I take it this was also the Los Alamos way, periods of intense intellectual activity punctuated by intense engagement with the natural environment. It’s a mix that fits me perfectly, and one that I’m sure contributed to the long-standing relationships that the SFI CSSS creates. Just recently I reached out for the first time in years to Paul L. Hooper who was part of our small hiking group at the CSSS, and the relationship felt fresh as ever. Paul was the first anthropologist I’d ever met and I was instantly taken by his quiet curiosity and intellect as we talked and hiked in the shadows of Santa Fe Baldy. When thinking of people to provide initial comments on a transdisciplinary project I’m involved with, Paul’s name came immediately to mind. I wasn’t at all surprised to find that he now leads the Quantitative Computational Anthropology Lab at Emory, one of the most innovative labs in the field. That’s the SFI CSSS for you!

2. What are your primary research interests and where do you see your research taking you?

This is tricky. I normally introduce myself as a ‘specialist generalist.’ What I mean by that is that I take a complexity science mindset to whatever problem I interact with and try to work on things that I think are important and interesting, regardless of scientific boundaries. To the outsider my research outputs probably look eclectic at best, but to me, they have a common thread — self-organizing polymer films display emergence and phase-change phenomenahttp://bit.ly/1Gm2RsR; studying world-record marathon pacing at a granular level is about getting at a recently posited theory of complex neural regulation of fatigue in the tiring athlete http://bit.ly/1ETMphD; running genetic algorithmic search over a high-fidelity CA model of cancer growth is about systems biology, non-smooth, evolutionary search, and refining numerical simulation methods at scale http://bit.ly/1Cq9NU4; and so on. The complexity paradigm harmonizes these disparate projects.

In Economics, my emergent focus is on technology, ideas and innovation. Like others (Padgett, Arthur, Hausmann, Farmer, and luminaries of a somewhat lost time of economics before them) I’ve come to the view that the biggest lever that we have for increasing the material prosperity of man-kind is to better understand our technology. Some point to financial or mineral wealth when classifying the prosperity of a nation, but actually, a human civilization is rich because of its store of ideas. (It’s the library you want to protect in Armageddon, not your house or car!!) Paradoxically, most economics is taught with a jaundiced view of technology — it enters, at best, as a simple (often fixed) multiplier at the front of a production equation. Whilst there has been some advances in the last decade, the most interesting work is being done with a complexity mindset (by economists and non-economists).

My own work with colleagues and students attempts to study technology in various ways and time-scales: a recent exciting project with my co-author Jonathan Newton (U Syd) studies the conditions under which cumulative culture would advance in early man, and when it would not, due to the interaction between the emergence of collaborative skills (on the genotype) and the incremental benefit afforded by adopting better technologies during a given epochhttp://bit.ly/1BnjsXy. Alternatively, with excellent honors students here (including Penny Mealy, now at iNET) we developed a generative model of technology which we call the 'Bit Economy’ which models open-ended discovery with a self-organizing inter-dependent network of devices http://bit.ly/1BqSq0K. Just now I’m working hard with a small group here (colleague Paul Raschky, PhD student Klaus Ackermann) to understand humankind’s interaction with the internet — arguably the transformative technology of our age — by handling around 1 trillion observations on IP activity over the last decade.

Robert Lucas has said that once you start thinking about economic growth, it’s hard to think about anything else. I think the saying is more true of technology — it’s the open-ended solution space that gets you in, like the way that I think Kristian Lindgren’s open-ended computational model of evolution probably did for those who first encountered it in 1990 at SFI [1]. If we better understood the nature of our own technological history and dynamics we’d have access to a prosperity engine without parallel. We’re really just starting on that journey, so it’s an exciting area.

[1] Lindgren, Kristian, ‘Evolutionary Phenomena in Simple Dynamics’, in Artificial Life II, (Eds: Langton, C G; Taylor, C; Farmer, J D; Rasmussen, S), SFI Studies in the Sciences of Complexity, vol X, pp.295-312.

3. What mark do you want to leave on the world?

That’s also tricky. I think that the further I go on in my scientific life, and the deeper I understand technology and the linkages in ideas across time and space, the more I realize that science is inherently collaborative. I know we say that and it seems simple or obvious, but I mean it in a forceful way. As scientists, we are not an association of super-stars, we are a vast, inter-dependent network across cultures and generations of 'ideas people’. We contribute to, and draw from, the cumulative knowledge of mankind. Viewed this way, any individual’s contribution to the effort must first be seen as part of the whole; the collective scientific enterprise. I mean this to the extent that I don’t really believe that individual scientists can really say they have specific ideals for their science. Our aims and goals are collective, our methods are collective, our enterprise is collective. This doesn’t detract from the significant steps that a certain scientist at a certain time makes, but ultimately, their gain is a gain for the collective (and so we all cheer!). We all benefit. And it is our collective privilege to contribute.

Let me put it another way. Human knowledge can be illustrated well as a technology tree, where individual discoveries are nodes and links between nodes are the dependencies that make any given discovery possible (e.g. the bicycle depends on steel bonding, bearings, the wheel, gearing and so on).  This tech tree is given exogenously (known unto God), probably dependent on the properties of our universe and our cognitive apparatus. Now think of this tree as a vast, infinite expanse going off into space. That’s the future of human knowledge. “Good science” is that which uncovers another node, or dependency to that tree. If your group or individual effort contributes to uncovering one more node or link, then I think you can say that you’ve left your mark. But note also, given that we are dealing with a network of infinite diameter, your ultimate contribution is infinitesimal. This may sound depressing, but I don’t think so. Consider that physical exploration is exhilarating, but even it has limits (once you’ve conquered the mountain, or plumbed the depths, that’s it...), but knowledge exploration is unbounded! Science is the expedition that never ends.

So let’s just say that I hope to be seen as a ‘good ant’, when my time comes to hang up the microscope.

4. What interests do you have that might surprise your colleagues?

I spent a lot of my life trying to perfect the art of sourdough bread making (sometimes called ‘hearth loves’ or ‘frontier bread’ in the Western states of America). I have written a fair bit about my experiences here [2]. Given that my first training was in industrial chemistry, maybe this shouldn’t be a surprise. I just love good bread.

[2] http://tinyurl.com/AngusSourdoughBread