I’m Gully. It’s a cool name. My parents gave me the moniker from a character in a 1950s ‘pulp’ science fiction novel called ‘The Stars My Destination’.

I studied physics as an undergraduate at Imperial College in London, and loved the mathematical precision of the models and the quantitative certainty it was possible to enjoy with physical models of reality. When you’re thinking about conservation of mass energy, the speed of light or Planck’s constant, you always like you’re on solid grounds.

In my final year, I decided, quite suddenly, to study how the brain works. Little did I know that I would never feel that secure about my knowledge again. Neuroscience is quite messy, complex and heterogeneous and I found the best way of making sense of it was to attempt to apply a phyics-like modeling approach to the concepts used by my colleagues and simply develop databases and tools to bring together how neural circuits work.

As a postdoc, I moved to Los Angeles and started working in an experimental neuroanatomy lab. I took my prior work and started to develop knowledge management tools for neuroscientists. We built an open source knowledge management platform for the neuroscience literature called `NeuroScholar’, and embarked on an academic research career attempting to make science faster, and more efficient by talking to bench scientists, modeling their knowledge and building systems to help them.

In 2006, I made a second big pivot in my career. I moved to the USC’s Information Sciences Institute, a soft-money computer science research institute that had, amongst other things, contributed to the invention of the internet. I collaborated with experts in Natural Language Processing (NLP), Knowledge Representation, Information Integration, Workflows, Semantic Web to drive a high-level research program that brought in funding, and made progress. My role was high-level, and most of the cutting-edge data science was performed by students under the direction of my colleagues. For me, this always lead, inevitably, to a sense of powerlessness. These were not my students; and my CS collegues always focused on their research rather than the applied goals of a Scientific Knowledge Engineering perspective.

I was at a DARPA meeting, when I saw Andrew MacCallum first talk about the Chan Zuckerberg Initiative (CZI). I was especially struck by their vision of they wanted to transform and accelerate science. This seemed to reflect exactly the work that have dedicated my life to. I jumped at the opportunity to join their team and now find myself at the cutting edge between Tech and Philanthropy as a professional data scientist working in Silicon Valley. This is a far cry from academia (even the insanely-innovative and solution-driven world of ISI).

Now, my work is down-in-the-weeds and striving to finding working solutions for our team as we develop tools to help scientists accelerate their work.

It is thrilling to be working on this, especially now. Apart from being the fulfilment of my life’s work to date, the stakes could not be higher in terms of both scientific and sociological challenges to science as an endeavor.

We must raise ourselves up, rapidly solve deadly problems that we face and do so with integrity, humility, and celerity. The world can’t wait.

In addition to my work, I love to write and maintain a blog called ‘Ars Veritatis - the Art of Truth’, and beyond that, my universe is joyfully filled with being a proud husband and father.