The questions that preoccupy me are epistemological, and this is reflected in both the kinds of topics that I choose to work on, and the emphasis that I place on methodology. I want to know how we discover things about ourselves, our past and our place in the world, and I am curious which of those capacities we might have in common with other animals or with machines. In my recent monograph, Spark from the Deep, I argued that humankind’s longstanding experience with strongly electric fish led us to develop electrical and electronic technologies that greatly extend our ability to perceive and to act in the world. My first monograph, Archive of Place, was a study of the ways that people reconstruct various pasts from physical traces like geological strata, tree rings and fish genes. In writing both books, I drew on my background in the sciences. As an undergraduate I did research in perception and psychophysics, sensory deprivation, and animal navigation. In graduate school I worked with computational models of agents that could learn, remember, communicate and evolve. Among other things, I published research on how the process of language learning might be improved by the presence of noise, and on how changes in learning could drive historical and evolutionary change. In more recent publications, I have continued to explore the boundaries of what humanists can learn from material evidence. In a paper in the journal Rethinking History, for example, I tackled the question of whether we could build a machine to reconstruct what the past smelled like.

All of my research, past and present, is also shaped by the fact that I have more than 35 years of experience as a programmer, including professional work in the forest industry and in epidemiology and clinical trials. I routinely use techniques like machine learning, text mining and image processing to find, harvest, manage, excerpt, cluster and analyze digital sources. As much as possible, I share my methods in the form of open source code and open access online publications. The latter–Digital History Hacks,, and The Programming Historian–have received about a half a million unique page views so far. For the past decade I have also been the director of digital infrastructure for NiCHE: Network in Canadian History & Environment, and our work online has been praised and imitated in Canada, the US, the UK, Germany and elsewhere. To date, my collaborators and I have raised about $3.5 million in external research funding.

In addition to a number of ongoing and productive research collaborations in digital history, I am currently working on three monograph-oriented projects. The first is a study of attempts to build a device that can replicate itself, starting with the machine tools of the Industrial Revolution and continuing to the 3D printers of today. Tacit knowledge forms a key part of this work, so I have built a series of RepRaps and computer-controlled machine tools to explore the relation between hand and mind. The second project is a study of mid-20th-century analog electronic computing. Here, again, hacking is a way of knowing: I am reverse engineering the vacuum-tube-based computers of the 1930s, 40s and 50s using the transistors and analog integrated circuits that became available a generation later. The third project is a study of what I call ‘the universal scientific instrument’. Over the past two hundred years, most scientific instrumentation has come to take the form of a domain-specific front end which transduces signals into electronic form, and a universal back end which processes them. I first presented some of this work at a symposium at the University of Chicago in April, 2014.