Nathaniel J. Smith - Academic homepage

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Until recently, I was a Computational Fellow at BIDS, the UC Berkeley Institute for Data Science, where I divide my time between computationally-informed research on human cognition (esp. language processing), and on building better computational tools for researchers in general.

Brief research statement: Language is one of humanity's most complicated artifacts -- yet language use is fast, effective, and tightly coordinated with concurrent non-linguistic activities. The goal of my research is to understand the architecture of the cognitive systems that allow language to be used in real time, and to interact in a fine-grained, flexible, and non-modular way with non-linguistic cognition and action. I'm interested in this both for its own sake, and because it seems to me a paradigm case of a challenging cognitive task: a domain where some of the complexities of high-level cognition are laid bare, and whose study is likely to give insight into the architecture of high- and low-level cognition in general. Theoretically, my work draws on insights from traditional, psycho-, cognitive, and computational linguistics, and also theoretical tools from other psychological domains, in particular rational models of perception and control. Empirically, I use a wide variety of methods, including both designed experiments and corpus studies of eye-tracking, self-paced reading, cloze tasks, and EEG/ERP/rERP.

Some recent papers/manuscripts

• Abend, O., Kwiatkowski, T., Smith, N. J., Goldwater, S., & Steedman, M. (2017). Bootstrapping Language Acquisition. Cognition, 164, 116-143. (DOI, PDF)
• Smith, N. J. (submitted). ZS: A file format for efficiently distributing, using, and archiving record-oriented data sets of any size. (draft PDF)
• Smith, N. J., & Kutas, M. (2015). Regression-based estimation of ERP waveforms: I. The rERP framework. Psychophysiology, 52(2), 157-168. (PDF)
• Smith, N. J., & Kutas, M. (2015). Regression-based estimation of ERP waveforms: II. Non-linear effects, overlap correction, and practical considerations. Psychophysiology, 52(2), 169-189. (PDF (including supplementary information))
• Smith, N. J., Goodman, N. D., & Frank, M. C. (2013). Learning and using language via recursive pragmatic reasoning about other agents. In C. J. C. Burges and L. Bottou and M. Welling and Z. Ghahramani and K. Q. Weinberger (Eds.), Advances in neural information processing systems (NIPS) 26 (pp. 3039-3047). (paper PDF, poster PDF)
• Smith, N. J. (in press). Blending across modalities in mathematical discourse. In L. D. Edwards, F. Ferrara, & D. Moore-Russo (Eds.), Emerging perspectives in gesture and embodiment in mathematics. Charlotte, NC: Information Age Publishing. (final manuscript PDF)
• Smith, N. J., & Levy, R. (2013). The effect of word predictability on reading time is logarithmic. Cognition, 128(3), 302-319. (PDF)