Research output per year

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Personal profile

Research interests

I do research in the philosophy of mind that occasionally relies on computational modeling and is heavily informed by machine learning.

An overarching project is to show how intuitive psychological descriptions of the human mind (for example in terms of propositional attitudes like belief and desire) may be grounded in computational models of neural information processing, particularly those that appeal to unsupervised learning and statistical inference using hierarchial generative models ("Helmholtzian" models).

My main current interests within this project are of two broad types: (1) technical challenges to do with extending Helmholtzian models of sensorimotor processing to higher cognitive functions such as reasoning and language ability, and the implications of this for theories of cognitive architecture; (2) foundational issues concerning the nature of mental representation and its relation to the structure and information-processing capabilities of the brain.

I also conduct experiments on artificial neural networks, and use generative models to create music, visual art and text, both as a serious hobby and as a research tool.

Education/Academic qualification

Philosophy, PhD, City University of New York

Award Date: 5 Jan 2019

Research Output

Content and misrepresentation in hierarchical generative models

Kiefer, A. & Hohwy, J., 1 Jun 2018, In : Synthese. 195, 6, p. 2387-2415 29 p.

Research output: Contribution to journalArticleResearchpeer-review

18 Citations (Scopus)