Pentti Kanerva is a research affiliate at the Redwood Neuroscience Institute, and is the author of sparse distributed memory. He is responsible for relating the properties of long-term memory to mathematical properties of high-dimensional spaces and compares artificial neural-net associative memory to conventional computer random-access memory and to the neurons in the brain. This theory has been applied to design and implement the Random indexing approach to learning semantic relations from linguistic data. 
Kanerva has an A.A. from Warren Wilson College, M.S. in forestry, with a minor in mathematics and statistics from the University of Helsinki, and has a Ph.D. in Philosophy, from Stanford University.
After earning his Ph.D. at Stanford in 1984, Kanerva moved to work at the NASA Ames Research Center. He also worked at the Swedish Institute of Computer Science, then finally moving on to his current position at the Redwood Neuroscience Institute located in Berkeley.
- "Scientific Staff". Redwood Neuroscience Institute. Retrieved 11 November 2011.
- Kanerva, Pentti, Kristoferson, Jan and Holst, Anders (2000): Random Indexing of Text Samples for Latent Semantic Analysis, Proceedings of the 22nd Annual Conference of the Cognitive Science Society, p. 1036. Mahwah, New Jersey: Erlbaum, 2000.
- Sahlgren, Magnus, Holst, Anders and Pentti Kanerva (2008) Permutations as a Means to Encode Order in Word Space, In Proceedings of the 30th Annual Conference of the Cognitive Science Society: 1300-1305.
- Kanerva, Pentti (2009) Hyperdimensional Computing: An Introduction to Computing in Distributed Representation with High-Dimensional Random Vectors, Cognitive Computation, Volume 1, Issue 2, pp. 139–159.
- Joshi, Aditya, Johan Halseth, and Pentti Kanerva. "Language Recognition using Random Indexing." arXiv preprint arXiv:1412.7026 (2014).
- "Pentti Kanerva". Redwood Neuroscience Institute.