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Dr. Alona Fyshe

Assistant Professor, University of Alberta, Computer Science Department

Neuroscience and Language, Natural Language Processing, Machine Learning, Data Analysis and Data Mining, Data Science, Computational Linguistics, Computer Science


CMU ML Lunch (May 12): Alona Fyshe

Speaker: Alona Fyshe Title: Interpretable Semantic Vectors from a Joint Model of Brain- and Text- Based Meaning Abstract Vector space models (VSMs) represent word meanings as points in a high dimensional space. VSMs are typically created using a large text corpora, and so represent word semantics as observed in text. We present a new algorithm (JNNSE) that can incorporate a measure of semantics not previously used to create VSMs: brain activation data recorded while people read words. The resulting model takes advantage of the complementary strengths and weaknesses of corpus and brain activation data to give a more complete representation of semantics. Evaluations show that the model 1) matches a behavioral measure of semantics more closely, 2) can be used to predict corpus data for unseen words and 3) has predictive power that generalizes across brain imaging technologies and across subjects. We believe that the model is thus a more faithful representation of mental vocabularies. Joint work with Partha Talukdar, Brian Murphy and Tom Mitchell For more ML lunch talks, visit

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Alona Fyshe is an Assistant Professor in the Computer Science Department at the University of Victoria and a CIFAR Global Scholar. Fyshe received her BSc and MSc in Computing Science from the University of Alberta, and a PhD in Machine Learning from Carnegie Mellon University. Fyshe uses machine learning to leverage large amounts of text and neuroimaging data to understand how people mentally combine words to create higher-order meaning.


Canadian Institute For Advanced Research Global Scholar | Professional

The CIFAR Global Scholar award funds researchers within five years of their first academic appointment, helping them build research networks and develop essential skills needed to become leaders in global research

Past Talks

The Semantics of Phrases and Sentences in the Human Brain

Research Seminar

University of British Columbia, September 5, 2014

Interpretable Semantic Vectors from a Joint Model of Brain- and Text- Based Meaning

Machine Learning Lunch

Carnegie Mellon University, May 12, 2014

Corpora, Cognition and Composition: Exploring Semantics in the Human Brain

CLSP Seminar

Johns Hopkins University, February 17, 2016

Decoding semantics from phrases and sentences using magnetoencephalography.


Halifax, NS, August 26, 2014



  • Neuroscience and Language
  • Natural Language Processing
  • Machine Learning
  • Data Analysis and Data Mining
  • Data Science
  • Computational Linguistics
  • Computer Science


  • University of Alberta
    Computing Science
    B.Sc., 2006
  • Carnegie Mellon University
    Machine Learning
    Ph.D., 2015

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