Alona in Oslo, 2013

I am a Post Doc working with Tom Mitchell at Carnegie Mellon University in the Machine Learning Department. I recently defended my PhD thesis, which is available here.

I am a member of Tom's Brain Imaging Group. We develop Machine Learning techniques to better understand how the human brain represents and combines semantics and meaning. My research specifically focuses on the composition of meaning for minimal phrases, like adjective-noun pairs. My research is funded by NSERC and an MNTP fellowship.

I have a BSc and MSc in Computing Science from the University of Alberta and completed a research internship with University of Alberta bioinformatics lab. My advisor there was Duane Szafron.

After I completed my MSc, I joined Google as a Software Engineer. Though I loved working at Google (and learned a great deal while there!), I missed research, and so returned to grad school.

Here's my CV.

I also have a blog, to which I post very rarely. I post when I solve a technical problem after finding no help on Google (my way of contributing to the internet knowledge base) or for interesting discoveries that are too small for a paper, but I still feel are worth sharing.

How's the thesis writing going, Alona? Update: it's done!!

That's a funny looking name....

Though my name looks complicated, it's really quite simple. Fyshe is just pronounced fish, and here's a limerick to help you remember the rest:

There once was a girl named Alona,
Whose parents gave her an iguana.
But the iguana grew mold,
The clime was too cold!
The reptile desires a hot sauna.

Interesting factoid: though my mom swears she made up the name, Alona means oak tree in Hebrew.


See also my Google Scholar page.

  • Alona Fyshe, Leila Wehbe, Partha Talukdar, Brian Murphy, and Tom Mitchell. A Compositional and Interpretable Semantic Space. The 2015 Conference of the North American Chapter of the Association for Computational Linguistics - Human Language Technologies (NAACL HLT 2015), Denver, CO. 2015. pdf Supplementary Material
  • Leila Wehbe , Brian Murphy, Partha Talukdar, Alona Fyshe, Aaditya Ramdas, Tom Mitchell. Simultaneously uncovering the patterns of brain regions involved in different story reading subprocesses PLoS ONE, 9(11): e112575 Journal Website Supplementary Material
  • Evangelos E. Papalexakis, Alona Fyshe, Nicholas Sidiropoulos, Partha Pratim Talukdar, Tom Mitchell, Christos Faloutsos. Good-Enough Brain Model: Challenges, Algorithms and Discoveries in Multi-Subject Experiments. ACM SIGKDD, New York City, USA. 2014 pdf
  • Alona Fyshe, Partha Pratim Talukdar, Brian Murphy and Tom M Mitchell. Interpretable Semantic Vectors from a Joint Model of Brain- and Text- Based Meaning. The 52nd Annual Meeting of the Association for Computational Linguistics, Baltimore, Maryland. 2014. pdf Supplementary Material
  • Michelle Shu and Alona Fyshe. Sparse Autoencoders for Word Decoding from Magnetoencephalography. 3rd NIPS Workshop on Machine Learning and Interpretation in NeuroImaging (MLINI), 2013. pdf
  • John J Grefenstette, Shawn T Brown, Roni Rosenfeld, Jay DePasse, Nathan TB Stone, Phillip C Cooley, William D Wheaton, Alona Fyshe, David D Galloway, Anuroop Sriram, Hasan Guclu, Thomas Abraham and Donald S Burke. FRED (a Framework for Reconstructing Epidemic Dynamics): an open-source software system for modeling infectious diseases and control strategies using census-based populations. BMC public health. 2013;13(1):940 pdf
  • Alona Fyshe, Partha Talukdar, Brian Murphy and Tom Mitchell. Documents and Dependencies: an Exploration of Vector Space Models for Semantic Composition. International Conference on Computational Natural Language Learning (CoNLL 2013), Sofia, Bulgaria., 2013. pdf Supplementary Material (25% acceptance rate)
  • Alona Fyshe, Gustavo Sudre, Leila Wehbe, Brian Murphy and Tom Mitchell. Decoding Word Semantics from Magnetoencephalography Time Series Transformations. 2nd NIPS Workshop on Machine Learning and Interpretation in NeuroImaging (MLINI), 2012. pdf
  • Gustavo Sudre, Dean Pomerleau, Mark Palatucci, Leila Wehbe, Alona Fyshe, Riitta Salmelin, Tom Mitchell. Tracking Neural Coding Of Perceptual And Semantic Features Of Concrete Nouns. Neuroimage 62(1) 451-463, 2012. Link
  • Alona Fyshe, Emily Fox, David Dunson and Tom Mitchell. Hierarchical Latent Dictionaries for Models of Brain Activation. Fifteenth International Conference on Artificial Intelligence and Statistics, 2012 pdf Supplementary Material (6% acceptance rate for oral presentation)
  • Alona Fyshe, Yifeng Liu, Duane Szafron, Russ Greiner, and Paul Lu. Improving Subcellular Localization Prediction using Text Classification and the Gene Ontology. Bioinformatics, 24(21):2512-2517 2008 pdf
  • Alona Fyshe and Duane Szafron. Term Generalization and Synonym Resolution for Biological Abstracts: Using the Gene Ontology for Subcellular Localization Prediction. BioNLP Workshop (HLT-NAACL), 2006 pdf (38% acceptance rate)
  • Brett Poulin, Roman Eisner, Duane Szafron, Paul Lu, Russ Greiner, D.S. Wishart, Alona Fyshe, Brandon Pearcy, Cam MacDonell and John Anvik. Visual Explanation of Evidence in Additive Classifiers. Eighteenth Conference on Innovative Applications of Artificial Intelligence (IAAI), July 2006 pdf
  • Paul Lu, Duane Szafron, Russell Greiner, David S. Wishart, Alona Fyshe, Brandon Pearcy, Brett Poulin, Roman Eisner, Danny Ngo and Nicholas Lamb. PA-GOSUB: a searchable database of model organism protein sequences with their predicted Gene Ontology molecular function and subcellular localization. Nucleic Acids Research, 33:D147-D153, 2005 pdf
  • Duane Szafron, Paul Lu, Russell Greiner, David S. Wishart, Brett Poulin, Roman Eisner, Zhiyong Lu, John Anvik, Cam Macdonell, Alona Fyshe, and David Meeuwis. Proteome Analyst: Custom Predictions with Explanations in a Web-based Tool for High-throughput Proteome Annotations. Nucleic Acids Research, 32:W365-W371 2005 pdf
  • Nicholas Lamb, Paul Lu, and Alona Fyshe. Trellis Driver: Distributing a Java Workflow Across a Network of Workstations. International Workshop on High Performance Scientific and Engineering Computing (HPSEC), 2004 pdf



  • Intermediate Statistics (10-705)
  • Machine Learning (10-701)
  • Statistical Machine Learning (10-702)
  • Probabilistic Graphical Models (10-708)
  • Algorithms in the Real World (15-853)
  • Systems Neuroscience (PITT MSNBIO/NROSCI 2012)
  • Statistical Models of the Brain (36-759)
  • Cognitive Neuroscience (85-765)
  • Multimedia Databases and Data Mining (15-826)
  • Advanced Cellular Neuroscience (03-762)

Teaching Assistant Positions


University of Alberta

  • Fall 2006, Introduction to Computing Science
  • Fall 2005, Introduction to Computing Science