Dale Tovar creates new sparse array format for SciPy

There are countless numbers of applications which involve large amounts of sparse data in all scientific and commercial domains. To that end, our own Dale Tovar has created and implemented the GXCS format, which is a novel storage scheme for ultra-large sparse arrays and tensors. One of the advantages of the new format is that it takes up much less storage space in many of the scenarios encountered in practice. For example, unlike the commonly used COO format where storage size increases strongly as both a function of the number of axes and the number of nonzero values, GXCS increases in storage size primarily as a function of the number of nonzero values. The software includes conversions to and from different formats. This will help greatly speed up analyses for anyone who uses it. 

In even bigger news, GXCS is written in the Python and has been incorporated in to pydata/sparse library which is replacing the defacto sparse matrix library in SciPy in a couple of years!

Amazing work and huge congrats to Dale!

Relating personality and psychopathology with diffusion MRI.

Using structural connectivity and predictive modeling methods to relate personality and mental health variables is one of the projects we have going on in the lab. Here is my talk on some preliminary efforts on this project from the Computational Preconference at the 2019 Social & Affective Neuroscience Society meeting in Miami, FL.

 

This is your Brain on Psychology – This is your Psychology on Brain

My colleague Sanjay Srivastava was gracious enough to let me write a guest post on his blog about some of my musings on the relationship between neuroscience and psychology. Here, I try to make the case that neuroscience and psychology can be mutually informative to one another in ways that are sometimes unappreciated.

You can find the post here:
This is your Brain on Psychology – This is your Psychology on Brain (a guest post by Rob Chavez)

UO Psychology Data Science Gallery

In the Spring of 2018, I taught a graduate seminar called Data Science Methods for Psychology. This course was indented to introduce students to topics, concepts, and workflows that are commonplace in “data science” more generally but are less formally discussed in Psychology.  Each week, a pair of students would lead a tutorial session on a given topic before assigning a “mini-hackathon” project for the rest of the class to complete over the coming week. These presentations were consistently excellent, and I thought I would share them as widely as possible for others interested in learning from them. Find them in my GitHub site in the link below:

UO Psychology Data Science Gallery

Inaugural post

This is the inaugural post of the CSN lab. If you’ve made it this far, thank you for  your interest in our work. We hope to continue to use this blog/news section for updates on the lab, ‘pop’ summaries of our work, and links to personal and other academically relevant blogs.

Thanks again, and stay tuned.

-Rob