Matthew Turk

Matthew Turk

Assistant Professor of Information Sciences

University of Illinois

National Center for Supercomputing Applications


Matthew Turk is an assistant professor in the School of Information Sciences and also holds an appointment with the Department of Astronomy in the College of Liberal Arts and Sciences. His research is focused on how individuals interact with data and how that data is processed and understood.

At the University of Illinois, he leads the Data Exploration Lab and teaches in Data Visualization, Data Storytelling, and Computational Astrophysics.


  • Data Analysis
  • Data Visualization
  • Open Source Scientific Software
  • Astrophysical Computation


  • PhD in Physics, 2009

    Stanford University

  • BA in Physics and Math, 2003

    Northwestern University


Data Representation

Data Viz




Scientific Computing



Assistant Professor

School of Information Sciences, University of Illinois

Sep 2016 – Present Illinois

Research Scientist

NCSA, University of Illinois

Jun 2014 – Aug 2016 Illinois
At the National Center for Supercomputing Applications, I built a research group to conceptualize, develop and understand tools for data exploration and visualization. In collaboration with others at the NCSA, I worked to advance the National Data Service and other initiatives.

Associate Research Scientist

Columbia University Astronomy

Jan 2014 – May 2014 New York City
Supported by the NSF SI2-SSE grant ACI-1339624 (proposal available here) I was an associate research scientist at Columbia.

NSF CI TraCS Postdoctoral Fellow

Columbia University Astronomy

Jan 2011 – Dec 2013 New York City
As part of the NSF CI TraCS fellowship program, I spent three years at the Columbia University Astronomy Department developing computational tools for astrophysical simulations in collaboration with Prof Greg Bryan.

Postdoctoral Scholar

University of California San Diego

Jul 2009 – Dec 2010 San Diego, CA
I worked as a postdoc with Prof Mike Norman at the Center for Astrophysics and Space Sciences at UCSD.

Graduate Student

KIPAC/SLAC, Stanford University

Aug 2004 – Jun 2009 Palo Alto, CA

Recent Posts

A Little Bit of Endianness

(Confession time: I did not even realize I was mildly-punning in that title.) Over the last few months, my hobby-time has mostly been focused on some reverse engineering of old DOS games I played as a kid.

yt: Internal and External Ecosystems

I think I’ve talked myself into proposing a big change in yt. I’m not the “boss” of yt, so it might not happen, but I’ve kind of worked up my courage to make a serious suggestion.

Loading data in yt: Can we make it better?

In this blogpost, I walk through the annoying bits about loading unknown data into yt.

Whole Tale: Exploration, Analysis and Reproducibility

What is this Whole Tale thing?
Whole Tale: Exploration, Analysis and Reproducibility

Kaitai Struct and Scientific Data

tl;dr: kaitai struct is awesome. File formats can be pretty annoying – especially when you figure them out through weird combinations of reverse-engineering, hand-me-down code and trial-and-error. What we’ve ended up with in yt is a bunch of data formats where the process of conducting the IO is all mixed up with the description of that IO.



yt is an open-source python package for analyzing and visualizing volumetric data.

Crops in Silico

Crops in Silico is an integrative and multi-scale modeling platform to combine modeling efforts toward the generation of virtual crops, open and accessible to the global community.

Whole Tale

Whole Tale is an initiative to build a scalable, open source, web-based, multi-user platform for reproducible research.


Repositories and websites for courses I have taught.

IS590ADV - Spring 2019

Seminar on advanced or in-depth topics in data visualization

IS590DV - Fall 2018

Data Viz from Fall 2018

ASTR496 - Spring 2018

Introduction to Computational Astrophysics

IS590DV - Spring 2018

Data Viz from Spring 2018

Recent & Upcoming Talks

Interpretation, Grammar and Visualization

This talk explores some ideas about how to interpret volumetric data in an AI-focused way.

QMC-HAMM: Quick Research Overview

Brief overview of my interest in the QMC-HAMM project.

A Grammar of Volumetric Analysis

Sam and I talked about our work building a grammar for volumetric analysis. It features some D3js diagrams, which I think I will …

Getting Lost in Community Building

It’s really easy to get lost in community building.

OSHIW: NumFOCUS Sustainability

In this talk, I present a retrospective on the origins and goals of the NumFOCUS software sustainability project I was involved in in …

Recent Publications

Computing environments for reproducibility: Capturing the ``Whole Tale''

The act of sharing scientific knowledge is rapidly evolving away from traditional articles and presentations to the delivery of …

unyt: Handle, manipulate, and convert data with units in Python

Software that processes real-world data or that models a physical system must have some way of managing units. While simple approaches …

GAMER-2: a GPU-accelerated adaptive mesh refinement code -- accuracy, performance, and scalability

We present GAMER-2, a GPU-accelerated adaptive mesh refinement (AMR) code for astrophysics. It provides a rich set of features, …

Crops In Silico: Generating Virtual Crops Using an Integrative and Multi-scale Modeling Platform

Multi-scale models can facilitate whole plant simulations by linking gene networks, protein synthesis, metabolic pathways, physiology, …

grackle: a chemistry and cooling library for astrophysics

We present the grackle chemistry and cooling library for astrophysical simulations and models. grackle provides a treatment of …