Alexander Huth

Assistant Professor at University of Texas at Austin

Alexander Huth is an Assistant Professor of Computer Science and Neuroscience at the University of Texas at Austin. Here are some key details about his background and research:

Education and Career

Received his PhD from the University of California, Berkeley, where he worked in Dr. Jack Gallant's laboratory at the Helen Wills Neuroscience Institute.3
Completed both a bachelor's and master's degree in Computation and Neural Systems (CNS) at the California Institute of Technology (Caltech).3
Joined the faculty at UT Austin in 2017 as an Assistant Professor.2

Research Focus

Alexander Huth's research lies at the intersection of neuroscience, computer science, linguistics, and artificial intelligence. His work focuses on:

Using computational methods to model how the brain processes language and represents meaning.1 3
Developing techniques to analyze fMRI data and visualize brain activity.2
Building complex models of language representation in the brain using approaches from multiple disciplines.3

Notable Work

In 2016, he authored a significant paper exploring the relationship between language meaning and brain activity.4
His research demonstrated that models based on semantic properties of words can predict fMRI responses to naturally spoken narratives.4
He developed detailed maps of semantic representation across the human cortex, showing consistency across individuals.4

Current Projects

Huth is currently working on ambitious projects involving:

Collecting extensive fMRI data from individual subjects (aiming for 200 hours per person) to build more accurate models of language processing in the brain.3
Using modern AI techniques, including large language models like GPT, to better understand brain function.4

Approach to Research

Huth emphasizes the importance of large datasets and letting the data guide discoveries rather than relying solely on structured experiments. He combines methods from neuroscience, computer science, and linguistics to tackle complex questions about brain function.3