Matthew Caudill, Ph.D.
Assistant Professor
Positions
- Assistant Professor
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Neuroscience
ÌÇÐÄlogo
Houston, TX, US
- Director
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Data Analytics Core
Jan and Dan Duncan Neurological Research Institute Texas Children's Hospital
Houston, Texas, United States
Education
- BS from Wake Forest University
- 05/2005 - Winston-Salem, North Carolina, United States
- Physics
- BA from Wake Forest University
- 05/2005 - Winston-Salem, North Carolina, United States
- Mathematics
- PhD from Washington University in Saint Louis
- 12/2011 - St. Louis, Missouri, United States
- Physics
- Postdoctoral Fellowship at University of California San Diego
- San Diego, California, United States
- Systems Neuroscience
Honors & Awards
- GAANN Fellowship Recipient
- US Department of Education (09/2007)
- William E. Speas Award
- Wake Forest University Physics (05/2005)
- Inducted to Pi Mu Epsilon
- Pi Mu Epsilon Mathematics Society (05/2003)
- Inducted to Sigma Pi Sigma
- American Institute of Physics (05/2003)
Professional Interests
- Applied Mathematics and Statistics
- Iterative Data Processing and Analysis
- Machine and Deep-learning
- Software Architecture
Professional Statement
From genes to circuits to behaviors, today's Neuroscientist has a wide array of tools to record and perturb the brain across vastly different spatial and temporal scales. These sophisticated experimental tools have led to sophisticated datasets that pose three specific challenges for learning about brain function and neurological disorders. First, many of these data sets are large, disparate and disconnected from important context providing metadata. Mylab develops deeply crafted software to read and integrate these data into structures that scale with the data size and are accessible to experimentalist. Second, my lab builds opensource scalable software for transforming data for exploratory analyses. This means we re-envision standard algorithms for image or signal processing as "on-the-fly" algorithms that can build to solutions from streamed data. Finally, my lab uses these software tools as a springboard for the development, application and deployment of machine and deep-learning algorithms to learn relationships, detect events, uncover patterns or states, and form new hypotheses that can drive basic science and clinical research discoveries.
Websites
Selected Publications
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Matthew S. Caudill. " " JOSS. 2025 Nov 11; 10 (115)
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Matthew S. Caudill. " " JOSS. 2023 Apr 5; 8 (84)
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Sih-Rong Wu, Jessica C. Butts, Matthew S. Caudill, Jean-Pierre Revelli, Ryan S. Dhindsa, Mark A. Durham, Huda Y. Zoghbi. " " Sci. Adv.. 2023 Jun 30; 9 (26)
Pubmed PMID: . -
Lingjie He*, Matthew S Caudill*, Junzhan Jing, Wei Wang, Yaling Sun, Jianrong Tang, Xiaolong Jiang, Huda Y Zoghbi. " " Neuron. 2022 ; 110 (10) : 1689-1699.
Pubmed PMID: .
Funding
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Studying the effects and mechanisms of deep brain stimulation in Rett syndrome mice
#2R01NS100738 - (04/01/2018 - 07/31/2027)
- Grant funding from NIH NINDS
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Novel viral vectors-based gene therapies for brain disorders
- (12/09/2020 - 04/30/2025)
- Capsida Biotherapeutics Sponsored Research Agreement
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A combinatorial therapy paradigm for treating developmental and epileptic encephalopathy
- (07/01/2024 - 07/01/2025)
- Gift funding from Cain Foundation
Skills
- Programming Languages
- Python, MATLAB, Tkinter, SQL, Markdown, Linux
- Software Design
- OO Design Patterns, Numerical Programming, Functional (compositional) Program- ming, Scalable Design Patterns and Hardware Acceleration
- Tools
- Git, CI/CD, Static-Type Checkers, Unit-Testing, Linters, LaTex
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