Paxton Fitzpatrick

About me

I build computational models of human learning and memory, and create software tools for research and education.

I’m currently a Ph.D. candidate in Cognitive Neuroscience at Dartmouth College.
I grew up in a small town in central Pennsylvania before starting college at Dartmouth in 2015.
From 2016 to 2019, I worked in the Dartmouth Brain Imaging Center, collecting and processing fMRI data for a multi-year neuroimaging study.
In 2017, I worked with Bregman Media Labs to create Exnectome, the first EEG sonification-based musical ensemble.
I joined the Contextual Dynamics Lab in 2017, working on developing novel methods and software for studying episodic memory. I managed the CDL from 2018 to 2021, designing and executing studies, mentoring teams of undergrads, and maintaining the lab’s software stack.
In 2019, I graduated from Dartmouth with a BA in cognitive neuroscience. I wrote my honors thesis on a computational framework for modeling how memories deform over time and predicting neural activity from verbal recalls. My thesis won the Nickerson and Leaton awards for undergraduate neuroscience research.
Since 2019, I’ve TA’d and guest-taught undergrad and grad-level courses on neuroscience, statistics, programming, data science, and research methods. I won awards for teaching from Dartmouth in 2019 and 2024.
I started my Ph.D. at Dartmouth in 2021. In 2024, my master’s thesis on modeling conceptual knowledge and learning using text embedding models won a Neukom prize for graduate research in computational science.
I’m now a Ph.D. candidate in cognitive neuroscience, working with Dr. Jeremy Manning. My current work is focused on building automated, scalable systems for personalizing and improving how people learn.
  • Undergraduate, Dartmouth College
  • Research Assistant, Dartmouth Brain Imaging Center
  • Research Assistant, Contextual Dynamics Lab
  • Research Assistant, Bregman Media Labs
  • Laboratory & Research Manager, Contextual Dynamics Lab
  • Peer Tutor, Intro Computer Science
  • Teaching Assistant, Human Memory
  • Teaching Assistant & Guest Lecturer, Intro to Programming for Psychological Scientists
  • Teaching Assistant, Storytelling with Data
  • Teaching Assistant, Intro to Programming for Psychological Scientists
  • Ph.D. Student, Dartmouth College
  • Teaching Assistant, Laboratory in Experimental Psychology
  • Teaching Assistant, Experimental Design, Methodology, and Data Analysis Procedures
  • Teaching Assistant, Methods in Neuroscience at Dartmouth (MIND) Summer School
  • Teaching Assistant, Laboratory in Psychological Science
  • Ph.D. Candidate, Dartmouth College
  • Teaching Assistant, Laboratory in Psychological Science
Programming & web development
Python Python
R R
JavaScript JavaScript
Unix shell Unix shell
LaTeX LaTeX
SuperCollider SuperCollider
HTML HTML
CSS CSS
Sass Sass
Liquid Liquid
Jekyll Jekyll
Development tools
Git Git
Docker Docker
SQLite SQLite
SLURM SLURM
Moab-TORQUE Moab-TORQUE
Conda Conda
GitHub Actions GitHub Actions
Travis CI Travis CI
pytest pytest
Selenium Selenium
Jupyter ecosystem Jupyter ecosystem
Python packaging Python packaging
Experimental design & data collection
jsPsych jsPsych
psiTurk psiTurk
Amazon MTurk Amazon MTurk
PsychoPy PsychoPy
SuperLab SuperLab
OpenBCI OpenBCI
OpenSesame OpenSesame
MorphX MorphX
Qualtrics Qualtrics
Data analysis & visualization
NumPy NumPy
Pandas Pandas
SciPy SciPy
NLTK NLTK
lme4 lme4
statsmodels statsmodels
scikit-learn scikit-learn
Nilearn Nilearn
igraph igraph
Graphia Graphia
Matplotlib Matplotlib
Seaborn Seaborn
Plotly Plotly
Hypertools Hypertools
FreeSurfer FreeSurfer
BORIS BORIS
ANVIL ANVIL
Non-technical
Adobe Illustrator Adobe Illustrator
Adobe Photoshop Adobe Photoshop
Keynote Keynote
French French
Scientific writing Scientific writing
Public speaking Public speaking

Research

My research uses language models to capture how our memories preserve, distort, and compress the external world, and to identify the neural mechanisms that drive these transformations.
X

Text embedding models yield high-resolution insights into conceptual knowledge from short mulitple-choice quizzes

Fitzpatrick P. C., Heusser A. C., Manning J. R. (2025). Text embedding models yield high-resolution insights into conceptual knowledge from short mulitple-choice quizzes. PsyArXiv: 10.31234/osf.io/dh3q2.

X

Feature and order manipulations in a free recall task affect memory for current and future lists

Manning J. R., Whitaker E. C., Fitzpatrick P. C., Lee M. R., Frantz A. M., Bollinger B. J., Romanova D., Field C. E., Heusser A. C. (2024). Feature and order manipulations in a free recall task affect memory for current and future lists. PsyArXiv: 10.31234/osf.io/erzfp.

X

Davos: a Python package “smuggler” for constructing lightweight reproducible notebooks

Fitzpatrick P. C., Manning J. R. (2024). Davos: a Python package “smuggler” for constructing lightweight reproducible notebooks. SoftwareX, 25, 101614.

X

Fitness tracking reveals task-specific associations between memory, mental health, and exercise

Manning J. R., Notaro G. M., Chen E., Fitzpatrick P. C. (2022). Fitness tracking reveals task-specific associations between memory, mental health, and exercise. Scientific Reports, 12(1), 13822.

X

Geometric models reveal behavioral and neural signatures of transforming experiences into memories

Heusser A. C.†, Fitzpatrick P. C.†, Manning J. R. (2021). Geometric models reveal behavioural and neural signatures of transforming experiences into memories. Nature Human Behaviour, 5(7), 905–919.

†denotes equal contribution

X

Is automatic speech-to-text transcription ready for use in psychological experiments?

Ziman K., Heusser A. C., Fitzpatrick P. C., Field C. E., Manning J. R. (2018). Is automatic speech-to-text transcription ready for use in psychological experiments?. Behavior Research Methods, 1–9.

X

Quail: a Python toolbox for analyzing and plotting free recall data

Heusser A. C., Fitzpatrick P. C., Field C. E., Ziman K., Manning J. R. (2017). Quail: a Python toolbox for analyzing and plotting free recall data. The Journal of Open Source Software, 2(18): 424.

X

Davos: a novel approach to sharing reproducible research code with collaborators, students, and the public

Fitzpatrick P. C. (2024). Davos: a novel approach to sharing reproducible research code with collaborators, students, and the public. Dartmouth College. Hanover, NH.

X

A framework for modeling idiosyncratic distortions and compressions of semantic content representations

Fitzpatrick P. C. (2023). A framework for modeling idiosyncratic distortions and compressions of semantic content representations. Dartmouth College. Hanover, NH.

X

How do context and time modulate the geometric trajectory of memory?

Fitzpatrick P. C. (2023). How do context and time modulate the geometric trajectory of memory? Context and Episodic Memory Symposium. Lake Buena Vista, FL.

X

Modeling real-world learning & memory

Fitzpatrick P. C. (2023). Modeling real-world learning & memory. Dartmouth College. Hanover, NH.

X

Connecting fragmented networks of neuroscientific research via bibliometric analysis

Fitzpatrick P. C., O'Nell K. C. (2022). Connecting fragmented networks of neuroscientific research via bibliometric analysis. Dartmouth College. Hanover, NH.

X

Automated personalized instruction for improving online learning

Fitzpatrick P. C. (2022). Automated personalized instruction for improving online learning. PBS Annual Retreat. Fairlee, VT.

X

Thought trajectories: a geometric framework for studying complex cognitive processes

Fitzpatrick P. C. (2022). Thought trajectories: a geometric framework for studying complex cognitive processes. Dartmouth Text-analysis Workshop. Hanover, NH.

X

Capturing the geometric and neural structures of experiences and memories

Fitzpatrick P. C. (2022). Capturing the geometric and neural structures of experiences and memories. Dartmouth College. Hanover, NH.

X

Docker for scientific research

Fitzpatrick P. C. (2021). Docker for scientific research. Dartmouth College. Hanover, NH.

X

Web-based behavioral experiments for online data collection

Fitzpatrick P. C. (2020). Web-based behavioral experiments for online data collection. EPSCoR Attention Consortium meeting. Virtual.

X

A geometric approach to modeling knowledge and learning from Khan Academy course videos

Fitzpatrick P. C., Heusser A. C., Manning J. R. (2022). A geometric approach to modeling knowledge and learning from Khan Academy course videos. Context and Episodic Memory Symposium. Philadelphia, PA.

X

Cognitive tasks as a diagnostic tool for mental health

Jain S., Schreder N., Fitzpatrick P. C., Ziman K., Manning J. R. (2021). Cognitive tasks as a diagnostic tool for mental health. Trends in Psychology Summit. Cambridge, MA.

X

Exploring the evolving geometric structure of experiences and memories

Fitzpatrick P. C., Heusser A. C., Manning J. R. (2019). Exploring the evolving geometric structure of experiences and memories. Society for Neuroscience Annual Meeting. Chicago, IL.

X

Mapping between naturalistic experience and verbal recall

Fitzpatrick P. C., Heusser A. C., Manning J. R. (2018). Mapping between naturalistic experience and verbal recall. Society for Neuroscience Annual Meeting. San Diego, CA.

X

Capturing the geometric structure of our experiences and how we remember them

Heusser A. C., Fitzpatrick P. C., Manning J. R. (2018). Capturing the geometric structure of our experiences and how we remember them. Conference on Cognitive Computational Neuroscience. Philadelphia, PA.

X

The utility of speech-to-text software for transcription of verbal response data

Fitzpatrick P. C., Ziman K., Heusser A. C., Field C. E., Manning J. R. (2018). The utility of speech-to-text software for transcription of verbal response data. Wetterhahn Science Symposium. Hanover, NH.

X

Adaptive free recall: Enhancing (or diminishing) memory

Lee M., Chacko R., Whitaker E., Fitzpatrick P. C., Field C. E., Ziman K., Bollinger B., Heusser A. C., Manning J. R. (2018). Adaptive free recall: Enhancing (or diminishing) memory. Wetterhahn Science Symposium. Hanover, NH.

X

Text embedding models yield high-resolution insights into conceptual knowledge from short mulitple-choice quizzes

Fitzpatrick P. C., Heusser A. C., Manning J. R. (2025). Text embedding models yield high-resolution insights into conceptual knowledge from short mulitple-choice quizzes. PsyArXiv: 10.31234/osf.io/dh3q2.

X

Davos: a novel approach to sharing reproducible research code with collaborators, students, and the public

Fitzpatrick P. C. (2024). Davos: a novel approach to sharing reproducible research code with collaborators, students, and the public. Dartmouth College. Hanover, NH.

X

Feature and order manipulations in a free recall task affect memory for current and future lists

Manning J. R., Whitaker E. C., Fitzpatrick P. C., Lee M. R., Frantz A. M., Bollinger B. J., Romanova D., Field C. E., Heusser A. C. (2024). Feature and order manipulations in a free recall task affect memory for current and future lists. PsyArXiv: 10.31234/osf.io/erzfp.

X

Davos: a Python package “smuggler” for constructing lightweight reproducible notebooks

Fitzpatrick P. C., Manning J. R. (2024). Davos: a Python package “smuggler” for constructing lightweight reproducible notebooks. SoftwareX, 25, 101614.

X

A framework for modeling idiosyncratic distortions and compressions of semantic content representations

Fitzpatrick P. C. (2023). A framework for modeling idiosyncratic distortions and compressions of semantic content representations. Dartmouth College. Hanover, NH.

X

How do context and time modulate the geometric trajectory of memory?

Fitzpatrick P. C. (2023). How do context and time modulate the geometric trajectory of memory? Context and Episodic Memory Symposium. Lake Buena Vista, FL.

X

Modeling real-world learning & memory

Fitzpatrick P. C. (2023). Modeling real-world learning & memory. Dartmouth College. Hanover, NH.

X

Fitness tracking reveals task-specific associations between memory, mental health, and exercise

Manning J. R., Notaro G. M., Chen E., Fitzpatrick P. C. (2022). Fitness tracking reveals task-specific associations between memory, mental health, and exercise. Scientific Reports, 12(1), 13822.

X

A geometric approach to modeling knowledge and learning from Khan Academy course videos

Fitzpatrick P. C., Heusser A. C., Manning J. R. (2022). A geometric approach to modeling knowledge and learning from Khan Academy course videos. Context and Episodic Memory Symposium. Philadelphia, PA.

X

Connecting fragmented networks of neuroscientific research via bibliometric analysis

Fitzpatrick P. C., O'Nell K. C. (2022). Connecting fragmented networks of neuroscientific research via bibliometric analysis. Dartmouth College. Hanover, NH.

X

Automated personalized instruction for improving online learning

Fitzpatrick P. C. (2022). Automated personalized instruction for improving online learning. PBS Annual Retreat. Fairlee, VT.

X

Thought trajectories: a geometric framework for studying complex cognitive processes

Fitzpatrick P. C. (2022). Thought trajectories: a geometric framework for studying complex cognitive processes. Dartmouth Text-analysis Workshop. Hanover, NH.

X

Cognitive tasks as a diagnostic tool for mental health

Jain S., Schreder N., Fitzpatrick P. C., Ziman K., Manning J. R. (2021). Cognitive tasks as a diagnostic tool for mental health. Trends in Psychology Summit. Cambridge, MA.

X

Capturing the geometric and neural structures of experiences and memories

Fitzpatrick P. C. (2022). Capturing the geometric and neural structures of experiences and memories. Dartmouth College. Hanover, NH.

X

Geometric models reveal behavioral and neural signatures of transforming experiences into memories

Heusser A. C.†, Fitzpatrick P. C.†, Manning J. R. (2021). Geometric models reveal behavioural and neural signatures of transforming experiences into memories. Nature Human Behaviour, 5(7), 905–919.

†denotes equal contribution

X

Docker for scientific research

Fitzpatrick P. C. (2021). Docker for scientific research. Dartmouth College. Hanover, NH.

X

Web-based behavioral experiments for online data collection

Fitzpatrick P. C. (2020). Web-based behavioral experiments for online data collection. EPSCoR Attention Consortium meeting. Virtual.

X

Exploring the evolving geometric structure of experiences and memories

Fitzpatrick P. C., Heusser A. C., Manning J. R. (2019). Exploring the evolving geometric structure of experiences and memories. Society for Neuroscience Annual Meeting. Chicago, IL.

X

Mapping between naturalistic experience and verbal recall

Fitzpatrick P. C., Heusser A. C., Manning J. R. (2018). Mapping between naturalistic experience and verbal recall. Society for Neuroscience Annual Meeting. San Diego, CA.

X

Capturing the geometric structure of our experiences and how we remember them

Heusser A. C., Fitzpatrick P. C., Manning J. R. (2018). Capturing the geometric structure of our experiences and how we remember them. Conference on Cognitive Computational Neuroscience. Philadelphia, PA.

X

The utility of speech-to-text software for transcription of verbal response data

Fitzpatrick P. C., Ziman K., Heusser A. C., Field C. E., Manning J. R. (2018). The utility of speech-to-text software for transcription of verbal response data. Wetterhahn Science Symposium. Hanover, NH.

X

Adaptive free recall: Enhancing (or diminishing) memory

Lee M., Chacko R., Whitaker E., Fitzpatrick P. C., Field C. E., Ziman K., Bollinger B., Heusser A. C., Manning J. R. (2018). Adaptive free recall: Enhancing (or diminishing) memory. Wetterhahn Science Symposium. Hanover, NH.

X

Is automatic speech-to-text transcription ready for use in psychological experiments?

Ziman K., Heusser A. C., Fitzpatrick P. C., Field C. E., Manning J. R. (2018). Is automatic speech-to-text transcription ready for use in psychological experiments?. Behavior Research Methods, 1–9.

X

Quail: a Python toolbox for analyzing and plotting free recall data

Heusser A. C., Fitzpatrick P. C., Field C. E., Ziman K., Manning J. R. (2017). Quail: a Python toolbox for analyzing and plotting free recall data. The Journal of Open Source Software, 2(18): 424.

Software

I also regularly develop, maintain, and contribute to a number of open-source software projects.

davos

Import Python packages even if they aren’t installed. Enables the “smuggle” statement: a drop-in replacement for import that handles missing packages on the fly. Add “onion comments” alongside smuggle statements to specify package versions and additional options. Can be used to turn Jupyter or Colab notebooks into self-contained, reproducible Python environments that manage dependencies at runtime.

docker-tutorial

Walkthroughs and template code for running experiments and analyzing data from within Docker containers. Pre-built images are available on Docker Hub.

particle-image

Animate a particlized image in vanilla JavaScript. Turn an image from the web into an animated swarm of interactive particles. Set parameters to control particle color, size, density, speed, hover/click/touch interactions, and more.

psiturk-experiment-template

A template behavioral experiment ready to be deployed locally or online via Amazon Mechanical Turk. Implemented using the psiTurk platform and jsPsych library, and isolated within four networked Docker containers: a Debian 9 container to house the experiment code and psiTurk server, an nginx server for load balancing, a MySQL database for storing data, and Adminer for inspecting and downloading data.

CDL-docker-stacks

A collection of optimized, extensible, hierarchically built Docker images for common neuro/data science tasks. Pre-built images are available on Docker Hub in Python 3.6, 3.7, and 3.8 variants.

cluster-tools-dartmouth

A Python toolbox for remotely interacting with Dartmouth’s Discovery HPC cluster. Automatically generates PBS scripts, submits jobs to the scheduler, monitors progress, and compiles results when finished. Can easily be configured to work with any Moab/TORQUE system.

gittracker

A CLI app for tracking the states of all your local Git repositories in one place. Run a single command from any directory to display git status-like information for each repo gittracker is configured to track. Supports arbitrarily nested submodules, multiple verbosity levels, and automatic discovery of local repos.

quail

A Python toolbox for processing, analyzing, and visualizing free recall data. Provides a common interface for working with data from both list-learning and naturalistic memory experiments. Integrates with the Google Cloud Speech-to-Text API for rapid, on-the-fly audio transcription.

autoFR

A verbal free recall experiment that incorporates automated speech decoding. Uses quail to automatically obtain recall transcripts, onset/offset times, IRTs, confidence scores, and other metadata. Provides a custom jsPsych plugin for collecting and saving verbal recall data.

hypertools # lead maintainer

A Python package for visualizing and manipulating high-dimensional data. Transform, align, normalize, interpolate, cluster, reduce, and plot numeric or text data with a single function call or in individual steps. Save full analysis pipelines including data and trained models as DataGeometry objects for later reuse. Designed to be fully customizable with reasonable defaults.

umap-learn # core maintainer

Python implementation of Uniform Manifold Approximation and Projection. A general-purpose non-linear dimensionality reduction algorithm based on finding a low-dimensional projection of the data that best preserves its fuzzy topological structure. The Python package also implements supervised, semi-supervised, aligned, and parametric UMAP variants, an inverse transform, densMAP, and a plotting library.

timecorr # core contributor

A Python toolbox for exploring higher-order structure in multivariate timeseries data. Iteratively computes dynamic correlations and reduces dimensionality to approximate higher-order dynamic correlations in a computationally tractable way. Also supports computing various dynamic graph theoretic measures.

SuperEEG # core contributor

Infer activity throughout the brain from a small(ish) number of electrodes using Gaussian process regression

CDL-bibliography # core contributor

A shared bibtex file containing references for ~6,000 psychology, neuroscience, math, and machine learning papers.

lab-manual # core maintainer

Lab manual and associated source code for the Contextual Dynamics Lab at Dartmouth College.

…and of course this website!

Get in touch

Contact info

Paxton.C.Fitzpatrick.GR@Dartmouth.edu

@paxt0n4

416 Moore Hall, Dartmouth College
Hanover, NH 03755

Where am I?