Education

Ph.D.   |   Applied and Computational Mathematics and Statistics (ACMS)

• University of Notre Dame   |   2020


• Doctoral thesis: "Second-order moments of activity in large neural network models"



Relevant coursework: machine learning, Bayesian statistics, network science, stochastic analysis, time series analysis, partial differential equations, nonlinear dynamics

B.S.   |   Applied Mathematics & Cognitive Science

• Minors: Computer Science, Philosophy, Psychology, and Neuroscience
• University of Evansville   |   2015


• Senior thesis: "Crime prediction models applied to the city of Evansville"
• Honors thesis: "Goodness of fit metrics for joint probability distributions"



Relevant coursework: calculus, linear algebra, probability, statistics, discrete & combinatorics, numerical analysis, real analysis, mathematical physics, algorithms & data structures, cryptography, machine learning, symbolic logic, cognitive psychology, neurophysiology, advanced neuroscience, philosophy of mind, philosophy of science

Experience

Research Software Engineer

• Center for Open Neuroscience (CON)   |   2025-Present
  Center for Cognitive Neurosciences (CCN)   |   Psychological and Brain Sciences (PBS)   |   Dartmouth College



Maintaining and enhancing several NIH data archives that store neuroscientific data by standardizing dataset organization across multiple modalities and providing usage analytics, including geolocation, through parsing terabytes of raw S3 log files.

Assisting with user support tickets and feature requests to ensure smooth operation of data submission and retrieval processes.

Developing open source software for use in neurophysiology research with an emphasis on achieving reproducibility of scientific findings.

Researching options for stable, cost-effective, long-term backup of petabyte-scale data storage. Working with a range of institutions and services to provide solutions and cost estimates to that effect.

Providing software, consultation, and computing support for the Brain Behavior Quantification and Synchronization consortium (BBQS).

Research Software Engineer

• CatalystNeuro   |   2020-2024



Developed and maintained 5 repositories of open-source software by ensuring proper functionality of automated testing suites, documentation, tutorials, and demos.

Created and maintained 12+ data processing pipelines for neuroscience labs, allowing their data to flow from acquisition to sharing in a seamless fashion.

Curated a total of 256 TB of high-value datasets to NIH data archives on behalf of various research groups.

Managed the company's cloud resources (Amazon Web Services; AWS), including storage, compute resources, and identity access management (IAM).

Handled user interactions within the research community by offering technical support and resolving issues or feature requests in a timely manner.

Facilitated user education across various platforms by running sessions at multiple conferences and workshops, increasing user adoption and effective system utilization.

All software related in some way to the facilitation of terabyte-scale data management, analysis, and visualization for the field of neurophysiology.

Research Assistant

• Neural Dynamics and Computing Group at University of Notre Dame   |   2016-2020



Reconciled the computational properties of biologically realistic neural networks with artificial machine learning models (such as those used across computer vision) through complex mathematical theory and stochastic biophysical simulations, with results communicated through 3 journal publications and a presentation at the high-impact COSYNE conference (top 4% of abstracts accepted).

Collaborated with several top experimentalists in neuroscience as a trainee in the NeuroNex program, which focused on understanding how neural function emerges from underlying structure.

Teaching Assistant

• Applied and Computational Mathematics and Statistics (ACMS)   |   2015-2017



Ran 4 tutorial sections for 112 students, aiding their study of course concepts to achieve a 96% satisfaction rate. Graded homework assignments and exams. Filled in main lectures for the professor as needed.

Data Analyst

• JRM Environmental Inc   |   2015



Analyzed geological data from water samples in conjunction with the Indiana Department of Environmental Management to issue compliance permits for Indianapolis regulation standards.

Technical Editor

• Penguin Random House   |   2015



Reviewed and corrected over 300 pages of "An Idiot's Guide to Algebra II".

Research Intern

• BITLab   |   Michigan State University   |   2014



Explored statistical effects of algorithmic curation (the use of automated filtering mechanisms in the delivery and display of information) by measuring properties of simulated models of social networks, with results presented at the MIDSURE conference.

Research Intern

• Bioinformatics   |   University of Kansas   |   2013



Examined information diffusion through large-scale simulations of G-protein signaling mechanisms using a high-performance super-computing cluster (HPC), then presented results at an undergraduate symposium.

Highlighted Projects

• NWB GUIDE   |   Lead Developer



Developed an intuitive user interface for file management using interactive validation and real-time suggestions, streamlining the process for data submission to NIH archives.

Ensured a robust testing suite involving multiple levels of integration and user interactions emulated using Puppeteer to enhance reliability and long-term maintainability.

Tracked and documented dozens of hands-on user tests to refine the user experience.

• nwb2bids   |  Lead Developer



Created a metadata extraction tool for organizing datasets of NeurodataWithoutBorders (NWB) files following the Brain Imaging Data Structure (BIDS) structure. Encourages best practices in data curation, such as self-describing entities, FAIR principles, and rich Hierarchical Event Descriptor (HED) annotations.

Developed in conjunction with the BIDS Enhancement Proposal (BEP) 032 for micro-electrode neurophysiology data.

• NeuroConv   |   Lead Developer



Established an automated data conversion tool capable of reading more than 40 distinct data formats used by neurophysiology acquisition devices in order to automatically write to the NeurodataWithoutBorders (NWB) standard.

Designed universal APIs which transparently handled each layer of complexity to simplify the tasks of tagging, grouping, metadata transcription, temporal alignment, asset linking, buffering, chunking, and compression.

Implemented a distributed cloud deployment system to run large-scale, off-site, batched conversions through Amazon Web Services (AWS).

• NWB Inspector   |   Lead Developer



Built a command line tool used by the NIH data archive to validate all data uploads, which ensures all submissions are provided automated suggestions for metadata improvements that enhance data findability and reuse.

Mirrored the design, style, and functionality of linting tools such as flake8, pydocstyle, and ruff.

• Neurosift   |   UX Consultant



Aided in the design of a browser-based application for visualizing the contents of terabyte-scale neurophysiology datasets. Supports time series, images, videos, pose, tabular, annotated events, and all associated metadata through an intuitive exploration interface. Utilizes a specialized HDF5 web assembly implementation for increased efficiency when streaming data from the S3-backed archives.

• NWB Benchmarks   |   Core Developer



Managed a collection of unit and integration tests whose performance metrics (time, memory, and web packets) are sampled against a range of environmental run configurations, machine specifications, and bandwidth limits with the results used to assess the performance of HDF5 and Zarr file packaging parameterization against cloud streaming methods.

Run outputs are aggregated into a common public database and built-in visualization tools generate reports of summary findings. A manuscript discussing interpretations and recommendations is in preparation.

Built as an extension on top of the popular Airspeed Velocity (ASV) benchmarking framework.

• duct   |   Developer



Maintained a simple command line tool for monitoring and maintaining records of process-specific system resource utilization of any other command line invocation.

Tracks wall clock time, CPU time, RAM consumption, and more!

• Hierarchical Data Modeling Framework (HDMF)  |   Contributor



Enhanced a generic schema language for defining structured data standards intended to be written to group-like backend file types (such as HDF5 and Zarr) by generalizing, parallelizing, and optimizing lazy data buffering for terabyte-scale datasets.

• NWB Widgets (Legacy)   |   Developer



Drafted Jupyter widgets-based tools for visualizing the contents of terabyte-scale neurophysiology datasets. Supports many custom plugins for specific neural data types. Has some remote streaming capability, but is more intended for reading from local disks.

Largely replaced by the Neurosift browser-based application.

Data Curation

Over the years, I have participated directly (by acting as the primary point person) or indirectly (in a supervisory capacity) in the management, curation, and publication of dozens of high-impact datasets across many research institutions.

Those described below are among the more notable.

Visual Coding (2-Photon Calcium Imaging)

• Group: Neural Dynamics and Computing   |   Location: Allen Institute for Brain Science
• Modality: Microscopy   |   Role: Primary Engineer
Dataset   |   Jupyter Notebook   |   Conversion Code


Wrote custom code to standardize the mixed JSON/HDF5 metadata records for thousands of microscopy experiments and their associated visual stimuli.

Published a total of 93.4 TB of visual cortex microscopy data on the associated NIH data archive.

Adapted a Jupyter Notebook tutorial to demonstrate how to remotely stream and analyze the dataset.

Brain Wide Map

• Group: International Brain Lab   |   Modality: Electrophysiology   |   Role: Primary Engineer
Manuscript   |   Dataset   |   Jupyter Notebooks   |   Conversion Code


Wrote conversion code which interfaced with PostgresSQL metadata database to standardize the data structure of thousands of extracellular electrophysiology experiments with complex behavior.

Uploaded a total of 66 TB of synchronized electrophysiology, audio, and behavioral event data on the associated NIH data archive.

Neural signal propagation atlas of Caenorhabditis elegans

• Group: Leifer Lab   |   Location: Princeton University   |   Modality: Microscopy   |   Role: Primary Engineer
Manuscript   |   Dataset   |   Jupyter Notebook   |   Conversion Code


Wrote custom code for handling the output of a unique microscopy rig, including an electrically tunable lens capable of acquiring images at variable (but precisely measured) depths.

Published a total of 10 TB of C. elegans microscopy data on the associated NIH data archive.

Showcased reproduction of key figures from the associated manuscript through an interactive Jupyter Notebook.

Glia Accumulate Evidence that Actions Are Futile and Suppress Unsuccessful Behavior

• Group: Ahrens Lab   |   Location: Janelia Research Campus (HHMI)   |   Modality: Microscopy   |   Role: Primary Engineer
Manuscript   |   Dataset   |   Conversion Code


Wrote custom code for handling the output of a unique microscopy rig coupled with virtual reality environment and some limited electrophysiology responses from peripheral motor nerves.

Published a total of 23 TB of volumetric whole-brain zebrafish microscopy data on the associated NIH data archive.

MICrONS

• Group: Tolias Lab   |   Location: Baylor College of Medicine   |   Modality: Microscopy   |   Role: Supervisor
Manuscript   |   Dataset   |   Jupyter Notebook   |   Conversion Code


Supervised the conversion and publication of a high-value dataset which combined large-scale two-photon calcium imaging with associated electron microscopy reconstructions of the same tissue.

Resulted in the publication of a total 1.2 TB of functional imaging data on the NIH data archive, with region IDs coregistered with the associated electron microscopy datasets.

Miscellaneous (Buzsaki Lab)

• Group: Buzsaki Lab   |   Location: New York University   |   Modality: Electrophysiology   |   Role: Primary Engineer
Conversion Code


Wrote custom conversion code for a dozen previous datasets. Unique aspects of these data collections include temperature-modulating probes, long-term passive recordings of spontaneous behavior, and paired optogenetic stimulation with extracellular electrophysiology.

Published a total of 39 TB of mouse electrophysiology and behavioral data on the associated NIH data archive.

Publications

Journal Articles

• C. J. Gillon, C. Baker, et al. (2025). Open data in neurophysiology: Advancements, solutions & challenges. eNeuro, vol. 12, no. 11. DOI



Review article summarizing the current state of open data sharing in the field of neurophysiology as portrayed by the myriad of presentations and ensuing discussions from the inaugural Open Data in Neuroscience (ODIN) conference at MIT in 2023.

• K. Gunalan, R. Choudhury, et al. (2025). DANDI: Shaping the future of neurophysiology and neuroimage data publishing and exploration through collaboration with the community, standards, and analytic platforms. In preparation.



An in-progress manuscript detailing the cloud architecture, core features, and future plans for the DANDI archive for neurophysiology and neuroimaging data. Includes contributions from the entire extended DANDI team (10+ authors).

• R. Ly, C. Baker, et al. (2025). A practical evaluation of remote access methods for neurophysiology data in the cloud. In preparation.



An in-progress manuscript detailing a series of benchmarks which evaluate the performance of various remote access methods for reading data stored in AWS S3 cloud storage across a range of environmental and machine configurations.

• H. Mayorquin, C. Baker, et al. (2025). NeuroConv: Streamlining neurophysiology data conversion to the NWB standard. Python in Science Conference, 2025. DOI



The seminal article presented at the SciPy conference which describes the years-long effort ofc creating NeuroConv, the automated data conversion tool capable of translating more than 40 distinct data formats used by neurophysiology acquisition devices to the NWB standard.

• M. Hawrylycz, M. E. Martone, et al. (2023). A guide to the BRAIN Initiative Cell Census Network data ecosystem. PLoS biology, vol. 21, no. 6, e3002133, 2023.



Consortium article (with dozens of authors) describing the data ecosystem developed by the BRAIN Initiative Cell Census Network, of which the DANDI Archive is a core component for data sharing and publication.

• C. Baker, E. Froudarakis, et al. (2020). Inference of synaptic connectivity and external variability in neural microcircuits. Journal of Computational Neuroscience, vol. 48, pp. 123–147, 2020.



This paper made up the bulk of my doctoral thesis which explores the relationship between anatomical synaptic connectivity and observed spike train correlations in biophysically realistic systems of spiking neurons.

• C. Baker, V. Zhu, et al. (2020). Nonlinear stimulus representations in neural circuits with approximate excitatory-inhibitory balance. PLoS computational biology, vol. 16, no. 9, e1008192, 2020.



This paper demonstrates how even simple biophysical plasticity rules can give rise to complex nonlinear computations in networks of spiking neurons operating within a semi-balanced regime. Trained a realistic spiking neural network in an unsupervised manner to perform image classification on the MNIST dataset.

• C. Baker, C. Ebsch, et al. (2019). Correlated states in balanced neuronal networks. Physical Review E, vol. 99, no. 5, p. 052 414, 2019.



My very first publication - mathematically derives the asymptotic scaling for spike count correlations in balanced networks of spiking neurons.

Conference Presentations

• C. Baker, G. Flynn, et al. (2024). NWB GUIDE: Simplifying the conversion of neurophysiology data to NWB format. Society for Neuroscience (SfN) 2024.

• C. Baker, S. Weigl, et al. (2023). NeuroConv: Automated conversion of neurophysiology data to NWB format. Society for Neuroscience (SfN) 2023.

• C. Baker, V. Zhu, et al. (2020). Nonlinear computations in semi-balanced networks. Computational and Systems Neuroscience (COSYNE) 2020. Contributed talk (top 4% of abstracts).

• C. Baker and R. Rosenbaum (2018). Inferring connectivity and latent input covariance from spike train correlations. Computational and Systems Neuroscience (COSYNE) 2018. Poster (top 43% of abstracts).

Workshops

• C. Baker, R. Ly, et al. (2024). Neurodata Without Borders and DANDI Archive Tutorial. NWB and DANDI Workshop, Baylor College of Medicine.

• C. Baker (2023). Neuroconv and NWB GUIDE tutorial NWB User Days, Janelia Research Campus.

• C. Baker and R. Ly (2023). Neurodata Without Borders and DANDI Archive Tutorial Pre-conference, COSYNE.

• C. Baker, O. Ruebel, et al. (2023). Neurodata Without Borders and DANDI Archive Hackathon NeuroDataShare, Sainsbury Wellcome Centre.

• C. Baker, O. Ruebel, et al. (2023). Artificial intellgence, machine learning, computing, and visualization in neuroinformatics Open Data in Neuroscience (ODIN), Massachusetts Institute of Technology.

• C. Baker, O. Ruebel, et al. (2023). NeuroConv tutorial NWB User Days, Janelia Research Campus.