Kyle Johnsen

Kyle Johnsen

PhD Candidate
Biomedical Engineering

Georgia Tech/Emory University

SIPLab

Biography

Hello there! I’m a PhD student advised by Chris Rozell at Georgia Tech, developing advanced closed-loop optogenetic control techniques for neuroscience. Specifically, I am applying optimal, model-based control to manipulate population-level variables of neural activity.

I’m fascinated by the biological computational principles and how we can exploit them for next-generation AI/ML technologies. And vice-versa: how we can apply modern ML to neurotech/neuroscience, especially for building life- and time-saving brain-computer interfaces. I plan on graduating in spring 2025 and am looking for an industry research scientist role.

Download my CV (last updated 2023).

Interests
  • NeuroAI: Bridging theoretical neuroscience and machine learning
  • Brain-computer interfaces
Education
  • PhD in Biomedical Engineering, in progress

    Georgia Institute of Technology/Emory University

  • BS in Bioinformatics, 2019

    Brigham Young University

Projects

Cleo: Closed-Loop, Electrophysiology, and Optophysiology experiment simulation testbed
A Python package built around Brian 2 designed as a testbed for bridging computational models and experiments for mesoscale neuroscience. Specifically, it allows for convenient simulation of closed-loop real-time stimulation, electrode recording, 2P imaging, and optogenetics with spiking network models and provides a modular interface to facilitate future additions.
CLOCTools
A set of software to aid in real-time closed-loop optogenetic control. I have been involved in developing/maintaining ldsCtrlEst and supervising the development of lqmpc and nnmpc.
PhD dissertation proposal
Towards Optogenetic Feedback Control of Neural Population Dynamics
‘Step the Brain along a Path’ Lobby Installation
A foray into neuroscience-based music and art
tklfp: Teleńczuk Kernel LFP
A lightweight Python package approximating LFP from spikes alone as in Teleńczuk et al., 2020. Developed for use in Cleo to prototype real-time manipulation of LFP, but hopefully other people will find it useful too.
MMAPPR2: Mutation Mapping from RNA Sequences
The fruit of my undergraduate research in bioinformatics. MMAPPR2 maps mutations resulting from pooled RNA-seq data from the F2 cross of forward genetic screens.

Recent Posts

Publications

(2024). Probabilistic Decomposed Linear Dynamical Systems for Robust Discovery of Latent Neural Dynamics. arXiv.

Cite arXiv URL

(2024). Bridging Model and Experiment in Systems Neuroscience with Cleo: The Closed-Loop, Electrophysiology, and Optophysiology Simulation Testbed. bioRxiv.

Cite DOI URL

(2023). Manifold Contrastive Learning with Variational Lie Group Operators. Transactions on Machine Learning Research.

Cite URL

Contact