About me

I recently completed my Ph.D. in Bioengineering in Herbert Sauro's lab at the University of Washington where I developed software to readily construct graphs and recurrent neural network models of neural dynamics collected with calcium imaging data. I applied these packages to data collected from the dentate gyrus and the basolateral amygdala in live and behaving mice, in order to study functional connectivity changes in the anxiety circuitry.

I am seeking opportunities to work on neuromodulation or brain-computer interfaces for improving human health, especially to apply adaptive, closed-loop control to improving treatment-resistant mood and anxiety disorders.

A Whole Human

  • Research

    I study neural dynamics using graph theory and machine learning, investigating the anxiety circuitry in collaboration with skilled experimentalists.

  • Software development

    As a computational researcher, I develop Python packages to assist neurobiologists in analyzing their data. I aim to make reproducible and reuseable models.

  • Racing and Outdoor Pursuits

    I am a marathoner and am running my first IronMan soon! I love to boulder and rock climb, backpack, hike, summit mountains, snowboard, and explore the world.

  • Music and Art

    I also enjoy painting portraits, writing poetry and songs, singing, and playing my guitar.

Research Projects

  • cagraph

    cagraph

    cagraph is a Python package designed to construct graph objects of calcium imaging data.

  • carnn

    carnn

    carnn is a Python package designed to construct recurrent neural network models of neural dynamics collected with calcium imaging data.

  • Anxiety circuitry

    Anxiety circuitry

    The functional connectivity in the anxiety circuitry - specifically the dentate gyrus and basolateral amygdala - were studied using the cagraph and carnn Python packages.

Daniel lewis

Daniel lewis

Richard was hired to create a corporate identity. We were very pleased with the work done. She has a lot of experience and is very concerned about the needs of client. Lorem ipsum dolor sit amet, ullamcous cididt consectetur adipiscing elit, seds do et eiusmod tempor incididunt ut laborels dolore magnarels alia.

Resume


Education

  1. University of Washington: Ph.D. in Bioengineering

    2017 — 2023

    Thesis: Representing neurological systems using graph theory and recurrent neural network models
    GPA: 3.91/4.0

  2. University of Wisconsin-Madison: B.S. in Biomedical Engineering

    2013 - 2017

    Certificates: Honors in Research, International Engineering, Biology in Engineering
    GPA: 3.94/4.0

  3. Universitat Politecnica de Valencia

    2016

    Focus: Biotechnology, Biomedical Engineering

Research

  1. Identification of anxiety signatures in the dentate gyrus and basolateral amygdala

    2021 — Present

    Analyzing neural activity collected from the anxiety circuit (dentate gyrus and basolateral amygdala) in live and behaving mice during exposure to anxiety-provoking stimuli with graph theory and recurrent neural network models.

  2. carnn: Python package for building recurrent neural network models of calcium imaging data

    2021 - Present

    Developing a Python package to readily construct recurrent neural network models of neural dynamics collected using calcium imaging in live and behaving mice.

  3. cagraph: Python package for graph theory analysis of calcium imaging data

    2020 - 2023

    Developed a Python package that uses graph theory to study dynamic changes in functional connectivity of neuronal networks with graphs constructed from calcium imaging data of neural activity in live and behaving mice.

Selected publications

  1. V. L. Porubsky, H. M. Sauro. “A practical guide to reproducible modeling for signaling networks.” Methods in Molecular Biology. 2023. DOI: 10.1007/978-1-0716-3008-2_5

  2. V. L. Porubsky, A.P. Goldberg, A. K. Rampadarath, D. P. Nickerson, J. R. Karr, H. M. Sauro, “Best practices for making reproducible biochemical models.” Cell Systems. 2020. DOI: 10.1016/j.cels.2020.06.012

  3. V. L. Porubsky, L. P. Smith, H. M. Sauro, “Publishing reproducible dynamic kinetic models.” Briefings in Bioinformatics. 2020. DOI: 10.1093/bib/bbaa152

  4. V. L. Porubsky and H. M. Sauro, “Application of Parameter Optimization to Search for Oscillatory Mass-Action Networks Using Python.” Processes. 2019. DOI: 10.3390/pr7030163

Skills

  • Python
    90%
  • Systems neuroscience
    90%
  • Artificial neural networks and ML
    70%
  • Quantitative Research
    100%
  • Software Development
    65%