Doug Ollerenshaw

Doug Ollerenshaw

Computational Scientist • Engineer

I'm a computational scientist bridging the domains of neuroscience, data science, machine learning and engineering. My work focuses on developing data-driven solutions that help us understand complex biological systems.

I hold a PhD in Biomedical Engineering from Georgia Tech and Emory University, where I bridged engineering principles with neuroscience research. I subsequently spent eight years at the Allen Institute for Brain Science, where I worked on a team developing large-scale pipelines for neuroscience data, contributing to open platforms that serve the global research community. Recently, I've brought this expertise to industry startups, where I've applied machine learning and data science to decode complex biological signals, translating research innovations into practical solutions.

Based in Seattle, I love to spend my free time exploring the Pacific Northwest with family and friends. You'll find me skiing in the winter, hiking in the summer and running or riding my bike pretty much year round.

Featured Projects

CodeAIde

An AI-powered coding assistant that streamlines Python development through natural language interactions. Users can write, execute, and debug code directly in the application without managing environments or dependencies. A great tool for beginners and for quickly prototyping ideas.

  • Natural language code generation and modification
  • Integrated speech-to-text - Just click the microphone icon and describe what you want to do
  • Integrated code execution environment
  • Automatic error handling and AI-assisted debugging
  • Support for Google, OpenAI and Anthropic APIs
CodeAIde Screenshot

figrid

A lightweight Python library that simplifies the creation of publication-ready multi-panel figures. Built as a wrapper around matplotlib, figrid provides an intuitive interface for arranging and styling complex scientific visualizations with precise control over layout and formatting.

Sample figure created with figrid

Allen Institute Visual Behavior 2P Project

During my time at the Allen Institute, I worked as a core member of the team to develop and build a large scale data acquisition and processing pipeline consisting of optical recordings of neural activity during visually guided behavior. Recordings were obtained from thousands of neurons in hundreds of imaging sessions using two-photon microscopy, providing access to simultaneous activity across the visual cortex while mice performed a visually guided change detection task. This dataset is now available to the public and can be used to answer questions about the relationship between activity in genetically defined cortical cell types, visual stimuli, and behavior.

Screenshot of Allen Visual Behavior website