Camron Blackburn

camron.blackburn [at]

I am a PhD candidate jointly advised by Prof. Neil Gershenfeld in the MIT Center for Bits and Atoms and Prof. Karl Berggren in the Quantum Nanostructures and Nanofabrication group in the RLE at MIT. My PhD research focuses on ultra-low power computing systems built from superconducting electronic devices. My work spans the full stack of computing system development, from low-level superconducting device physics to high-level architecture analysis. I completed my masters degree in September 2021, with a thesis on asynchronous superconducting digital logic that you can check out here.

Before moving to Cambridge, I lived in NYC working at a data science / software engineer for Veritone, where I built hierarchical deep learning model for various AI tasks - mostly applications in computer vision. And prior to that, I received a bachelors in Physics with high honors from NYU while building an optical tractor beam in Professor David Grier's soft matter research group.

Things I get most excited to talk about (in no particular order):

CBA Courses

physics of information technology | Spring 2022
how to grow (almost) anything | Spring 2022
how to make something that makes (almost) anything | Spring 2021
nature of mathematical modeling | Spring 2020
how to make (almost) anything | Fall 2019

COVID-19 Response : filter material database

CBA spun up a quick response team to the COVID-19 global pandemic - public tracking page is here. I developed an instrument to test the filtration efficiency and pressure drop accross different types of filter material - more on that here. Using the data from this instrument and SEM imaging, I'm generating a databse of filter media with the hope to guide DIY mask material selection and development of new filtration material for PPE - more here. If you have any questions about, application for, or interest in the project - feel free to reach out.