Sebastian Goodfellow

Background

My research sits at the interface between laboratory experimentation, machine learning (ML) & data science (DS), and geoscience engineering and draws on numerous interdisciplinary research projects, both in industry and academia, that I have worked on over the past decade.

On the fundamental research side, I'm focused on using state-of-the-art laboratory facilities in the Department of Civil and Mineral Engineering to study induced earthquakes related to large-scale fluid injection as part of hydraulic fracturing. This includes conducting triaxial and true-triaxial rock mechanics experiments where detailed measurements of stress, deformation, fluid pressure, ultrasonic velocity & attenuation, and acoustic emission (AE) are collected.  We focus on the calibration of AE sensors to enable quantitative seismology analysis AE waveforms.

On the applied research side, I'm interested in applying ML and DS to solve engineering problems. As AI R&D Lead at a technology startup in the mining section, I worked to bring an AI product to market. It was through this experience that I learned firsthand how challenging it is to deploy a robust and reliable ML model in a production environment. I'm interested in collaborating with industry partners and researchers at U of T to see where this technology could be applied to drive transformative change.

Professional Experience

Senior Research Associate, The Hospital for Sick Children (2017 – Present)

AI Research Scientist, Laussen Labs (2017 – Present)

AI Research & Development Lead, KORE Geosystems (2016 – 2020)

Algorithm Research & Development Lead, Itasca IMaGE (2015 – 2016)

Education and Designations

PhD, Civil and Mineral Engineering, University of Toronto (2015)

MASc, Mechanical and Industrial Engineering, University of Toronto (2010)

BASc, Mechanical Engineering, University of New Brunswick (2008)