Andrew Johnston

WORK HISTORY

EDUCATION

SKILLS

ABOUT ANDREW JOHNSTON

I am an enthusiastic individual with an interest in leveraging machine learning and big data to solve real-world problems. I completed Nanotechnology Engineering at the University of Waterloo, a multidisciplinary engineering field that combines physics, materials science, electrical and computer engineering. I then completed my PhD in Electrical and Computer Engineering at the University of Toronto; my thesis focused on using machine learning techniques to accelerate the discovery of new photonic materials. As part of my PhD program, I have had the opportunity to lead the development of the Alliance for AI-Accelerated Materials Discovery (https://light.utoronto.ca/a3md/). Interfacing with the industry partners of A3MD has given me insight into the discrepancies between academic research and industrial needs, and provided me with an intuition to translate cutting-edge research to tangible outcomes.I am currently employed as a Data Consultant at Validere Technologies, where my role is to connect the business problems of our clients with scalable data science solutions- Extensive experience programming with Python for machine learning, data analysis and big data, gained through several research projects published in peer-reviewed journals- Expertise in semiconductor physics, gained both through courses and original research projects published in peer-reviewed journals- Comprehensive experience programming with Matlab, Visual Basics for Application (VBA), Javascript, Linux- Experience with advanced nanoscale imaging (TEM, SEM, AFM), materials characterizations (Grazing Incidence X-ray Scattering, Transient Absorption, Transient Photoluminescence, Zeta Potential, Ellipsometry, TGA, UV/VIS Spectrophotometry, DLS, SLS and Rheology) and deposition techniques (E-Beam/Thermal Evaporation, Sputtering, Atomic Layer Deposition).