Graham Antoszewski

Background

About Graham Antoszewski

My first love was mathematics, modeling and solving real-world problems. I was eventually drawn to cannabis for its healing properties as I sought help with a chronic condition, Wilson’s disease. I seek to bring data science and machine learning methods into the cannabis space, grounded in math and physics but with a passion for the plant. I wish to advance cannabis research, cultivation, and regulation through data and evidence-backed approaches.I’m currently a SIPS professional masters student at Cornell University focusing on Cannabis Science. Advised by Dr. Heather Grab and in partnership with Mariposa Technologies, I am investigating non-invasive detection of nutrient deficiency in live hemp! I’ve come back to higher education with a goal to use data science and modeling skills to help solve analytical problems within the cannabis space. Previous work experience in geospatial satellite imaging, specialties in deep learning and computer vision. Experience coding in Python & MATLAB, use of GitHub environment, and novel algorithm development.2018 Master's graduate from the interdisciplinary Applied Mathematics program (AMSC) at University of Maryland. Coauthor of a research paper regarding Nonnegative Matrix Factorization in the presence of shifted basis vectors published by NPJ Computational Materials.2015 Bachelor’s graduate in Mathematics and Physics from UMBC. Contributed to research of Maryland’s offshore wind energy resource using Doppler Lidar contact me through email at graham.antoszewski@gmail.com.