Vahid M.
About Vahid M.
Vahid M. is a Computer Vision and Data Scientist at FM Global with extensive experience in machine learning and programming.
Current Position at FM Global
As of 2023, Vahid M. works as a Computer Vision / Data Scientist at FM Global. The role involves leveraging his expertise in computer vision and data science to develop innovative solutions. His experience with machine learning models and programming in languages such as Python and R is key in his current position.
Previous Roles at 3M
Vahid M. previously held two positions at 3M in St. Paul, Minnesota. From 2021 to 2023, he served as a Senior Data Scientist, focusing on advanced data analysis and machine learning projects. Prior to that, from 2019 to 2020, he was a Research Scientist, contributing to research initiatives in the field of data science and machine learning.
Academic Research Experience at Michigan State University
Vahid M. has extensive research experience from his time at Michigan State University. From 2015 to 2019, he was a Research Assistant at the integrated Pattern Recognition and Biometrics (iPRoBe) Lab, where he engaged in cutting-edge research on pattern recognition and biometrics. Additionally, from 2010 to 2014, he worked as a Research Assistant at the Feig Computational Biophysics Lab, where he conducted research related to biophysics and computational methods.
Educational Background
Vahid M. holds two PhDs from Michigan State University. He earned a Doctor of Philosophy in Computer Science (2015-2020) and a Doctor of Philosophy in Mechanical Engineering joint with Biochemistry (2010-2014). He also has a Master's degree in Aerospace Engineering (2006-2008) and a Bachelor's degree in Mechanical Engineering (2002-2006), both from Sharif University of Technology.
Expertise in Machine Learning and Programming
Vahid M.'s expertise includes developing machine learning models using frameworks like PyTorch, TensorFlow, and Scikit-Learn. He is skilled in programming languages including Python, R, MATLAB, and C/C++. He is also proficient in unit-testing and writing code compliant with Flake8 style guidelines. Additionally, he co-authored a well-regarded book titled 'Python Machine Learning,' contributing significantly to the field.