Hossein Niyazi
About Hossein Niyazi
Hossein Niyazi is a Graduate Research Assistant at The George Washington University, where he has worked since 2016. He holds a Bachelor's degree in Physics from Sharif University of Technology and a Ph.D. in Physics from The George Washington University, along with a Graduate Certificate in Data Science.
Work at The George Washington University
Hossein Niyazi has been employed at The George Washington University since 2016. He holds dual roles as a Graduate Research Assistant and a Graduate Teaching Assistant. In these positions, he engages in research and teaching activities, contributing to the academic environment. His work involves the development of computer programs for Monte Carlo simulations in particle physics, as well as statistical analysis of physical observables.
Education and Expertise
Hossein Niyazi completed his Bachelor's degree in Physics at Sharif University of Technology from 2011 to 2015. He then pursued advanced studies at The George Washington University, where he earned a Doctor of Philosophy (Ph.D.) in Physics from 2016 to 2021, a Master of Philosophy (MPhil) from 2016 to 2018, and a Graduate Certificate in Data Science from 2018 to 2019. His education reflects a strong foundation in physics and data science, with a focus on computational methods.
Research Contributions
Niyazi has published peer-reviewed papers that focus on statistical analysis programs developed for computing physical observables. His research includes the design and implementation of computer programs using C, C++, and CUDA, specifically for Monte Carlo simulations in particle physics. He has also designed data pipelines utilizing Python and Bash scripts to handle large volumes of simulation data.
Technical Skills and Tools
Hossein Niyazi possesses technical expertise in various programming languages, including C, C++, and Python. He is experienced in using CUDA for high-performance computing tasks. His work involves utilizing state-of-the-art GPU accelerators on GWU computing clusters, which enhances the efficiency of his computational tasks. Niyazi is also enthusiastic about machine learning, deep learning, and natural language processing, indicating a broad skill set in data science and computational physics.