Dr.Farshad Nasiri is the local instructor lead for the Data Science Immersive (DSI) program at General Assembly in Washington, DC. He received his B.S. from Sharif University of Technology in Tehran and his Ph.D from George Washington University in mechanical engineering where he applied machine learning tools to predict air bubble generation on ship hulls. Prior to joining General Assembly, he worked as a computational fluid dynamics engineer and a graduate research assistant. As the DSI instructor, he delivers lectures on the full spectrum of data science-related subjects.
Farshad is interested in high-performance computing and implementation of machine learning algorithms in low level, highly scalable programming languages such as Fortran. He is also interested in data science in medicine specifically preventive care through data collected by wearable devices.
Favorite Data Books:
- A Modern Introduction to Probability and Statistics: Understanding Why and How – F.M. Dekking
- An Introduction to Statistical Learning – Gareth James
- Introduction to High Performance Computing for Scientists and Engineers – Georg Hager