Vahid earned his Ph.D. in Mechanical Engineering, joint with Biochemistry & Molecular Biology from Michigan State University.
Vahid has been actively developping tools and packages for data science. His interests are large scale data analysis, machine learning.
His PhD research involved data mining and statistical analyses of massive datasets from molecular dynamics simulation in order to improve/refine protein structures. During his PhD study, he participated in the refinement category of CASP, in which they were ranked number 1 in CASP10 (2012) and CASP11 (2014). Protein structure refinement is an important step for computer-based protein structure prediction to obtain high-quality structures that are suitable for biological and pharmaceutical studies. Currently, structure determination relies on experimental techniques (such as X-ray cruystallography), however, experimental techniaues are known for being costly and demand long preparation times.
He obtained his B.S. degree in Mechanical Engineering in 2006 from Sharif University of Technology. Then, he pursued to the master's program in Sharif University of Technology, with his research focus in Computational Fluid Dynamics (CFD) and developping efficient parallel codeswith MPI (Message Passing Interface) for a particle-based simulation of rarefied gas flow and its heat transfer in micro-channels.