Summary
Apaar Shanker is a Machine Learning Research Engineer with 11 years of experience building high-performance computational tools and ML systems, currently applying research to real-world problems at a Bay Area startup. He holds a Ph.D. in Computational Science and Engineering from Georgia Tech, where his work spanned ML for materials science, CNNs for PDE simulations, and high-performance C++/MPI code for scientific workloads. Apaar blends deep numerical modelling and production ML—his past projects include an MPI-parallel lattice Boltzmann phase-field solver and a Python MKS implementation used at NIST. Comfortable across Linux, Python, C++, and distributed compute, he has moved research prototypes into scalable code for autonomous vehicles and industry applications. Based in Sunnyvale, he brings a rare combination of academic rigor and hands-on engineering that accelerates ML-driven simulation and analytics.
11 years of coding experience
1 year of employment as a software developer
B.S. and M.S., First Class, B.S. and M.S., First Class at Indian Institute of Science (IISc)
All India Secondary School Certificate, 94.6%, All India Secondary School Certificate, 94.6% at Don Bosco Academy, Patna, Bihar, India
Doctor of Philosophy (Ph.D.), Computational Science and Engineering, Doctor of Philosophy (Ph.D.), Computational Science and Engineering at Georgia Institute of Technology
Senior School Certificate Examination, Physics, Chemistry, Math, 92%, Senior School Certificate Examination, Physics, Chemistry, Math, 92% at DAV Public School, Kota, Rajasthan, India
Hindi, English