Experience

MIT Materials Research Laboratory

• United States
• Higher Education
• 1 - 100 Employee

• Analyzer-Free Polarization-Sensitive Optical Ptychography (research assistant)

  • Feb 2022 - Present

  - optimized the vectorial ptychography technique: built a new model allowing for the simplification of a physical setup for data collection thus reducing its cost - made a full reconstruction of phases possible in the absence of an analyzer - optimized the vectorial ptychography technique: built a new model allowing for the simplification of a physical setup for data collection thus reducing its cost - made a full reconstruction of phases possible in the absence of an analyzer



Massachusetts Institute of Technology

• United States
• Higher Education
• 700 & Above Employee

• Renormalization in Lattice QCD (research assistant)

  • Aug 2022 - Aug 2022

  - discretizing path integrals for particle scattering by representing spacetime as a 4-dimensional lattice - estimating them numerically for non-Abelian Gauge theories using Monte Carlo methods - performing renormalization of field operators: developing computational methods for dealing with infinities naturally arising in quantum relativistic field theory - discretizing path integrals for particle scattering by representing spacetime as a 4-dimensional lattice - estimating them numerically for non-Abelian Gauge theories using Monte Carlo methods - performing renormalization of field operators: developing computational methods for dealing with infinities naturally arising in quantum relativistic field theory



MIT Materials Research Laboratory

• United States
• Higher Education
• 1 - 100 Employee

• Vectorial Ptychography (research assistant)

  • Jun 2021 - Aug 2021

  - using PyTorch, developed a software for implementing coherent diffractive imaging methods allowing for phase retrieval in vectorial formalism - successfully reconstructed simulated datasets - utilized the technique for studying anisotropic properties of birefringent materials including: collection of diffraction patterns at the optical table samples structure reconstruction using machine learning - using PyTorch, developed a software for implementing coherent diffractive imaging methods allowing for phase retrieval in vectorial formalism - successfully reconstructed simulated datasets - utilized the technique for studying anisotropic properties of birefringent materials including: collection of diffraction patterns at the optical table samples structure reconstruction using machine learning