About

Work Experience

• Nonlinear Dynamics and Deep Learning Researcher, 

  Aug, 2020 - May, 20254 years 9 months

  Dissertation on Differentiable programming with Nonlinear Dynamics

  • Showed increased expressivity in neural networks through metalearning of activation functions(Published, Patent Pending)

  • Crafted gradient based optimization framework for reconfigurable nonlinear logic gates(Preprint available, Patent Pending)

  • Improved neural network convergence by growing neurons in situ during training(Preprint available, Patent Pending)

  • Controlled noisy chaotic dynamics using self-supervised neural network to configure stochastically integrated complex systems

• Teaching Assistant, 

  Aug, 2020 - May, 20254 years 9 months

  Teaching in tandem with research for the duration of the PhD

  • Taught and graded >100 students/semester in various introductory labs

  • Managed, maintained, and supervised physics undergraduate research labs

  • Managed and supervised undergraduate teaching assistants(7 TAs)

  • Created computational and organizational resources for physics major courses

• High Energy Physics and Deep Learning Researcher, 

  Aug, 2018 - Jul, 20201 year 11 months

  Developing deep learning algorthms for processing ATLAS detector data

  • Developed NLP inspired neural network architectures in PyTorch to process data from the ATLAS Detector

  • Maintained public codebase to compare effectiveness of contemporary techniques

  • Setup integration of model into ATHENA(root/c++) framework

• Applied Superconductivity Researcher, 

  Aug, 2018 - Jul, 20201 year 11 months

  Performed experiments and created analysis pipelines for characterizing superconducting RF cavities

  • Performed and analyzed vertical radio-frequency(RF) tests of superconducting RF cavities in the framework of Fermilab's high-gradient high-Q research

  • Simulated effect of impurity layer on superconductors to compare with theory

  • Achieved a 48x increase in data processing efficiency by automating key sections of the processing pipeline

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