Ziyi Zhu

Software Development Engineer at Amazon

Canada

About

I graduated from the University of Pittsburgh with a MS degree in bioengineering. I also received my bachelor's degree in engineering science here at Pitt. Through my education, I developed a solid background in mathematics and physics. I am a fast learner and enthusiastic about learning new knowledge and facing challenges. Such characteristics made me a highly interdisciplinary person. My current work is mostly related to image processing and image registration but includes providing programming solutions to the analysis of all kinds of other data as well. I also involved in projects related to finite element modeling as well as inverse modeling with virtual fields method. - GitHub: https://github.com/Ziyi-OBM - Programming and software skills: MATLAB, Python, C++, ImageJ, Linux, Git, Microsoft office. Familiarity with Java, R, Avizo - Engineering knowledge: Digital image processing, digital signal processing, image correlation and registration, machine learning, optimization methods, communication systems, electronic circuits and digital logic, semiconductor physics, crystal structures and diffractions, thermodynamics and phase transformations of materials. - Science and mathematics knowledge: Quantum mechanics, electromagnetism, Lagrangian and Hamilton mechanics, differential geometry, partial differential equations.

Experience

  • Software Development Engineer at Amazon
    Aug 2020 - Present · 6 yrs

    • Amazon Web Services: Developing serverless applications in Typescript with AWS Lambda, AWS Step Functions, AWS DynamoDB, AWS SNS&SQS • Kubernetes: Hosting containerized microservices at scale with Kubernetes, Istio and AWS EKS • Operational Excellence: Maintaining large scale, high availability system. Improving operations by implementing metrics and alarms with Prometheus and AWS CloudWatch • DevOps and CI/CD: Adaptation to the DevOps framework and continues deployment framework

  • Graduate Research Assistant at University of Pittsburgh Swanson School of Engineering
    Aug 2018 - Jul 2020 · 2 yrs

    Laboratory of Ocular Biomechanics • OCT image analysis: Processing and registering 3D OCT and OCT-angiography images to study structural and mechanical changes of the tissue in the progression of glaucoma • 3D Digital Image Correlation (DIC): Applying 3D DIC techniques to compute tissue displacements and strains in OCT images • 2D DIC: Applying 2D DIC techniques to compute strains in fibers under mechanical loading • Software maintenance in Linux: Responsible for troubleshooting and version control of collaborators’ code in Linux via GitHub • Image segmentation with neural network: Deploying Fully Convolutional Network (FCN) in literature to collagen beam segmentation • Publication: Interplay between intraocular and intracranial pressure effects on the optic nerve head in vivo (https://www.sciencedirect.com/science/article/abs/pii/S0014483521003754?via%3Dihub)

  • Research Assistant at University of Pittsburgh School of Medicine
    Jun 2017 - Jul 2018 · 1 yr 2 mos

    Laboratory of Ocular Biomechanics • Statistical analysis: Applying techniques such as bootstrapping, mixed-effect regression to analyze experimental data • Inverse modeling of tissue mechanics: Developing advanced inverse modeling software using virtual fields method to measure the mechanical properties of tissues • OCT Image compensation: Applying image compensation algorithm to enhance OCT images quality

  • Undergraduate Research Internship at University of Pittsburgh Swanson School of Engineering
    May 2016 - Sep 2016 · 5 mos

    Laboratory of Ocular Biomechanics • 3D data visualization: Reconstructed and visualized 3D structures and surfaces in MATLAB from delineations • 3D data analysis: Developed MATLAB programs to compute morphological parameters from biomechanical structure data consisting of 3-dimensional data points • Problem-solving with custom scripts: Developed innovative programs to automate manual data processing steps that otherwise would take hours • Poster presentation and publication: The work was selected to be published in University’s journal “Ingenium” and presented at the university's Science 2017 conference

  • Research Assistant at Nanotechnology Laboratory - University of Pittsburgh, PA
    Jun 2015 - Apr 2016 · 11 mos

    Research experience in the fabrication of Nano-devices based on graphene and conductive polymers Diagnosed the chemical vapor deposition (CVD) instruments to identify software and hardware problems in the automatic control system