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Hey there!

Hanna Jiang


Pursuing BS/MS from the University of Massachusetts Amherst. My interests include fullstack, cloud computing, and machine learning.

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About Me

  • I've always been fascianted by the world around me and my interested in human cognition and perception led me to computer science. From human cognition to artifical cognition, my journey has taken me to internships in academia and industry.
  • Languages: Python, Java, C/C++, JavaScript, TypeScript, HTML/CSS, SQL, R, Go, Shell Scripting
  • Libraries: Pandas, PyTorch, TensorFlow, NumPy, Matplotlib, OpenCV, Scikit-Learn, Keras
  • Tools and Frameworks: AWS, Azure, Google Cloud Platform (GCP), ReactJS, NodeJS, Flask, Django, Git, Docker, Kubernetes, Rest API, GraphQL, FastAPI
  • Name: Hanna Jiang
  • Hometown: Lexington, MA
  • Email: hannajiang@umass.edu

Experience

Amazon Web Services

Software Development Intern

JUN 2024 - AUG 2024

  • Collaborated with the ELB Orchestration team to design and implement diagnostic tools resolving recurrent throttling issues.
  • Developed Java packages for automated throttling systems using AWS services like Lambda, API Gateway, and CloudWatch.
  • Built 5 real-time dashboards using CloudFormation and Grafana, achieving $1M/month savings across all regions.

    • Lab for Advanced Systems Software and Sleep, UMass Amherst

    Software Engineering Intern

    JUN 2023 - AUG 2023

  • Developed a data analytics and visualization web dashboard using Streamlit to help users study their sleep data.
  • Organized and analyzed sleep data by using Pandas dataframes and generated charts using Matplotlib and Plotly.
  • Managed and organized participant data using REDCap and executed data quality checks using SQL.

    • Lab for Internet-scale Distributed Systems, UMass Amherst

    Undergraduate Research Volunteer

    JUN 2023 - AUG 2023

  • Spearheaded the development of Instant-NGP, innovatively improving real-time training for Neural Radiance Fields (NeRF) and amplifying the efficiency of novel view synthesis in Ringmaster under Dr. Ramesh Sitaraman.
  • Engineered an effective algorithm and compact neural network, substantially increasing training and rendering speed, while successfully implementing a scalable multi-resolution hash encoding method.

    • Neuro Learning and Performance Lab, UMass Amherst

    Undergraduate Research Assistant

    DEC 2021 - MAY 2022

  • Developed and implemented machine learning models and Bayesian inference techniques using MATLAB and Python to analyze eye-tracking and multimodal data in a cognitive science lab.
  • Conducted comprehensive data preprocessing, statistical analysis, and interpreted complex findings to illuminate cognitive behaviors and decision-making processes.

    • Work

    Discover my projects, where creativity meets innovation

    Contact Me

    Ask a question or just say hi

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