Michael J. Ryan

Michael J. Ryan

Masters student in NLP

Stanford University

Hi, I’m Michael Ryan and I’m a Master’s student studying Artificial Intelligence at Stanford. This Fall I’m a Course Assistant for CS221: Artificial Intelligence Principles and Techniques.

My research interests include multilingual NLP and fairness in large language models. I am also excited about retrieval augmentation for more trustworthy text generation. My most recent work is on multilingual text simplification and multilingual readability as well as multicultural fairness. Previously I was an undergraduate researcher in Dr. Wei Xu’s NLP X Lab at Georgia Tech.

Have a quick look at my resume!

  • Multilingual Text Generation
  • Simplification and Readability
  • Retrieval Augmented Generation
  • LLM Fairness
  • MS in Computer Science, 2025

    Stanford University

  • BSc in Computer Science (Intelligence & Systems/Architecture), 2023

    Georgia Institute of Technology


Revisiting non-English Text Simplification: A Unified Multilingual Benchmark
Towards Massively Multi-domain Multilingual Readability Assessment
Cloud Computed Machine Learning Based Real-Time Litter Detection using Micro-UAV Surveillance

Work Experience

Software Engineer Intern
May 2022 – August 2022 Seattle, WA
  • Designed and programmed static analysis tool in C++ for identifying security vulnerabilities throughout Windows OS.
Software Engineer Intern
May 2021 – August 2021 Virtual
  • Refactored existing codebase from .NET Framework to .NET Core.
  • Ported server-specific architecture to serverless functional units using Azure Durable Functions.
Software Engineer Intern
May 2020 – August 2020 Virtual
  • Implemented end-to-end testing in GoLang for bike, scooter, and moped rentals by building a simulated 3rd party CRUD API.


Knock Knock: Neural Joke Generation and Classification
A joke generator built on GPT-2 and joke classifier built on BERT for CS4650 Natural Language Understanding.
Knock Knock: Neural Joke Generation and Classification
Sign Assist
Sign Assist is a digital American Sign Language (ASL) interpreter. Using a Kinect camera and computer vision Sign Assist tracks user movements and patterns to detect different signs. Sign Assist can output these signs as both text and speech.
Sign Assist


Honors Program Distinction in Research
Awarded for completing Honors Level Coursework and Approved Research as an undergraduate at Georgia Tech
See certificate
Outstanding Undergraduate TA for Interactive Computing
Awarded for contributions to teaching excellence at Georgia Tech School of Interactive Computing