Michelle Star

CV
Projects Research Art Reading About CV

Publications

Evaluating Supportive LLM Behavior Over Multiple Turns across Demographics

Michelle Star

Extended Abstracts of the 2026 CHI Conference on Human Factors in Computing Systems (CHI EA '26).

Auditing Support Strategies in LLMs through Grounded Multi-Turn Social Simulation

Michelle Star, Andrew Aquilina, Yu-Ru Lin

Proceedings of the 2026 International AAAI Conference on Web and Social Media (ICWSM) Workshops.

BPhil Thesis

Evaluating Supportive LLM Behavior Across User Contexts Using Simulated Multi-Turn Conversations

  • Mentor: Dr. Yu-Ru Lin
  • Program: BPhil in Data Science, David C. Frederick Honors College University of Pittsburgh
  • Methods: Multi-turn simulation; NLP sentiment & linguistic tools; Data analysis

I am auditing support variance and bias in LLM support with demographically distinct Reddit communities. Prior work has shown that LLM performance can degrade over multiple turns suggesting that biases not apparent in a single response may emerge over the course of a longer interaction. In this work I will be simulating multi-turn conversations using posts across subcommunities (e.g., r/TwoXChromosomes, r/NonBinary, r/Daddit) to reveal these discrepencies and hopefully add to the greater body of work towards equitable AI support.

Lab and Projects

PICSO Lab

Computational social dynamics and HCI.

  • RA: NLP keyword extraction and classification, weekly research paper reading
  • Recieving mentorship for my independent research thesis
Visit Lab

CivicWatch

Tasks from NLP for legislative transparency and policy communication, to front end interface design

  • Extract and classify political discourse on social media
  • Project focusses on relief in the misinformation epidemic
View NLP Script

AccessiRide

System to easily discover Wheelchair Accessible Vehicles near you with LLM agents that will contact providers for you.

  • 1st place, Wireless Innovation Hackathon for Accessibility
  • Created working prototype that was developed in consultation with a person from the disability community
Case Study

Industry & Applied

Latitude AI (Ford)

Data pipeline of road work zones for autonomous vehicles.

  • Pulling information from open-source data from all over the US and analyzing the information to create safer self-driving cars.

Osher Lifelong Learning Institute

UX/UI redesign for modernity and accessibility for an older audience.

  • Researching insufficiencies in current website, making information screen reader friendly, creating an intuitive website flow.

Talks & Recognition

Downloads

CV (PDF)

PhD Advising Fit

Seeking research support in Human-AI Interaction, accessible and assistive technologies, and human connection systems with technology. I am excited to learn new things in the ever evolving field of technology and make a real impact on humanity.