About

RUEI-JIE (RACHEL) CHANG

M.A. Digital Texts and Culture

I am an M.A. student in Digital Studies of Language, Culture, and History at the University of Chicago. My research examines the cultural and literary history of imaginaries of machine intelligence and the epistemologies of large language models.

Methodologically, I combine close reading with computational analysis. I build and curate structured textual corpora, encode materials in TEI, design metadata schemas, and apply machine learning and other quantitative methods to trace conceptual shifts across time. My approach is both technical and critical: I am interested not only in what models reveal, but also in how their assumptions structure interpretation, and how editorial decisions in data preparation shape the worldviews reflected in computational outputs.

Ruei-Jie Rachel Chang

Education

  • 2025 – 2027

    M.A. in Digital Studies of Language, Culture, and History (DIGS)

    Two-year concentration with Thesis in Digital Texts and Culture

    University of Chicago (UChicago), Illinois, US

  • 2020 – 2025

    B.A. in Foreign Languages and Literatures (DFLL)

    Certificate Program in Women's and Gender Studies Research

    National Taiwan University (NTU), Taipei, Taiwan

  • 2023 – 2024

    Exchange: College of Letters and Science (UCEAP Program)

    English and Comparative Literature

    University of California, Santa Barbara (UCSB), California, US

Skills & Tools

Languages

  • English
  • Mandarin
  • French
  • Japanese
  • Latin

Programming Languages

  • Python
  • JavaScript

Databases

  • SQLite
  • Neo4j

Web Technologies

  • HTML
  • CSS
  • Svelte

Research Areas

Literary History & Cultural Theory

Close reading across traditions, tracing how ideas travel across time.

Machine Consciousness & AI Imaginaries

Cultural histories of how machine minds are imagined across literature and technological discourse.

Media Archaeologies of Artificial Intelligence

Automata, early computers, and the long history of imagining intelligent machines.

Large Language Models & Epistemology

How probabilistic language models produce meaning, how scale reshapes interpretation, and how computational infrastructures influence what counts as knowledge and representation.

Critical Theory of AI & Subjectivity

Drawing on feminist and queer theory to examine how artificial intelligence reconfigures embodiment, normativity, and forms of knowledge.

Computational Literary Studies

Discovering patterns across large textual corpora using machine learning, network analysis, and other computational methods.

Corpus Building & Digital Editing

TEI encoding, metadata schema design, and corpus curation for structured literary and historical materials.