Faculty/Staff Search

OR

Department/Unit Search

  1. Home
  2. Research
  3. Research Projects
  4. Interdisciplinary Think Tank Projects
  5. Historical Biography and Bibliography at Scale

Historical Biography and Bibliography at Scale

2025-2026

This project investigates AI-assisted collective historical biography to understand how networks of interacting individuals create institutional contexts and operate within them. Using the history of computer algebra and symbolic computation as a case study, the project addresses the grand challenge of understanding and shaping the historical emergence of technoscientific fields. 

Early developments in computer algebra were explicitly connected to artificial intelligence and emphasized hybrid human–machine thinking. Thanks in part to symbolic computation, historians now operate in a research environment where hybrid human-AI teams can increasingly address large-scale historical problems that would be inconceivable using traditional tools alone. 

The project adopts a collective biography approach that focuses on network interactions rather than isolated life stories. These interactions are captured as factoids—assertions made in historical sources—and used to link biography with bibliography. Large Language Models are employed to extract factoids from sources, store them as structured knowledge graphs, and support historical exploration and reasoning. 

In the short term, the project aims to produce new historical understandings of computer algebra and symbolic computation. In the longer term, it aims to develop tools that can be generalized to other technoscientific domains and shared through computational notebooks compatible with contemporary computer algebra systems such as Maple and Mathematica. 

Faculty members: 

  • PI: Rob Corless, Emeritus Distinguished University Professor, Department of Mathematics and Department of Computer Science, Faculty of Science; Department of Philosophy, Faculty of Arts & Humanities 
  • Bill Turkel, Department of History, Faculty of Social Science 

Trainees: 

  • John (Jack) Kausch, PhD Student, Faculty of Information and Media Studies 
  • Uesio Jeremias da Gama Santos, PhD Student, Department of History, Faculty of Social Science 

Pre-print journal article:

Related book in progress:
  • Robert M. Corless and Nicolas Fillion, Perturbation Methods Using Backward Error, Mathematical Modeling and Computation 25