Dr. Peter Darch

Associate Professor

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Biography

Peter Darch focuses on responsible AI, data ethics, and information systems that support Open Science. He leads studies of large research organizations examining how these organizations develop and implement policies, processes, and systems for AI and data-driven research. His research is aimed at shaping policy and tool development for effective, ethical, and transparent research practices. Darch is the lead for the NSF-funded Institute for Geospatial Understanding through an Integrative Discovery Environment (I-GUIDE), a large, multi-year project that builds an AI platform for research. He previously worked as a postdoctoral researcher at UCLA's Department of Information Studies, where he examined the relationships between information systems, data, and collaborative practices in astronomy and earth sciences. Darch holds a Doctorate in Computer Science from the University of Oxford, an MA in History and Philosophy of Science from Durham University, and an MMath in Mathematics from the University of Oxford. He has published research in journals such as Philosophical Transactions of the Royal Society and the Journal of the Association for Information Science and Technology. Darch has developed an undergraduate course on Ethics and Policy in Data Science and has advised doctoral students on technology ethics and data quality.

Research Interests

Experience

Associate Professor

2023-08-29 — Present

University of Illinois Urbana-Champaign • Champaign, IL

Teaching and researching in the fields of responsible AI and data ethics.

Courses

Soc Science Research LIS - IS560OA

Requirements for University of Illinois

Master Program
Requirements
GPA Requirement
Required:3
IELTS
Listening
Required:7
Reading
Required:7
Writing
Required:7
Speaking
Required:7
Overall
Required:7.5
TOEFL
Listening
Required:17
Reading
Required:19
Writing
Required:21
Speaking
Required:20
Total
Required:103
GRE General
Prerequisites
Mathematical background Linear Algebra Calculus
Application Checklist
  • Online application
  • Unofficial transcripts
  • 3 Letters of Recommendation
  • Academic Statement of Purpose
  • Resume/CV
Specialization Notes

GRE is optional for admission to all graduate programs in Statistics. Full status admission requires higher language scores than limited status.