Dr. Jill Naiman

Assistant Professor

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Biography

Jill Naiman is a Teaching Assistant Professor at the School of Information Sciences, University of Illinois at Urbana-Champaign, with a focus on data visualization and scientific digitization in the context of Astronomy and Astrophysics. She completed her PhD at the University of California, Santa Cruz, where she explored feedback mechanisms in star clusters and the numerical simulations of galaxy formation. Her expertise includes the use of machine learning methods and image processing, particularly in creating educational tools for astrophysical data visualization. Jill has been actively involved in outreach activities aimed at mentoring students and developing open-source visualization tools. Her contributions to the field include several notable publications on clustering-informed cinematics, multiresolution data visualization techniques, and other astrophysical visualization projects. Currently, she is working on projects that transform astrophysical literature into actionable data that can facilitate insights and promote effective data storytelling in libraries. Jill's teaching strategies emphasize engaging and efficient research methods across technological fields.

Research Interests

Experience

Teaching Assistant Professor

2020-08-01 — Present

University of Illinois at Urbana-Champaign • Champaign, IL

Teaching and research in data visualization and scientific digitization.

Visiting Scholar

— Present

NCSA •

Conducting research in data visualization related to astrophysical data.

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.