Where & When
April 8, 2021
Workshop Objectives and Topics
In honor of Shannon's 105 th Birthday, and in celebration of our recently edited book Advances in Info-Metrics: Information and Information Processing across Disciplines (Chen, Dunn, Golan, Ullah, OUP, 2021), we will have a one-day online workshop to discuss recent advances in info-metrics and information-theoretic inference. The workshop will focus on info-metrics in the 21st century: recent advances, open questions and directions for future research within an interdisciplinary perspective. The aims of the workshop are to provide a forum for the dissemination of new research in all areas of info-metrics and to stimulate discussion between researchers, and students, across fields.
The workshop will consist of invited talks, papers’ presentations, a graduate student session and a panel discussion.
Topics of interest include (but not limited to)
- Modeling and Inference
- Applied Info-Metrics Inference
- Philosophy of info-metrics
- Causal Inference and info-metrics
- AI, Machine Learning, Deep Learning and info-metrics
- Covid-19 and info-metrics
- Inequality and info-metrics
- Min Chen (Oxford)
- Rossella Bernardini Papalia(University of Bologna)
- Amos Golan (American University) Co-Chair
- Nataly Kravchenko-Balasha (Hebrew University)
- Aman Ullah (UC Riverside) Co-Chair
Confirmed Invited Speakers and Discussants
Call for Participation
We encourage interested researchers from across disciplines to submit papers. All papers (and topics) must be related to info-metrics.
We encourage interested students from across disciplines to submit papers to be presented at a special Students’ Session.
What to Submit?
Complete, or draft, papers are preferred, but detailed abstracts are also acceptable.
Monday, January 25.