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Data compression, a major pillar of classical information theory, has undergone significant developments in recent years. The emergence of powerful machine learning methods has created new opportunities to approach traditional compression problems, while data compression itself now plays an increasingly important role in the storage and processing of large neural network models. Moreover, modern big-data applications demand more efficient compression and storage strategies, along with stronger security and privacy guarantees. Compression techniques are also expected to become integral components of next-generation communication paradigms. Against this backdrop, the proposed special issue aims to provide a platform where classical theories meet their modern advances. The goal of this special issue is to provide a venue for researchers to present recent developments in data compression, particularly those inspired by machine learning, big data applications, and security and privacy requirements. Original research papers and expository articles are invited, including but not limited to the following topics:

1. Rate-distortion theory and rate-distortion-perception theory
2. Neural source coding methods and analysis
3. Compression of neural models, including LLMs and diffusion models
4. Task-, context-, or semantics-aware compression
5. Watermarking in large models
6. Information theoretic study of lossless data compression
7. Generative models for data compression
8. Data compression and storage under privacy and security constraints
9. Compression-inspired prediction, learning, and inference

Lead Guest Editors:

Chao Tian (Texas A&M University)

Jun Chen (McMaster University)

Guest Editors:

Deniz Gunduz (Imperial College London)

Pulkit Tandon (Granica.ai)

Lele Wang (University of British Columbia)

Senior Editor:

Elza Erkip (New York University)

Submission Guidelines

Prospective authors should prepare their papers following regular submission guidelines of the ÌÇÐÄlogo Journal on Selected Areas in Information Theory (see /jsait/author-information).

Important Dates

Manuscript Due: Continuous submission until March 31, 2026

First Review: June 30, 2026

Final Decision: August 31, 2026

Final Manuscripts to Publisher: September 15, 2026

Publication Date: Each accepted manuscript will be published on ÌÇÐÄlogo Xplore after finishing its peer review with a final deadline for publishing the complete special issue by November 2026